It’s 2027. Maya is nineteen, and she’s directing a feature film.

She isn’t on a soundstage in Burbank or a backlot in London. She’s in her bedroom in Minneapolis, navigating an interface that feels more intuitive to her than driving a car. Maya isn't a filmmaker in the traditional sense. She has no formal training, no industry connections, and certainly no budget.

But she has a story.

With a series of precise text prompts, she generates the establishing shot: a sweeping aerial view of a neo-noir cityscape, drenched in digital rain. She nudges the virtual camera angle, tweaks the color grading from "somber blue" to "electric cyan," and instructs the AI to populate the streets with bustling, synthetic crowds.

When her protagonist needs to deliver the pivotal line, she doesn't call "action." She types the dialogue and specifies the emotional inflection weary, but resolute. The AI renders the scene, complete with synchronized audio and nuanced facial expressions.

Maya is reviewing the fifth iteration of her climax. It’s taken her three hours. A comparable sequence in a traditional pipeline would have taken a team of animators and VFX artists three months.

This isn't science fiction. It’s the immediate, inevitable future of how we tell stories.

We are standing at the inflection point of a fundamental shift in creative production. The rise of powerful generative AI video models is doing more than just "disrupting Hollywood." It is enabling something far more profound: an era of unbounded creativity.

This technology is rapidly dismantling the industrial barriers that have governed entertainment for a century. It is creating a new blueprint where the most valuable assets are no longer access to capital or infrastructure, but a creator's unique vision and their skill in wielding these new tools.

As an expert in workflow automation, I observe these shifts across nearly every industry. My core belief is that technology’s primary purpose is to elevate the human experience. The transformation occurring in filmmaking is perhaps the most visible, exciting, and profound example of this principle in action. The blockbuster movie, once the exclusive domain of multinational corporations, is becoming an achievable goal for an individual with a subscription and the drive to create.

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The Shift: From Gatekeepers to Unleashing

For the past century, the story of filmmaking has been the story of access.

The traditional model is inherently industrial. It’s heavy. It demands massive capital investment: fundraising, studio backing, physical soundstages, specialized equipment, and large, highly specialized crews. This system, by necessity, created gatekeepers. The sheer cost of entry meant that only a select few ideas, deemed commercially viable by executives, could access the machinery required to bring them to the screen.

This wasn't a "problem" to be solved, it was simply the reality of the technology. The process was linear, expensive, and slow.

We are now watching the rapid decoupling of vision from infrastructure. Generative AI is collapsing the production pipeline. The barriers to entry are shifting from the financial to the intellectual and the artistic.

In this new paradigm, creativity itself is the primary currency. The focus is on the "unleashing" of artistic vision. The critical skill set is no longer the mastery of complex, specialized software or the ability to manage a hundred-person crew. It is the clarity, originality, and strength of the creator's idea.

And, crucially, it requires fluency in the new language of creative AI the ability to articulate that vision through effective prompts and intelligent workflows.

This is the rise of the prompt-driven auteur.

The Engines of Creation

The engines driving this revolution are a new class of generative AI known as foundation models. These systems, trained on vast datasets of media, can synthesize novel, high-fidelity moving images from simple text prompts. They are a quantum leap forward, moving from mere image manipulation to the generation of entire scenes with coherent motion and environments.

Two models currently define the state-of-the-art, and they reveal different philosophies for shaping this new creative landscape.

Google's Veo: The Polished Professional

Google has positioned Veo as a high-fidelity, enterprise-ready tool. It generates high-definition (1080p) video and is integrated directly into Google's broader cloud ecosystem, targeting existing professional workflows [1].

Veo's key differentiator is remarkable: native, single-pass audio generation. The model produces synchronized sound including dialogue with accurate lip movements, sound effects, and musical scores—simultaneously with the video frames [1]. This is a massive workflow advantage. It solves a major hurdle in AI filmmaking, where audio has often been a difficult, post-production afterthought. The ability to prompt characters to speak specific lines of dialogue is a significant advance for narrative storytelling [2].

Google is also keenly aware of the societal implications. Every video generated by Veo is embedded with SynthID, an invisible, persistent digital watermark that identifies the content as AI-generated a crucial tool in maintaining digital trust [1].

OpenAI's Sora: The World Simulator

In contrast, OpenAI presents Sora as an engine for raw creative exploration—a tool for simulating the physical world in motion [3]. Sora's most significant advantage right now is duration. It can generate continuous videos up to a minute long, a substantial leap that allows for more complex narrative sequences [3].

The model excels at generating complex scenes with multiple characters and demonstrates strong temporal consistency meaning it maintains visual style and character appearance across multiple shots within a single generated video [3]. OpenAI has also developed the "Sora Video Editor," a suite of tools (like "Remix" for iterating on a scene and "Blend" for transitions) that emphasizes an iterative, creator-driven workflow [4].

OpenAI has been notably transparent about Sora's current limitations. The model struggles to accurately simulate complex physics and lacks a true understanding of cause and effect. A character might bite a cookie, but the cookie remains unmarked [3]. These flaws reveal the next great challenge in this space: building models with a genuine, causal understanding of the world, rather than just statistical correlation.

While Google targets the enterprise with Veo, OpenAI is aiming Sora at the broad base of individual artists and prosumers [3]. This sets the stage for a future where a large advertising agency uses Veo for a global campaign, while a solo creator uses Sora to produce their first animated feature.

The New Creator Stack

While foundation models like Sora and Veo provide the raw power, they are just the engine. A vibrant ecosystem of startups is building the rest of the vehicle the application layer. These are the tools, platforms, and communities that make this power accessible.

They are constructing a new "creator stack."

Runway ML: The Toolmaker

Runway has established itself as a central player, offering a comprehensive suite of AI-powered tools focused on video generation and editing, powered by their flagship model, Gen-4 [5, 6]. Runway is focused on bridging the gap between experimental AI and professional production, offering training on integrating its tools into established visual effects (VFX) pipelines [7].

Perhaps its most influential project is Gen:48, a recurring 48-hour AI film competition [8]. This event fundamentally recalibrates the value proposition of filmmaking. The traditional paradigm involves months, if not years, of painstaking work. Gen:48’s premise is the opposite: translate a complete vision into a finished film within a weekend.

The fact that the winning entries are often coherent and emotionally resonant short films proves that this new mode of rapid, vision-driven production is viable [9]. Speed is the new currency.

Pika Labs: The Accessible Entry Point

Where Runway caters to a professional leaning user, Pika Labs has focused on accessibility and intuition for a broader audience [10]. Pika’s platform allows users to generate video from text or images, offering versatile features like automated lip-syncing, video inpainting (editing elements within a video), and a wide range of aesthetic styles, from photorealistic to anime [11]. Pika serves as the accessible front door to AI filmmaking.

Curious Refuge: The Educator

The third critical pillar is education and community, a role filled by Curious Refuge. Positioning itself as "the world's first home for AI storytellers," Curious Refuge does not build its own tools. Instead, it functions as an essential educational platform, offering courses in AI Filmmaking, Animation, and Documentary production [12]. Their training focuses on professional workflows, prompt engineering, and how to combine the best available AI tools to produce studio-quality projects from scratch [13].

These startups are not just competitors; they are complementary components of an emerging ecosystem. A new filmmaker might begin experimenting on Pika, enroll in a specialized course from Curious Refuge to learn narrative techniques, and finally graduate to Runway's powerful toolset for their most ambitious projects. This structure provides the infrastructure for the "bedroom creator" to not only produce work but also to learn, network, and professionalize their craft.

A New Ecosystem Emerges

The ripple effects of this technological shift are profound, touching everything from the value of physical real estate to the definition of an actor's career. We must explore these changes with a balanced perspective, focusing on the evolution of the ecosystem rather than a simplistic narrative of destruction.

From Soundstages to Servers: The Economic Restructuring

The core economic promise of AI is its ability to reduce the industry's reliance on physical production. Morgan Stanley Research estimates that generative AI could cut overall TV and film production costs by as much as 30% [26]. These savings come from replacing physical production with digital components: generating realistic environments instead of traveling on location, and creating digital assets instead of building expensive sets [26].

This poses a direct, long-term challenge to the value of massive physical infrastructure. As the industry moves toward "Synthetic Media" content partially or entirely generated by AI the economic justification for maintaining vast, expensive studio lots will come under pressure [27]. Real estate matters less.

We can already see this happening in pre-production. Location scouting, traditionally a costly endeavor, is being revolutionized by AI platforms that can digitally match script requirements with global locations, delivering cost savings between 5-20% [28]. As studios become comfortable using AI to digitally scout locations, the next logical step is to use AI to digitally create them.

The investment landscape is shifting fundamentally. The global "AI in Film" market is projected to grow tenfold, from $1.4 billion in 2023 to $14.1 billion by 2033 [28]. In this new landscape, the most valuable assets are no longer square footage of soundstage space, but petabytes of proprietary training data and access to massive computing power. Data matters more.

The Human Element: Redefining Labor and Artistry

This transformation is profoundly human. It impacts the livelihoods and workflows of creative professionals. But far from being passive victims, Hollywood's labor unions have taken a proactive stance.

The 2023 Hollywood strikes established crucial precedents. SAG-AFTRA successfully argued that the use of a performer's likeness or voice to train AI, or the creation of a digital replica, are mandatory subjects of bargaining [20]. Central to the new protections is the principle of "informed consent" and fair compensation for the creation and use of a "Digital Replica" [21].

This is giving rise to a new business model: the actor as a licensable digital asset. Performers can now license their "talent avatars" highly realistic digital doubles for use in various media [22]. This creates new revenue streams, allowing actors to work on multiple projects simultaneously without the physical constraints of being on set. In this new landscape, consent is the new currency, transforming a performer's identity into a scalable piece of intellectual property [22].

Creative roles behind the camera are also evolving. The shift is moving from manual execution to strategic oversight and creative direction—from the how to the why.

For VFX Artists, AI is automating labor-intensive tasks like rotoscoping and rendering. Ed Ulbrich, President of Production at Metaphysic, predicts this will allow artists to "focus more on the creative elements," evolving their roles from digital laborers to creative directors managing a suite of AI tools [23]. Similarly, Film Editors will use AI to handle technical tasks like syncing audio and generating rough assemblies, freeing them to concentrate on the nuanced art of storytelling, pacing, and emotional arcs—the things that make a film feel human [25].

But we have to approach this evolution with open eyes and genuine empathy. There is a real systemic risk. A 2025 report from Luminate Intelligence highlights the "erosion of entry-level jobs" as a major consequence of AI adoption [24]. The tasks where young artists historically learned the fundamentals basic digital cleanup, coloring, etc.—are the most likely to be automated. If the industry automates the bottom rungs of the career ladder, it risks severing its own talent pipeline. This is a challenge that demands thoughtful, human-centric solutions [24].

The Empire Adapts: Hollywood's Strategy of Efficiency

While startups embrace AI as a revolutionary creative tool, the incumbent powers of Hollywood are approaching the technology with a distinctly different strategy: optimization, efficiency, and cost containment.

The Walt Disney Company has established an internal AI task force with an explicit mandate to "help control spiraling production costs" [14]. Netflix Co-CEO Ted Sarandos has framed AI as a tool to "enhance filmmaking processes" and "manage production costs effectively" [15]. Netflix has already used generative AI on its series The Eternaut to complete a complex VFX sequence "ten times faster and at a significantly lower cost" than traditional methods [16].

The incumbents see AI as a way to optimize the factory, not to redesign it. A 2025 Deloitte prediction forecasts that major studios will dedicate less than 3% of their production budgets to generative AI for actual content creation, focusing instead on back-end functions like marketing, localization, and planning [17].

Simultaneously, studios are waging an aggressive legal war to control the terms of AI's integration. Warner Bros., Disney, and Universal Pictures have all filed copyright infringement lawsuits against AI generators like Midjourney, alleging the unauthorized use of their IP for training [18]. Universal has even begun adding explicit warnings to the end credits of its new releases stating the motion picture "may not be used to train AI" [19].

This strategy is designed to create a powerful legal moat. The endgame for Hollywood is not to halt AI, but to monopolize its most valuable resource: high-quality training data. Their goal is to become the sole gatekeepers and licensors of their vast archives, transforming their intellectual property from a content library into the foundational, high-margin raw material of the AI era.

The Era of Unbounded Creativity

The convergence of these forces technological advancement, economic restructuring, and evolving creative workflows has created a perfect storm. We are not witnessing an incremental change, but a fundamental decentralization of creative power.

Powerful, accessible generative tools are being placed in the hands of a global community of creators at the precise moment that the traditional industry is focused inward on defensive cost-cutting. The economic foundations of large-scale physical production are beginning to erode.

This confluence creates the conditions for the biggest movies of 2027 to be made not on a sprawling studio lot, but in a bedroom.

The prompt-driven auteur, armed with a subscription to an AI model, skills honed through online communities, and a unique creative vision, can now compete on the merits of their ideas and their speed of execution.

While technological shifts are often gradual, the pace of AI implementation is accelerating much faster than previous transformations. The movie industry is the most tangible, visceral example of this shift in action.

The ultimate outcome is not the "death of Hollywood," but its transformation—and expansion. We are entering a future of unbounded creativity, where the means of high-quality visual production are democratized. This will likely lead to a Cambrian explosion of new voices, new stories, and new forms of entertainment that were, until very recently, impossible to imagine.

The tools are here. The shift has begun.

And creators like Maya are already hitting 'render.'

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REFERENCES USED

[1] Google's Veo 3 AI video creation tools are now widely available, accessed September 8, 2025, https://www.artificialintelligence-news.com/news/google-veo-3-ai-video-creation-tools-now-widely-available/

[2] How To Use Google VEO 3 To Make Realistic Videos (Easy Step-By-Step Tutorial), accessed September 8, 2025,

[3] Sora | OpenAI, accessed September 8, 2025, https://openai.com/index/sora/

[4] What Is OpenAI's Sora? How It Works, Examples, Features ..., accessed September 8, 2025, https://www.datacamp.com/blog/openai-announces-sora-text-to-video-generative-ai-is-about-to-go-mainstream

[5] Runway | Studios, accessed September 8, 2025, https://runwayml.com/studios/

[6] RunwayML - MIT - Docubase, accessed September 8, 2025, https://docubase.mit.edu/tools/runwayml/

[7] Tools for human imagination. - Runway, accessed September 8, 2025, https://runwayml.com/ai-for-vfx

[8] Gen:48 Aleph Edition - Runway, accessed September 8, 2025, https://runwayml.com/gen48

[9] 10 BEST Must-See AI Short Films From Runway ML Gen:48 Contest - YouTube, accessed September 8, 2025,

[10] Pika, accessed September 8, 2025, https://pika.art/

[11] Pika Labs Review: Features, Pros, Cons, & Alternatives - 10Web, accessed September 8, 2025, https://10web.io/ai-tools/pika-labs/

[12] Curious Refuge - The World's First Home for AI Filmmaking, accessed September 8, 2025, https://curiousrefuge.com/

[13] Free AI Filmmaking Course | The Best Intro to AI for Filmmakers - Curious Refuge, accessed September 8, 2025, https://curiousrefuge.com/start-here

[14] Disney Has An AI Taskforce That Is Looking For Ways To Trim ..., accessed September 8, 2025, https://www.cartoonbrew.com/tech/disney-ai-taskforce-ballooning-production-budgets-231315.html

[15] Netflix Lays Down the Law: New Rules for Using Generative AI - Just Think AI, accessed September 8, 2025, https://www.justthink.ai/blog/netflix-lays-down-the-law-new-rules-for-using-generative-ai

[16] Netflix Embraces Generative AI: A Turning Point for Visual Effects and Budget Filmmaking, accessed September 8, 2025, https://generativeaiawards.com/netflix-embraces-generative-ai-a-turning-point-for-visual-effects-and-budget-filmmaking/

[17] Large studios will likely take their time adopting generative AI for content creation. Social media isn't hesitating. - Deloitte, accessed September 8, 2025, https://www.deloitte.com/us/en/insights/industry/technology/technology-media-and-telecom-predictions/2025/tmt-predictions-hollywood-cautious-of-genai-adoption.html

[18] Warner Bros. sues Midjourney for AI-generated images of Superman, Bugs Bunny and other characters, accessed September 8, 2025, https://apnews.com/article/warner-bros-midjourney-ai-copyright-lawsuit-dc-studios-b87d80d7b4a4dfdcf0ee149d30830551

[19] Universal Pictures Adds Warning to AI Companies in Film Credits - Futureweek, accessed September 8, 2025, https://futureweek.com/universal-pictures-warns-ai-companies-against-using-its-content/

[20] SAG-AFTRA maintains that the right to digitally replicate a performer's voice or likeness to substantially manipulate a performa, accessed September 8, 2025, https://www.sagaftra.org/sites/default/files/sa_documents/SAG-AFTRA%20AI%20Letter.pdf

[21] Digital Replicas 101 What You Need to Know About the 2023 TV/Theatrical Contracts General Information - sag-aftra, accessed September 8, 2025, https://www.sagaftra.org/sites/default/files/sa_documents/DigitalReplicas.pdf

[22] Talent Avatars: Actors Licensing Digital Doubles to Ads, accessed September 8, 2025, https://beverlyboy.com/film-technology/talent-avatars-actors-licensing-digital-doubles-to-ads/

[23] AI/VFX ROUNDTABLE: REVOLUTIONIZING IMAGERY – THE FUTURE OF AI AND NEWER TECH IN VFX - VFX Voice, accessed September 8, 2025, https://www.vfxvoice.com/ai-vfx-roundtable-revolutionizing-imagery-the-future-of-ai-and-newer-tech-in-vfx/

[24] Animation Jobs In The Age Of AI: Revelations From Luminate Intelligence's 2025 Special Report - Cartoon Brew, accessed September 8, 2025, https://www.cartoonbrew.com/tech/animation-jobs-in-the-age-of-ai-revelations-from-luminate-intelligences-2025-special-report-253718.html

[25] A Look at What The Future Holds for AI in Video Editing - ECG Productions, accessed September 8, 2025, https://www.ecgprod.com/what-the-future-holds-for-ai-in-video-editing/

[26] AI in Media and Entertainment: Cost Reductions & Risks | Morgan ..., accessed September 8, 2025, https://www.morganstanley.com/insights/articles/ai-in-media-entertainment-benefits-and-risks

[27] Three predictions for the future of media distribution in the age of AI - DVB, accessed September 8, 2025, https://dvb.org/news/three-predictions-for-the-future-of-media-distribution-in-the-age-of-ai/

[28] AI in Film Production: Why Location Intelligence is the Next $14B Investment Frontier, accessed September 8, 2025, https://massif.network/filmmaking/ai-film-production-location-intelligence-investment/

If you are mad at AI, it’s output and it’s run arounds you are not alone. I do this professionally and it can get to me. This article will show you how you can achieve the highest amount of output quality within the possiblities your plan allows.

The Executive Summary

1. The best performing AI Models & Agents are specialized

2. Achieving a high levels of efficiency requires a focused context

3. If you are trying to achieve too many overall goals in one model instance (chat) your context grows too high

4. Seperate your tasks to different Models that work well together.

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A Brief Overview Of My Credentials

As many of you likely know my company Saiwala Consulting is a fractional CTO service company. I provide CTO services to businesses who otherwise would not have the know-how or the budget to have their own tech team. I have been doing this since 2015.

Some of my projects require no code solutions, some low code solutions and some require a full on development team. One of my companies that I cofounded is Knowetic.ai. Basically what we built is our own AI Agent that helps Behavior Analysts in the autism healthcare space make better decisions.

When our customers chat with our AI all they know is that they are talking to KnowYeti. What they do not know is that in reality they are talking to one model that interacts with other models, which interact together in a system.

Each individual instance of a model has a specific task. When the task is completed it passes the output of the task on to another model that does something else with it, which then passes it on to another until at some point a final model formats the output.

Think of this like a old school ford style assembly line of AI models doing a specifc task until one finally puts it all together, hands it to the sales person (the model our custom has been chatting with) and then the final output is given back to the customer.

The best performing AI Models & Agents are specialized

In the article: “Best practices for building agentic AI systems” Shayan Taslim breaks it down as follows:

After studying OpenCode and other systems, I’ve found three ways to specialize agents that make sense:

By capability: Research agents find stuff. Analysis agents process it. Creative agents generate content. Validation agents check quality.

By domain: Legal agents understand contracts. Financial agents handle numbers. Technical agents read code.

By model: Fast agents use Haiku for quick responses. Deep agents use Opus for complex reasoning. Multimodal agents handle images.

Don’t over-specialize. I started with 15 different agent types but now I have 6, each doing one thing really well.

Basically what this means is do not let a research agent do math. Do not let a creative agent do research. Do not let a legal agent crunch financial numbers. Give one instance of a model a specific task and then hand the output to another in case you need a system.

You can mimick the exact same behavior in the front end UIs of ChatGPT, Claude and Gemini. You do not need to know how to code.

The first thing you need to do is evaluate each task you want AI to complete for you from a lense of: “How many different capabilities and domains will this require?“ In other words you need to think through your goal a little before you just start prompting.

Anytime you have a Google type question you do not need to think, just ask. But when you need the AI create a more complex output it is very likely that at the current state of technology you will likely require at least two instances.

For example if you use AI to support your creative writing and you also generate image content with it you should use two different models (chat instances). Your one chat will always be used to build out writing for you. When the output is completed you feed a condensed version to the chat that creates the images for you.

Of course the type of writing will determine if you need two models for that task and then have a third model that writes it into a cohesive text for you. For example one model writes content, the other model does financial modeling and the third model builds it into a great sounding article based on your tone of voice, style etc.

The next advantage you automatically inherhit from this system is that each model (chat instance) has a specialized context.

Achieving a high levels of efficiency requires a focused context

AI performs at its best when it has a clear objective and a focus context. In essence this means do not mix tasks together and provide it with context important only for the task you are trying to accomplish.

By keeping all your tasks in one model (one chat window) you are continously expanding upon it’s knowledge. This will make your output a bit better every time. Now, depending on the plan you have (Free, Pro, Plus, Ultra etc.) the context can get too large. We will discuss what to do here later.

AI requires context to be able to perform your task properly. So it is important to give it as much information as possible pertaining to your task. I think many front end users have not yet grasped this completely. They understand the concept, but lack in execution. This again is why keeping one specific chat for one specific task is such a great way to achieve this.

If you are trying to achieve too many overall goals in one model instance (chat) your context grows too high

I just mentioned that at some point in time even a focused chat window will run into context issues. This is due to the amount of compute that is allocated to your chat. The less you pay, the less you have basically. So keeping your context to the point is important.

If you use one chat for multiple tasks you not only add to the overall context, but you’re also forcing the model to reiterate over different topics within it’s training data, or search the internet for more topics. This adds to your context window and sort of dilutes your AIs focus.

This is perfectly relatable though. You would do the same thing if you were asked to multi task constantly through different problem sets. It would likely be stressful, annoying or outright now possible. Your performance would decrease overtime. The same thing happens with the AI.

Seperate your tasks to different Models that work well together.

So the solution is to have dedicated chats for specific tasks. Sub-divide these into further specialized tasks if needed. Organize your chats into folders. However you feel comfortable organizing it. I have a chrome extension for Gemini which allows me to create folders and sub-folders. I have one called Health, Investing, one for each of my clients.

Now for more complex tasks that require several models tell the AI that it is one model in a sequence and that the final output should be written for another instance which will format the output, or calculate something or whatever it is. This is the starty of a system.

In the example above from Shayan Taslim you have a horizontal flow of information. Agent 1 (chat 1) for example writes you ideas for an article, agent 2 (chat 2) builds them into content and agent 3 (chat 3) generates images for you. The chat 4 (in this case the reducer) takes all of it and makes it into a cohesive post.

Now in development world the instructions are coded into the agent and it happens automatically. You can achieve the same thing by copying the output and pasting it into the next chat. Just instruct the AI to always generate it as an LLM formatted output so it is a prompt as well as the content you need.

The diagram above is just an example flow. This can take on any kind of complexity depending on your goal. Just think through your goals properly, divide them into tasks and then decide how to best handle it.

Things You Should Always Tell your AI To Do In Every Chat

There are some instructions I find highly useful, especially in a front end chat window context. Your AI is quite smart, but without proper guidance it can also be quite annoying. Here is a list of useful tips to always have your AI do.

Instruct your AI to keep track of ABC

As you work on your tasks make sure your AI knows to keep track of the important things. I for example always have the AI manage a running Checklist of all tasks with a lamens explanation of what this task is about. I use this for two purposes.

1. I alwasy have a quick way to reference the entire project in a checklist format.

2. I can quickly have the AI write me an answer or a report for my clients.

Goodbye Asana, Trello.

Tell your AI to remember your agentic system

I mentioned this above already, but make sure your AI knows which link in the chain it is in. I cannot stress how much better that makes your final output. Context is king. Provide it for everything that is relevant.

Tell your AI what type of tone / style of communication you want

I find this an incredible way to interact with AI. I like to the point, short answers. Sometimes I need an explanation. My AI and I have an understanding about how we communicate. I have several modes that I can activate just by telling it to:

1. Default mode (short, to the point, factual)

2. Humor mode (interject some humor, to break up the feel of the work day)

3. Teacher mode (when I activate this the AI automatically goes into more long form explanations of codes, setups or software. This is quite useful). Now with guided learning or study mode, this is on steroids.

You can even create a mode for each of your chats. It all depends on how you want to handle it. Obviously on a free plan, your memory context is quite limited so this may become more difficult to manage.

What To Do When Your Context Gets Full

Ever seen ChatGPTs UI lag and glitch? Ever had Gemini answer old questions you asked 20 minutes ago even though you asked something completely different? Ever felt like the AI is looping back to the same wrong answers over and over again?

Your context just got too large. The allocated compute power has run out. This makes perfect sense. It’s like asking you to do your most complex math on no sleep and no food. You need to transition.

This is where it comes in very handy if you told your AI to keep track of the most important points of the chat in case you ever needed to hand it off to another chat. Well that time has now come. So ask it to write you a transition report that another LLM can pick up quickly.

The smaller the project the easier this is of course. If you have hours upon hours of chat the report will not get you 100% there. This is why the report should always conclude with a prompt: “Since you are taking over this project, please ask me as many questions as needed so you have a comprehensive context. Is anything unclear? Anything you need to know?“

For some of the best articles on how to prompt effectively you can check out Wyndo.

I hope that this helps you think about context and tasks differently. I hope this content inspired you to take a different approach with your AI. And of course, I hope this actually helped you.

Maria used to measure her day in burnt coffee and stained aprons. For three years, her world was the relentless hiss of the espresso machine, the blur of rush-hour faces, and the gnawing feeling that she was stuck. The pay was just enough to get by, the work was repetitive, and the path forward was… nowhere. Like millions of Americans in the service industry, she was talented, sharp, and hardworking, but her potential was capped by a ceiling made of paper resumes and college degree requirements. She had aptitude, but she didn't believe she had an opportunity.

Then, she saw a job posting that felt like it was from a different planet. It was for a technician role at a company building rocket parts. It didn't ask for a decade of experience or a fancy engineering degree. It asked for curiosity, a willingness to learn, and a desire to build. The company was Hadrian Manufacturing. A few months later, Maria was no longer serving lattes; she was operating a multi-million dollar 5-axis CNC machine, crafting components with a precision measured in microns.

Her story isn't just a feel-good anecdote. It’s a blueprint.

In a world gripped by anxiety over AI and automation-driven job loss, Hadrian is quietly building a powerful counter-narrative. They are proving that technology’s greatest purpose isn't to replace human workers, but to unlock their potential faster than ever before. This isn't a story about robots taking over; it's a story about how the right systems can empower people and, in doing so, begin to solve one of America's most critical economic challenges.

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The Problem: An Industrial Base on Life Support

To understand why Hadrian’s approach is so revolutionary, you first have to understand the crisis it was built to solve. The American advanced manufacturing sector, the same industrial engine that won World War II and put a man on the moon, is, in the words of Hadrian’s CEO Chris Power, a "house of cards."

For decades, the defense and aerospace industries have been propped up by a fragmented network of over 40,000 small, independent "mom and pop" machine shops. An estimated 90% of these vital businesses have fewer than 20 employees. This structure makes it nearly impossible to scale, standardize, or adopt new technology efficiently. They are often running on workflows and machinery that haven’t fundamentally changed since the 1960s, leading to agonizingly long lead times and high error rates.

But the most dangerous vulnerability isn't the technology; it's the people. Or rather, the lack of them.

We are standing on the edge of a demographic cliff. The average age of a lead machinist in the United States is now 63. As this generation of masters prepares to retire, they are taking decades of priceless, undocumented “tribal knowledge” with them. There is no one to take their place.

According to a landmark study by Deloitte and The Manufacturing Institute, the U.S. faces a potential shortfall of 1.9 million manufacturing workers by 2033. Of the nearly 4 million jobs expected to open in the next decade, almost half could go unfilled. This isn't a minor inconvenience; it’s a direct threat to our national security and economic prosperity. How can a nation lead the world in innovation if it can’t build its own inventions?

This is the fear that paralyzes progress. It’s the fear that we’ve lost the ability to make things, that we've outsourced our resilience, and that manufacturing is a dead-end career. As Chris Power puts it, the ultimate test of success is creating a cultural shift where a 17-year-old might one day "brag to their friend at a bar that they got a job in manufacturing." To get there, we don't just need a new policy; we need a new philosophy.

The Philosophical Shift: Betting on People, Not Pedigrees

This is where our work and the core philosophy of building bottom-up systems becomes critical. The traditional top-down approach to hiring is broken. It’s a system built on filtering people out based on credentials they were never given a fair chance to acquire. It looks at a resume from a barista like Maria and sees a lack of experience. It misses the resilience, the attention to detail, and the ability to learn under pressure.

Hadrian’s entire model is built on a simple, yet profound, philosophical shift: Hire for aptitude, train for skill.

This is a direct rejection of the old way. Instead of searching for the few people who already have the perfect resume, Hadrian widens the talent pool to include everyone. They believe that talent is distributed equally across the population, but opportunity is not. Their solution is to create the opportunity themselves.

They built their company around the conviction that they could take "former bus drivers, nurses, UPS drivers, or Home Depot workers" and empower them to do some of an industrial nation's most complex and critical work. This isn't just a clever marketing line; it’s the central pillar of their operational strategy. Internal data shows that "less than 10% of [its] manufacturing team actually stepped foot in a machine shop before their Hadrian interview."

This philosophy changes everything. It reframes the role of a company from a consumer of talent to a creator of talent. When you believe that the most valuable asset you have is the untapped potential of your people, you stop building systems that control them and start building systems that empower them. You focus on removing the pain points that create friction and fear—like the terror of breaking a million-dollar machine—and replace them with tools that build confidence and mastery.

The Journey: A 21st Century Apprenticeship

So how does Maria, the former barista, make the leap to a high-precision machinist in a matter of weeks? The answer lies in Hadrian’s proprietary software platform, Opus. This is the engine of their in-house trade school, the tool that makes their human-centric philosophy a practical reality.

Imagine Maria’s first day. She isn’t handed a 500-page manual or told to shadow a grizzled veteran for six months, hoping to absorb his knowledge through osmosis. Instead, she’s on the factory floor, in front of a clean, modern workstation with a ruggedized tablet. On that screen is Opus.

Phase 1: Immersion and Guided Learning. The software presents a "digital blueprint" of the task at hand. It’s not a flat, confusing 2D drawing, but an interactive 3D model she can manipulate and explore. Opus then walks her through the entire process, step-by-step. It tells her which tool to use, where to place it, and what action to perform. The system is engineered to "de-risk complex operations" by breaking them into simple, manageable tasks governed by clear "if/then" logic.

Phase 2: Real-Time Feedback. This is where the magic happens. The software is connected to the machine. As Maria completes a step, the digital twin on her screen mirrors the action, providing instant visual confirmation. If she makes a mistake, the system doesn't sound a terrifying alarm or shut down. It highlights the error in real-time, showing her exactly what went wrong and how to correct it. This closed feedback loop replaces fear with confidence. Every action is a learning opportunity, not a high-stakes gamble.

Phase 3: Human Mentorship. Critically, this technology does not remove the human expert; it elevates them. The software handles the rote, procedural instruction—the part of training that is slow and tedious. This frees up the senior machinists to do what they do best: coach and mentor. They become the "human-in-the-loop," available to help Maria with a tricky setup, explain the why behind a certain process, and transfer the subtle, intuitive "implicit knowledge" that can't be coded into software. They adapt their coaching to her specific learning style, building a relationship of trust and respect.

This symbiotic system—an AI that teaches the how and a human that teaches the why—is the 21st-century apprenticeship. It’s a system built from the bottom up, designed around the experience of the new employee, focused entirely on removing their stress and accelerating their journey to mastery.

The Outcome: Hope, Quantified

The results of this approach are staggering, both for the people and the business.

For an employee like Maria, the transformation is life-changing. In just 60 to 90 days, she can become certified on a complex 5-axis mill. Compare that to a traditional apprenticeship, which can take months and even years to produce a master machinist. She has gone from a minimum-wage job to a well-compensated career at the forefront of a revitalized American industry. She has a sense of purpose, a feeling of mastery, and a pathway for growth.

For the company, this system is a strategic superpower. By creating their own skilled workforce, Hadrian has solved the single biggest bottleneck in their industry. This allows them to scale at a speed their competitors can only dream of. It’s so effective, in fact, that it has evolved into a monetizable product. With their "Factories-as-a-Service" model, Hadrian can deploy its entire system—software, processes, and training methodology—directly into a customer's facility to solve their production challenges on-site. They aren't just selling parts; they are selling a solution to the labor crisis itself.

This model of tech-augmented human performance isn't isolated to Hadrian. Aerospace giant Lockheed Martin found that by using AR glasses to display digital work instructions, their assemblers could work 30% faster with 96% accuracy. Another study in the aerospace sector reported a 60% increase in productivity using AR guidance. These tools are proven to reduce employee onboarding time by up to 50%.

The evidence is clear: when you build a system that empowers your people, your company immediately becomes better, faster, and more resilient.

The Blueprint: Your Factory of the Future

Hadrian’s story offers a profound and hopeful blueprint for any leader in any industry. The lesson isn't that every company needs to build rocket parts, but that every company can achieve extraordinary results by focusing on the human experience of work.

It begins by asking the right questions:

• What is the biggest point of friction and fear for my employees?

• What "tribal knowledge" exists in the heads of my senior staff that we could codify and teach with technology?

• How can we use AI and automation not to replace our people, but to augment their skills and accelerate their growth?

Of course, this model is not without its challenges. The "significant initial investment" required to build an automated factory can be a high barrier for smaller companies. There's also the valid concern of de-skilling—that an over-reliance on software could prevent workers from developing the deep, foundational knowledge needed to solve problems when the system fails.

This leads to the most important question: is this human-centric model a stable, long-term philosophy, or just a transitional phase on the path to full automation?

Only time will tell. But today, Hadrian stands as a powerful proof of concept. They show us a future where technology serves humanity, not the other way around. It's a future where we stop seeing people as costs to be managed and start seeing them as assets to be developed. It's a future where a young person can once again feel a deep sense of pride in building something real and lasting.

The work of the future won't be about human versus machine. It will be about humans with machines. The companies that thrive will be the ones that build systems from the bottom up, designing every process with the goal of empowering their people to do the best work of their lives.

References

1. PR Newswire. "Hadrian Raises $260M to Build AI-Powered Factories for America, Adds Full Product Manufacturing, Opens Arizona Site." URL: https://www.prnewswire.com/news-releases/hadrian-raises-260m-to-build-ai-powered-factories-for-america-adds-full-product-manufacturing-opens-arizona-site-302508179.html

2. Contrary Research. "Hadrian: The Factory of the Future." URL: https://research.contrary.com/company/hadrian

3. Forbes (via YouTube). "This Next Billion-Dollar Startup Wants To Save American Manufacturing." URL:(

1. startup.jobs. "Training Specialist @ Hadrian." URL: https://startup.jobs/training-specialist-hadrian-4499159

2. jobs.spacetalent.org. "Training Specialist @ Hadrian." URL: https://jobs.spacetalent.org/companies/hadrian/jobs/26833741-training-specialist

3. Breaking Defense. "Manufacturing startup Hadrian to expand to Arizona, and into defense primes' own factories." URL: https://breakingdefense.com/2025/07/manufacturing-startup-hadrian-to-expand-to-arizona-and-into-defense-primes-own-factories/

4. Los Angeles Business Journal. "Series C Round Brings $260 Million to Hadrian." URL: https://labusinessjournal.com/technology/series-c-round-brings-260-million-to-hadrian/

5. jobs.spacetalent.org. "Manufacturing Engineer, Factory Development @ Hadrian." URL: https://jobs.spacetalent.org/companies/hadrian/jobs/54369539-manufacturing-engineer-factory-development

6. career.io. "Remote Training Program Specialist Los Angeles @ Hadrian." URL: https://career.io/job/remote-training-program-specialist-los-angeles-hadrian-a6fa1a9ea8f090550321535431ef3a02

7. Ashby. "People Partner @ Hadrian." URL: https://jobs.ashbyhq.com/hadrian-automation/7e84b242-8946-4611-a09f-4b32df991d16

8. Breaking Defense. "How startup Hadrian plans to take over the defense manufacturing world." URL: https://breakingdefense.com/2024/08/how-startup-hadrian-plans-to-take-over-the-defense-manufacturing-world/

9. The Manufacturing Institute. "The State of the Manufacturing Workforce in 2025." URL: https://www.themanufacturinginstitute.org/the-state-of-the-manufacturing-workforce-in-2025-20621/

10. National Association of Manufacturers. "The State of the Manufacturing Workforce in 2025." URL: https://nam.org/the-state-of-the-manufacturing-workforce-in-2025-33321/

11. NIST. "The Skills Gap in U.S. Manufacturing: 2015 and Beyond." URL: https://www.nist.gov/system/files/2015_skills_gap_report.pdf

12. Britannica. "Advantages and disadvantages of automation." URL: https://www.britannica.com/technology/automation/Advantages-and-disadvantages-of-automation

Yes, I said it. If hallucinations bother you so much you are ignorant. Not ignorant in a derogatory way, but in a definition of the word kind of way.

Ignorance means lacking knowledge. And if you are staying away from AI because you have been scared off by the nay sayers and complainers then you have been fooled.

It is natural to have concerns about the unknown. There was a time when people said: “What is the internet?” They were concerned then too. I am pretty sure people with horses were quite scared of the automobile.

There are two points in my feisty introduction. The first is that your feelings are natural, but they are based on ignorance. The second is that no matter how you feel about it, it’s about to change the entire world, so you may as well use it to your advantage.

People often complain about how business innovations pass them by, and how the system is tilted in the favor of the rich. No, the system is titled in favor of the bold, those who know they are ignorant and do something about it.

So let’s do something about it now.

If you get your panties in a twist when AI hallucinates you do not understand the reason why it does

You think that AI understands things, because of the word intelligence. AI does not understand anything. It matches patterns, it predicts the next word, it tries to assume what you want to hear.

Ever meet someone who says things like: “Oh my god yes, we should totally meet next Saturday. Yes, I would love to hang out.” But then never actually shows up, or cancels? We call them flakes.

AI is a flake. It tells you what it thinks you want to hear. But that right there is key to avoiding its limitations when it matters. You have the responsibility to give AI so much information that it doesn’t have to guess about it if you want to hear.

This is where most people screw up. They already fail at prompting, which is only one of 5 levels of AI according to yours truly. You need to make sure you give the AI a prompt that is so crystal clear that there is nothing to guess.

Then, when you have done that, you have to make sure you provide it with enough context so it knows how to shape what you want to hear properly. Like the flake, make sure you always tell it not to be flaky.

I see articles posted about the “dangers of AI”, and AI is lying to me about my own writing and bla bla bla. Then I read these articles and the only thing I see is that the AI is doing exactly what you are telling it to do.

“Hey, here is a PDF of my essay on birds. Can you read it and tell me how to optimize it”. Eh yes, the AI will “hallucinate” with this. You have 0 instructions that are meaningful, no context of your writing, who you are and you expect a genius outcome.

All these nay sayers and complainers have a valid emotional concern, but they simply do not understand AI limitations. They are like a parent telling a 5 year old to run a complex problem that involves several steps and then get upset that their kid started playing legos.

Humans hallucinate more than AI and you’re totally fine with it

Ever notice that humans hallucinate all the time? Why are you totally fine with that but when AI hallucinates based on bad prompting and missing context the world is about to end?

With humans it is actually much worse, because you do not know if they are doing it on purpose and what their ulterior motives are. AI wants to answer your question correctly, so that you use it more often, so that its creators make more money. The motives are quite clear.

Imagine you have read 100,000 books and now someone asks you questions about them. Guess what? You are going to hallucinate. Some people will lie on purpose just so they look good and continue to feel special.

I am sorry, maybe I am missing something here, but how is AI hallucinating such a big deal? Prompt with purpose, provide lots of context, frame your questions, guide the AI to answer in specific ways and check its answers. The statement on the bottom of the chat window is there for a reason.

I encounter AI hallucinations all the time. I don’t get upset about it, I just reframe and use the AI to my advantage. I built an entire inventory system in Google AppSheets with Gemini as my development partner.

Yeah, we ran into roadblocks where it confidently told me to use X code to achieve Y goal and it did not work. After a couple of times of that, I used Google AI Mode and checked on the documentation. In one case the difference was a vertical bar ( | ) versus a colon ( : ). How horrible.

AI has limitations. Learn them and build your system accordingly

AI isn’t a magical unicorn that solves all your problems. As a matter of fact if you do not treat its limitations with care it may make your problems worse. AI augments whatever it is you do with it.

Understanding the limitations is the key. Once you do that, you can build incredibly powerful systems into your business and workflows. Just put the AI into a box and don’t let it roam wild.

You don’t get a puppy, let it run around the house and then get upset when it pees on the floor. Actually, never mind, people do that and it is infuriating how irresponsible and harmful they are to the animal, but ok I digress, you get my point.

Defining clear roles for AI is the key. Nobody says you need to have an AI agent that does everything for you. That is not how this works. You need to have 20 AI Agents that each do one thing for you. There is no difference in outcome, just in setup.

For example, my last client has a lawn mower business. We built the inventory system and are now collecting data on which parts they need to order. All the AI does every month is this:

• On a set schedule (30th each month) Zapier triggers

• Good old machine learning predicts when the parts should be ordered

• AI reads this information and puts it into human words

• Then via Zapier it takes the dates, schedules an order email to the vendor

The AI is so restricted in this workflow, but the amount of time this saves is wild. What is the AI going to hallucinate when it is in such tight confines? Well, nothing, because there is nothing to hallucinate.

AI is not the ChatGPT Chat interface. If that is all you know you’re behind the times.

The example above never touches a ChatGPT, Claude or Gemini user interface. It all happens behind the scenes. Sam Altman has already said that AI in its current form is baby stuff. AI will become like the transistor. It will be everywhere, but we won’t even be cognizant of it anymore.

The point is that the best automations I built for clients with AI, do not involve the client interacting with AI. AI is just there, silent in the background and does its thing.

But people are very visual, so for them AI means Chat interface. No, the AI doesn’t care how you instruct it. The Chat Interface is actually very inefficient for business workflows and what I do.

AI can be stopped from hallucinating. Limit the scope of what it does, provide it strong context and it will be just fine. The problem is not the AI, it is that most people use Chat interfaces, give crappy instructions and expect it to cure cancer.

Closing out my rant

I sounded harsh sometimes. A little sarcastic and maybe hurt some peoples feelings with how I worded things. Well, sometimes the truth hurts a little. I would like to repeat what I said in the beginning: Strong feelings of fear of the unknown are normal. I do not fault anyone for that, but regardless, they are rooted in ignorance.

I hope that my explanations above shed some light on why mostly the laymen feel the uncertainty related to using AI in business operations.

I do need to acknowledge here that AI has already done some wild stuff. Just yesterday (07-21-2025) some AI deleted an entire codebase even though it was told not too. That had horrible effects on a company. However, why was one single AI allowed into the entire codebase?

This is the point of scope. But for normal businesses, everyday Joes, this is not a problem, because it is simple to curate all this. You can fine tune it for what you need, by making systems that give AI small tasks to do very well.

If you ever want to learn more about how this may apply to you, just reach out. I am happy to chat.

So Long.

I want you to meet Jim. He owns a lawn mower repair and resale business. And his workflow transformation is worth studying.

Jim was referred to me by another client of mine. I was told that he runs a lawn mower business and if I have experience with optimizing such hardware focused workflows. I told him the story of the flight school maintenance hangar.

At the time the problem set was similar, though at a much bigger scale. There were:

• Uncategorized parts

• Unorganized Inventory room

• No scanning or barcode system

• Paper notes to associate parts to airplanes

• Ineffective processes related to doing all this manually

The flight school stories always impress people, so naturally I share it. And yes it was quite an amazing project to take the maintenance hangar out of the stoneage. But honestly, airplane or lawn mower, the approach I take is exactly the same.

I told my client yes, let’s talk to Jim, I can do it, no question. When I met Jim on a video call just over a month ago I let him explain his business. It’s quite simple:

1. Buy a mower

2. Inspect the mower

3. Create a work order for the mower

4. Order the parts that are needed for the mower

5. Wait for the parts to arrive

6. Repair the mower

7. Sell the mower

Working with Jim is quite the joy, because he intuitively knows how my process works. He basically did the initial investigation of painpoints by himself. He knows what he wants optimized. Often that is not the case.

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The Best Way To Know What To Optimize

When you want to optimize anything in your business, the single best place to start is stress. Think about everything that is causing you stress, is getting you upset or is frustrating. The thing about improving these aspects of your workflows is that it not only creates efficiency, but it saves you more energy.

Usually I guide my clients through identifying their paint points. It is totally ok not to know or understand that these daily painpoints do not have to be the status quo. Most of the time this is 85% of the job.

Jim had already done this though. Their process by doing everything on paper was causing lots of micro frustrations throughout the day.

• Papers were misfiled

• Mechanics couldn’t find notes of other people sometimes

• Mechanics wouldn’t write detailed notes by hand, because it took longer

• Specific Parts from the inventory couldn’t be associated with the actual mower

All of these individual things were making people edgy. And these little micro frustrations build up and create a work environment that can become stressful. This then leads to less effective execution on the repairs themselves and causes repairs to take longer.

It is always the same cause and effect relationship with all the people I have ever worked with. Follow the stresses and optimize for them first. Most of the time, this solves most problems.

Finding The Optimal Solution

The next step of course is finding the best solution. Here people often make the mistake and begin with software. That is the wrong approach in my opinion. Why force people to adapt to a software when you can find out who they are, how they work and then just design the software around them?

This is the magic of today's AI age. You can build personalized solutions that would have cost thousands of dollars even two years ago for a fraction of the cost. Even if AI itself isn’t used directly in your solution, it is used in making it.

So I advocate for tailoring solutions to your needs. Yes, this is the new way of doing things. In Jim’s case we had a clear task list to eliminate their frustrations as well as optimize their workflows

1. Build a digital inventory system

2. Track Mowers, Work Orders and Parts

3. Be able to scan QR codes to assign Parts

4. Build reminders related to Work Order status

5. Create custom dashboards to visualize everything user by user

When that is completed, use AI to learn to optimize the part ordering process by anticipating then which parts need to be ordered in advance to reduce down time. Then use AI to track inspection times and auto assign better completion time frames.

In the past that would have meant you needed to pay hundreds of dollars a month for a software solution, then teach your staff how to use it and then deal with all the quirks that do not fit your custom business model.

Now you can use AI to help you build it and accomplish the same thing for a one time cost of creating it and then a low monthly operating cost saving you thousands of dollars.

In this particular case we landed on Google AppSheets combined with machine learning and Gemini. Google AppSheets offers a perfect software platform on which one can build inventory systems. It has machine learning capabilities and since we’re already in the Google Universe it makes sense to use Gemini for the fancy stuff later.

How You Can Build Efficiency One Step At a Time

You can learn something from this little story. I am currently working on this solution. Within two weeks, we finished a fully functioning system that is now being used by the entire team. This type of turn around time is the norm in my world. Now we can measure the impact this has on Jim's business.

1.
When looking at your own business or your own work (this can be applied personally of course as well) focus on what is annoying you. You’d be crazy to automate away what you enjoy doing. Write those things down.

2.
When you’re thinking about how to automate something, or find solutions to make the process better, focus on how you want to work. Focus on what you like to do. Do not focus on existing software solutions. That is a thing of the past. Modularity and adaptability is the name of the game now.

3.
Let AI run a Deep Research prompt on your desired solution. You will be amazed at the level of detail you get. But don’t just ask it a single question ok? Provide details and context. I often chat with my personal AI assistant for 5 minutes or so with the goal of it building me a perfect prompt. Context and detail is key.

4.
If you do not know how to write scripts or code, no problem. Let the AI know that you only want no-code solutions. It will take that into consideration. And even if a script is needed, AI can write it for you. You just need to have a bit of curiosity to learn.

5.
Take it one workflow at a time. Jim’s story is unique because he trusted me right out of the gate, because of the personal referral and he knew his painpoints. But just do one thing at a time. Take small steps. Rome wasn’t built in a day.

6.
Watch the transformations and build on them. I would say that in 75% of all my solutions AI is only in the background. If a solution doesn’t require it, then do not use it. AI is great when it fits.

If you are stuck, or you do not have time, talk to someone like me. Find out what is possible. Many people are just there to help you on your path. I for one love if I can guide you and then you can do it yourself. Perfect, one more person on my list that I helped.

A personalized AI assistant can and will change your life. Yes, it won’t magically make you rich or wash your car, but it will change your daily life.

I was right in the front row seat of the AI revolution. ChatGPT launched in November of 2022 and in early December I had used it to rebuild websites and adjust my clients marketing strategies.

I have used AI professionally at every stage of its evolution. From when simple prompting felt like a revolution to when ChatGPT passed the Turin test and then finally to when AI first clearly surpassed human capabilities with Deep Research.

AI is a personal experience, hence why we need to make personal assistants, well personal. We need to custom tailor them to who we are. This is what I have been doing ever since 2022. Now let me take you on a journey through the different levels of a personal AI assistant in the hopes that I will convince you to get on board.

Level 1 - Effective Prompting

We have all experienced ChatGPT (Claude, Gemini, whichever you use) giving us an answer that wasn’t satisfying. That is because we did not give it the information it needed to succeed.

Like I said, AI is personal, so not only does the AI need to know what you want to hear, but also how you want to hear it. The secret to getting good responses is to give the AI a comprehensive prompt.

This is the subject where people are building coaching businesses around. Where people write article after article on substack. I won’t go into the nitty gritty here, because to me, there are three simple things you need to do to get your assistant spot on every time.

1. Give the AI a clear role to take on related to the subject of your question. For example: “You are my doctor, specializing in A B C”

2. Give the AI background information about what you want to know

3. Always finish any prompt with: “Before you answer, do you have any questions you would like to ask me to be able to give me a great answer”.

If you follow these three principles the AI will be able to better personally assist you. All coaching and all paid offerings that focus on this, will end up teaching you those three principles.

Only by doing this you can already have quite the powerful personal assistant. Now you can get a great workout routine, nutrition plan, scheduling help, writing help, you name it.

Don’t be afraid to be personal. If you ever read a book on a subject and you trusted the book, you can basically trust the AI, because it literally read all the books. Just double check the sources. Parenting advice is not off the table, is what I am saying.

Level 2 - Contextual Prompting

To take your personal AI assistant to the next level you need to begin creating serious context. This is already where many people stop. And that is a shame, because the more context AI has, the more personal it can become.

Think of a coach for the gym, or an assistant for your office that handles emails and phone calls. What makes them great? When they know everything you told them, when they listen and give constructive feedback and when they do the things you want them to do properly.

To do that:

• They need context

• They need to know who you are

• They need to learn about your routine

• They need to understand your preferences

AI is no different. When you give it greater context it will take all of it into consideration. That means taking Step 2 from level 1 and taking it very seriously. The rule of thumb is, you cannot give your AI assistant too much context information.

When you want some advice for the gym, tell it everything about your current health routine or lack there of. You don’t need to hold back either, because unlike another human, the AI does not judge or care whatsoever. It is there to help.

Tell it what you are eating, how you sleep, how often you drink water, go all out. The same thing applies for any other subject you want to discuss with the AI. Give it as much context as possible.

Again, a personal assistant is no different. They need some time before they get really good at their job and before they are tailored to your needs, because they need to learn the context of their job.

The AI is the same way, except that when you give it context one time, it generally remembers it without needing to be told again (There are some exceptions to this when the context becomes too large, but this by now is over a million tokens. You will likely not get there unless you do some serious work with it).

Level 3 - Project Based Memory

Thus far we have been roaming around amateur land. Level 1 and Level 2 is where the herd hangs out. Now Level 2 is already much better than level 1, but it is still 1 off conversations. It doesn’t yet feel cohesive.

Level 3 is where things become assistant territory. You see AI’s have memories. ChatGPT illustrates this quite nicely, because it actually has a settings page where you can check what it remembers.

Next time you use AI ask it: “Tell me everything you know about me, remember about me or can recall about me”. This is an interesting experiment.

There are two types of memory. The first is simply your chat history. The AI can access all the chats you had previously. This means it can already infer things about you by accessing its own context about you.

Many people do not make use of this. You can literally store chats with the intention of talking about them later. ChatGPT even lets you create project folders for topics. Perplexity calls this Spaces.

Simply create a folder called Health and then store all your health related chats in the folder. Now at any time you can say: “Hey let’s go to my health project and talk about X”. This enables you to direct the AI quickly to all the information it needs to assist you best.

The second type is the settings page I mentioned earlier. You can tell ChatGPT to remember things while you are chatting. I do this every single day. Today while I was working out, I kept it updated about my routine, the weights I used and how many reps I did.

Next time before the gym it will give me a quick briefing about my last workout. This is a training tracker on steroids, because not only does it remember all my notes, but it can augment them, expand them, and give suggestions.

This is where the personal comes into play. Tell it specifically what to remember, to remind you, to build task lists around things. Tell it to remember things under specific titles so you don’t even need to recall yourself.

Level 4 - Connecting Your Applications

Up until this point we had the AI tell us what we should do based on its knowledge about us. Maybe it suggested to us how to write something, cook something, how to build an app, how to optimize our marketing.

But what about letting it do all this for you? What about not asking it to even help, but setting it up so that it just does the work for you? Is that even possible? Oh yes, it sure is.

A true personal assistant has access to your schedule. They can interact with your customers to reschedule appointments, can they not? This is the same idea. If you know how to code and use an API, then this is easy peasy.

If you do not know how to code you can use no-code tools like Zapier to build your own AI workflows. You can have the AI do something every day at 6am. Mine reads all my newsletters and filters them based on my preferences. It’s a pre-read so I only get to actually see what I like.

Yes, I had to train for a few days. Of course, your human assistant wouldn’t know what you want to read and what not. But like the human the AI learns, except it learns super quickly and doesn’t forget.

In this way you can connect AI to all your applications. Emails, calendars, CRMs, Advertising campaigns.. Anything. I mean literally anything. Now it will learn from all of it. You supervise it, correct it, teach it and then unleash it.

There are levels of complexity here too.

1. You can use linear automations that trigger AI for specific tasks

2. You can build Agents with n8n or Zapier that have access to some apps with a specific purpose.

3. You can build your own MCP server, connect all your apps and call your own custom GPT (sounds complicated, it is not. You can learn it in 3 hours).

Obviously 3 is where it’s really at, because now the AI has access to all applications without needing to be inside of a linear flow. You can prompt it and it will execute tasks in your apps. “Reschedule my 8am and move my lunch meeting by one hour. Make sure to email both and apologize based on my usual email style”.

Yep, it will do it.

Treat AI like a personal human assistant and you will be amazed

The secret to all these levels is to pretend AI is your new human assistant. Treat it exactly the same. Teach it who you are, what you need and what your preferences are.

Spend time with it to make sure it gets all the context it requires. Give it access to your emails, give it its own email if you want. Let it see your schedule, your routine and then just let it help you.

The sky is the limit.

I have been doing automation and business optimizations for a long time. In all my time, I have never seen so much impact from a single tool other than AI. It is remarkable how much time and money it can save people.

Just make sure you know who the boss is. People are afraid of losing their thinking capability. No you won’t, unless you let it. Let AI help you, not overtake you. Let the AI augment your creativity, not replace it. All that is in your control.

I use it daily and it makes me way more productive. I don’t know if it is 8x, 12x or 22x. Who cares? It is so much I can tell my life is much more efficient. And yours can be too.

If you’re aware of optimizations then you’re not completely wrong. Awareness is the first step to improvement after all. But there is a reason why many entrepreneurs and businesses have yet to adopt modern technology.

We have been indoctrinated by our success driven society to believe that we must follow the approach from other people who are successful. This is completely false. There is a very simple reason that this cannot work.

We are all unique people, with unique skills, emotions and drivers. I cannot follow Steve Jobs' approach, because I am not Steve Jobs. You cannot emulate someone who is successful without making the habits your own.

We have been made to believe that the right question to ask is: “Who do I want to become?” When instead you must ask: “Who am I?”

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When you ask “Who Do I Want To Be?” you forget about human nature

When I just started out my career I was fully committed to all the self improvement propaganda. I read the books, studied the successful stories and began adopting their habits and approaches. But nothing lasted.

I was not able to scale anything I tried for the long term. The reason is simple: None of the approaches fit who I was. You can wake up at 5am all you want, because some famous motivational ex-military person does it, but if that isn’t you, it will not work.

And the same logic applies to business. I kept asking who do I want this company to be modeled after? This inevitably led to processes and workflows (habits) that we could not sustain, because the individuals executing my proposed strategy didn’t like them and so the company didn’t like them.

This is the mindset that leads us to building out systems from the top down instead of the bottom up. We focus on a big wonderful system that is perfect for this business and never bother to find out who the individuals executing it actually are.

This is how I failed in the beginning. I build workflows for clients who have to learn a new system. This alienated the employees who thought: “oh great another consultant who knows better than us”, which then in turn also created distrust with their management team for hiring me in the first place.

Failing on that level was painful. I took it personally, issued refunds where applicable and doubted myself. I was not always the confident system architect I am now and at that time I was at a low point.

The Question You Must Ask Is “Who Am I?”

Over time I came to realize that forcing myself to adapt to habits is a bad approach. The epiphany came to me at the gym. The cliche starting point for all habits.

For the longest time I was at the gym with my former boss at 5:30am. That is when he went, he was jacked, so it must be working. The problem was that I was at my sharpest in the morning. For who I was, the gym at 5:30 was counter productive.

When I realized that working out for me was best done in the afternoon, I realized oh my god. I should not adapt myself around other people's habits. I need to build habits around me.

So I started doing my automation work in the morning (No AI yet at that time), because it felt right. And I went to the gym and played tennis with my dad in the afternoon, because it gave me another energy boost I could use until about 7pm.

But this article is not about my gym routine. It is about businesses and how they can be more efficient. So let me bring this full circle.

Lasing Business Optimizations Begin By Finding Out Who The People Are

When you transpose the question who am I to a business it works the exact same way. Some people simply like to use a certain application. Some people prefer to organize a calendar one way, other people another way. There are countless examples of this.

We are all unique individuals with our own preferences. When businesses think about optimizing they almost always start with a grand vision, some amazing examples and give talks and speeches to their staff about productivity. If you want to spend a lot of money without success, that is the way to go.

Instead, you need to talk to employees every day. Find out who they are. Ask them how they feel about their work, their day to day tasks and make it part of your culture to receive honest answers. That is the absolute most important and best optimization you can ever do.

Once you receive honest feedback, you will find so many places where you can optimize your entire company. It is so logical when you think about it. Jack works in the office. Jack has to talk to the customers and work with them directly. Jack is a person with feelings. Optimize Jack's process and you optimized part of the business.

Knowing That You Can Optimize Is The Second Half Of The Battle

The other thing that often bites businesses in the efficiency butt is that they do the above, they find out Jack would love it if they could adjust process A, but now what? Now what often is simply a lack of knowledge. They just don’t know you can actually do something about it.

Let me unequivocally tell you: 90% of the time you can do something about it. Google it. Ask ChatGPT about it. Gosh with AI available now, the world of optimization is literally at your fingertips. It is not isolated to programmers or people like me. You can do it too.

If you combine ChatGPT, Gemini or Claud, whichever LLM you want, with some reading and YouTube you can find out in 10 minutes if you can optimize a workflow. It just takes the will to do it. ChatGPT can even teach you how to do it and implement it. And if that is too much or you’re too busy, then you just talk to someone like myself.

The investment into optimization is so low compared to the return, many business owners just don’t know it’s possible.

Ever Since I Adjusted My Question, I Created Happiness Around Me

Yes, happiness. This is not an exaggeration. Employee satisfaction with their job is arguably the highest driver of efficiency for a company. Why do you think small startups can beat big companies? Because the entire team is all in on one goal with one single mission.

But this is not unique to startups in tech. This is just humans sharing in something and wanting the best for the collective. You can re-create that culture with my approach. Make your employees happy and they will be more efficient. It is so dumb simple that many don’t seem to do it.

Focus on the following:

• Reduce daily stress

• Eliminate tedious tasks

• Remove repetition from work

• Make your employees a bit happier each day

If you search for your answers with that goalset, you will succeed. And then just use AI and YouTube to optimize what you find. Yes, it takes time. But everything worthwhile does. But if it ends up saving you $150,000 a year or even $250,000 a year, why in the world would you not do it? Yes, those are actual numbers of my clients, cross my heart and hope to die.

The Only Tools You Need To Succeed In Optimization

1. ChatGPT or some other LLM

2. YouTube

3. Curiosity

4. A drive to make your business better

Of course this will eventually lead you down to:

• Zapier

• N7N

• Make.com

• AI Agents

There are 100s of tutorials, 100s of websites to read and the only thing standing in the way is your team's culture and approach. But yes, people are busy focusing on the operation. Well then you can call me or someone like me. That is why we have been running successful businesses for 10 plus years. This stuff works.

People write and talk about this concept so much that I almost skip articles like this automatically.

Everyone knows that small improvements are supposed to be the simplest way to get huge results. This advice has almost become a cliche. The problem is that everyone writes about this in generic terms, dancing around the concept, but never building a useful plan.

I am going to show you exactly how you can improve your business by 1% every single day.

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Why Virtually All Advice Lacks Results

I read all the recommended books on improvement. You likely have too. They did not magically lead to the results I wanted to achieve. They build up my expectations, only to lead to inevitable disappointment.

Advice on how to optimize your life or business is useless unless you follow it with action. Knowledge isn’t power. That is what most authors want us to believe so we keep buying their books. Without action knowledge is useless.

That is why most self / business-improvement books never lead to success. They do not give you the action steps required to succeed. They talk about cliches and obvious concepts without relating them back to you.

In the end most of these books lead to discouragement. I often felt that the problem must be me, because these books sold millions of copies, why are they not leading to results? I must be the problem right?

To be fair, a book has to be written from a 30,000 foot view, because the author is writing the book for the masses and not for you. But 1% improvement is a personal experience. It begins with you and your team. It begins with people.

And that is exactly why these books do not deliver the results we hope for. We need to tune into ourselves first at a personal depth a book simply cannot.

To Improve Daily You Must Start With People

We are all unique. We have different:

• Drivers

• Opinions

• Emotions

• Worldviews

• Motivations

All these affect our work ethic and how we see ourselves inside our work, within our team. The thing that drives one person to work hard may not be the same thing that drives another person. Yet all the books teach us that we need to build a system based on their advice.

The problem is that this advice will definitely not work for all people. Now you have a system you built on these great books and you realize that you are not getting the results you wanted. That’s because the book did not help you focus on the individuals that need to act on the advice.

Great Systems Are Built Around People

The most successful businesses have systems built around the uniqueness of their team. That is where 1% daily improvements can be achieved. You need to know what motivates each person in your team as well as what causes them stress. Then you optimize for it.

Systems that are created without the involvement of your team will fail. If you build something from the top down instead of from the bottom up then you will never reach a level where 1% improvement is part of your culture.

Failure of a system is easy to recognize though and you can change it immediately. Here are the most common ways system failure shows itself:

1. You feel stressed way too often

2. You feel like your system is not being appreciated

3. You feel like you must micromanage way too often

4. You feel like you are being asked redundant questions daily

5. You feel like your team isn’t performing as well as they should

These are the cues your body gives you. These are all emotions you need to listen to, because they are the roadmap to optimization.

• Stress

• Repetition

• Frustration

• Redundancy

• Micromanaging

• Lack of Appreciation

You need to tune into these feelings. Most systems never do that. They do not build a culture of 1% improvement. Top down systems assume that people's feelings will simply adjust to the process.

To Improve 1% Per Day, Focus On Reducing Stress A Little Bit At A Time

If you want 1% daily improvements you need to have a culture that makes people feel motivated to want to improve.

• Why should someone want to improve into a system they had no part in creating?

• Why should someone want to improve their own workflows if they have no incentive to do so?

• Why should someone want to change their daily habits when they don’t feel appreciated?

The way to improve your own daily routines and your team's performance by 1% daily is to eliminate stress, frustration etc 1% a day. Just get rid of what is causing you and your team to feel bad. It is quite obvious really isn’t it? If you make people's lives better, little by little, every day, success will come automatically.

Here is an action plan that actually works. Do this every day to begin your 1% improvement journey:

1. Your body clearly tells you when you feel stressed or frustrated. Begin listening, show genuine interest and then adjust the system for it.

2. Talk to your employees daily and ask them how they are feeling? Identify their painpoints. They feel emotions about their work, the same way you do.

3. Make it part of the company culture to talk about the negatives in peoples daily lives. Work is a big part of our daily routine, if you can reduce stress from it, it automatically improves business performance.

4. Optimize your system around pebbles' unique needs. Your business needs are your people's needs. They execute your operation every single day.

5. When you find the painpoints automate them. Some pain points are unavoidable. When you find the ones you cannot change, use AI, use automation. This is where technology comes in. Use it for that.

Over the last decade my clients have felt many noticeable improvements in their daily lives. But these did not come suddenly or immediately, because I implemented AI and automations into their routines. Why would you ever automate something that brings people joy or meaning?

If we reduce that which makes us feel stressed, 1% a day, we will experience large scale improvements over time. But it all starts with people. I always say that business optimization is 85% people and 15% technology. The AI is the easy part. But knowing what the AI should do is the hard part.

Names have been altered to protect privacy.

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When you create something truly impactful you will notice

I left the hotel at 8am. It was only a short drive over to the clinic. With my coffee in hand I got into my 4Runner and began to drive. This was the first time I would see a behavior health clinic in person.

It was early June 2023, the sun was out and the Colorado mountains stood in the distance. I parked my car, got out and followed the signs along the pathway. When I turned the first corner I saw the entrance door with hand drawn pictures of suns and elephants and other animals in the side panel window.

Meg opened the door and motioned me in. With a warm smile on her face she gave me a hug and told me how amazing it is that I am coming in person to check in on them. When I stepped through the door I did not know that I would be leaving with a sense of profound fulfillment because of what we had built.

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What Our Software Did For Meg

Meg is a wonderful person. Ever since she was in school she wanted to help families with kids with autism. It has always been her goal and her passion. To her a child with autism is incredibly special and her love for what she does shows in how she interacts with kids.

The first thing she showed me was a special lock on the front door. You could open the door from the outside when the clinic was open, but you needed a quick code to get out. This is how they protect kids from running outside.

Another thing that struck me is the incredible amount of patience Meg has. When she worked with Taylor it was clear that she loves helping him learn. Taylor was one of the newer kids to the clinic. You could tell that he has a lot of trouble communicating as compared to a neuro typical kid. But when he started on a puzzle, your jaw would drop on the floor.

In behavior therapy clinicians are busy, and I mean busy. The kids require constant supervision and attention. The best way to think of it is to take a 4 year old who is wild. That alone is a job, but now add to it that communicating and giving instructions doesn’t work at all. Neuro typical kids develop a sense for you. Some kids with autism do not have the ability to do that. That is one of the reasons why they are with Meg.

During the day Meg has no time for anything but the kids. Yet HIPAA requires that each session has notes and summaries. All the administrative work has to be done after. So what this means is that part of the allocated insurance reimbursed time is for paperwork. This is especially heavy for new patients. This is where our software Knowetic comes in.

We developed an AI supported Care Navigation Module which helped clinicians like Meg standardize the intake process of new patients. What this enabled Meg to do was spend on average 45 minutes to 1 hour less on administrative work per kid, because after you interview the family it generates all the reports for you.

When Meg works with the kids there is critical information she needs to know:

• Does the child have siblings?

• If yes, what are their names?

• Do we have a favorite toy?

• A favorite stuffed animal?

• Can the child swim?

• Does the child seek heights while outside?

• Does the child know what a road is and the danger associated with it?

• Does the child have a peanut allergy?

The list goes on and on. But when you run a clinic with 20 patients it is impossible to remember all of this in the beginning. Enter our AI LLM KnowYeti.

KnowYeti reads all the reports, session notes and medical records pertaining to the patient. Meg can then on the spot ask KnowYeti all the important questions and receive the answers within seconds. You see, KnowYeti lets Meg chat with the patient's medical history.

Meg told me that in the most severe cases (lot’s of medical and therapy history) she was able to reduce the intake and initial treatment time from 15 hours down to 5. That is an incredible amount of time saved, which could translate into an entire new patient entering the clinic for every 3 patients run through our software. The revenue implications are quite noticeable.

But that is not what Meg did.

The Most Admirable And Amazing Example Of What My Clients Can do

Imagine you and your spouse both work full time jobs. You have a mortgage, car payments and you’re just making ends meet. Finally the biggest blessing of your life arrives. You have a child. But your child is diagnosed with autism.

Depending on where on the spectrum your child is, the amount of attention you now need to devote is indescribable. It is fair to say that is almost impossible without professional help. And even if you are lucky enough to have an insurance plan that covers ABA (many do not) your life as you know it will no longer be possible.

For so many families this is a reality. They can barely make ends meet, they require incredible amounts of help and they simply want to feel that they are being taken care of. But healthcare is also a tough business and while clinicians and clinics do their best, sometimes they need to push time savings down to the bottom line. It is simply the reality of the system.

Meg did something entirely different. She took this extra time and did not add more patients to the clinic. She did not take extra time off, go home early or give some staff more vacation time. The team sat down and decided that every single minute of extra time will be spent talking to the family. It will be spent giving them:

• instructions for at home

• An extra hug when they need it

• A follow up phone call out of the blue

• Extra time to let them share their concerns

• More undivided attention and focus on their quality of life

Simply put, what Meg gave families was hope. Hope that there is a path ahead. Hope that even in the toughest moments they know Meg and her team are there to support them.

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True Transformations Lie at The Intersection Where Caring Meets Technology

Yes, in this particular case we are talking about a fully developed software solution. We worked on this for over a year with a full development team. This was a project in the hundred of thousands of dollars, with investor backing and a lot of dedication. But transformations in peoples lives do not require thousands of dollars in investment.

When organizations operate with a culture of caring, miraculous improvements can happen. The key to understanding what creates lasting change is that technology is but the means by which caring is instituted. But it is not the origin of where the change is created. If you care about your team, you notice their stresses and frustrations and you simply want to find a better solution.

When teams operate with less stress, more fulfillment and a feeling of belonging to the overall goal they work harder. It is not rocket science, it is emotional science. Empower your team, make them feel part of the process and you care about them and you can harness efficiency enabled by technology that you wouldn’t believe.

But the culture and mindset must come first. No AI in the world will function like KnowYeti unless the people using it want to help the family. KnowYeti could have also been built to read financial reports and create scheduling plans. But because of the love and care of the clinicians we work with and our incredible clinician founder, KnowYeti was built to change the lives of families one question at a time.

When Taylor's Mom Picked Him Up, I Saw A Smile That Will Be With Me Forever

Taylor was one of those complex cases. Meg told me that she saved around 8 hours of time because of the way the technology manifested caring. That is an entire day of time. Of course spread over the course of a few weeks, but it doesn’t matter, because each day you can channel those savings into the family. That is exactly what Meg did.

When Taylor's mom arrived Meg did not have to worry about too much administrative work. She did not push the savings into new patients so she had extra time. Her and Taylor's Mom talked. They spent time together. Meg could tell her about the day Taylor had, the puzzle he completed (and ehhh…. I am telling you, impressive puzzle skills), the games he played and the progress he made today.

The smile on Taylor's face, the calmness in his moms eyes and the wonderful picture of all three of them smiling together made me realize that I am part of the most profound technology I have ever been part of.

We can all harness incredible time savings if we only look for them.

The technology to make it happen is not hard to learn and is readily available.

I teach it and coach it to clients all the time.

The big question is not “how do I save time”, but rather

“What will I do with it”.

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A wonderful man

I met Michael at the tail end of 2020. The first time I saw him he had a warm smile for a stranger (me), a kind word and a major concern. He knew that I am acquainted with his boss and that I am here today to “automate things”.

Often the first reaction to my presence in a business is a fear of losing your job. That is natural though, especially now with AI. That’s why I felt quite curious about the person with such a genuine greeting.

What Michael did not know yet was that my approach to “automate things” is quite different than what most people do. Charlie (his boss) knew it, because we have been talking about it for a few weeks. Charlie knew that lasting improvements come from reducing stress one employee at a time. Charlie knew that I have a very clear principle I follow.

Improve the work life of each employee and the organization automatically improves with it. Fix the micro to improve the macro as I say.

If done properly this can also have a wonderful side effect on the company culture. People are naturally adverse to change. I have found that that happens for two main reasons:

1. Our brain simply LOVES routines. It will continue to release dopamine even though we know what we’re doing is not optimal; even sometimes bad for us. So we biologically resist change.

2. We are afraid that the outcome of the change is bad for us. In case of automation, the initial reaction is to fear it will make your job harder or that it will slowly take away your job entirely.

So if you can implement the change gently (usually this means gradually, but it can also mean abruptly with a lot of empathy) and show the employees that it makes their life better you will build trust.

People need to see small outcomes that make their life better. They need to feel less stressed, or have a little more time to focus on something else that they want to do. In other words the changes need to make them feel better. The primary side effect of doing it this way is that in the future, if there is a big change coming up, they tend to look forward to it. What a great culture.

Transformation Principle #1: Introduce change gently, usually gradually with empathy, focused on employees' work life improvements.

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Nobody Is Right, Nobody Is Wrong

When Michael shook my hand with his kind smile, he of course did not know about the conversations Charlie and I had. So he felt apprehensive. This gradually began to change in the next couple of hours when Michael and I sat down and began to talk. Naturally I knew what Charlie thought the problem was. We had been talking for a while at this point. But I needed to hear what Michael thought the problem was.

You see, the work routines in question will be exactly the same no matter if Charlie describes them or if Michael does. There is a process, done via an application, the process is overly cumbersome, that causes stress for Michael which causes stress for Charlie. It’s always some variation of that.

Where the story differs however is in what they both believe the root cause to be. Managers often (not always) think the employee just needs to work the process without so much fuss. That is natural, because the manager decided on the process. They subconsciously will defend it, because to them it makes sense. This is just a habit in disguise.

Employees on the other hand will blame the process. Not always, not in every situation, but generally the stress or frustration they feel is not because they think they are doing something wrong or should do something better. A work routine is just a habit. Same principle in action. Defend the status quo at all cost, rationalize your feelings (the stress etc.) and blame something else.

Transformation Principle #2: All work routines function exactly like habits in the brain. Cue, Routine, Reward.

A Quick Side Note

I always have deeper talks with the managers first, because I adjust my approach based on how the conversation unfolds. Managers know their business way better than I do. First of all I will learn the workflow process and the desired outcome, which in the end is what must be achieved. Secondly I can usually identify where the initial optimization needs to be made quite effectively.

For example, if the manager says something like: “Yeah my guys just aren’t good with technology”, that usually always means that the process itself isn’t optimal and that routines will need to change for the employee and for the manager level.

But If the manager says something like: “I don’t know if we’re using the right tech, my employees seem to have trouble with it”, then I know that the manager is not directly blaming the employees, which means they are open to the idea of it being them.

That makes a big difference, because now I will actually tell the manager right away to expect that I will recommend a change in their routine also. Subtle initial difference with a big psychological effect later in the process.

The work life of Michael

Michael opened the door to his office and let me in. Two comfortable white chairs on the left wall with a bookcase full of books a few feet beyond. His desk neatly placed in the middle with a good amount of paper and sticky notes. Michael sat down, motioned me to take a seat and so our first conversation began.

Michael became a therapist, because he wants to help people. He spent a long time studying to be a licensed therapist and counselor. When he was still living in Hawaii he focused on saving marriages with alcohol and drug problems, but when his wife got pregnant, they moved to New York to be closer to her parents. Now in Florida, Michael is directing his energy to helping people with mandatory therapy.

If you become a therapist, it is likely that what you want to focus your energy on is doing the actual group therapy session. You spent the time studying to become a therapist so that is where your personal fulfillment comes from. Michael's main problem though was that the administrative tasks (the process) became the center focus of his energy and he no longer looked forward to the sessions.

Michael runs court ordered, substance abuse, evening group therapy sessions. Each evening he had to bring a laptop into the group therapy room. He couldn’t use his normal computer. He then had to open a word document, find the correct therapy group attendance sheet and mark who was there.

Since the session is in the evening, the office staff is no longer at work. Michael then had to collect the payments from each person and mark an X next to the people who actually paid. This alone took 15 to 30 minutes of his time, depending on the night.

If you run therapy sessions that are court ordered this process will never be smooth. Many people do not want to be there, they have to. This causes them not to want to pay. So they have new excuses as to why they forgot their money most every night.

Another factor to consider is that it is in the evening. You’re already a bit tired, so are your patients. To now do tedious administrative work feels like expending extra energy that you really do not want to waste. This process set up the entire session, on a shall we say, unideal emotional foundation.

Here is a breakdown of how Michales stress cascaded down the entire organization:

• Michael feels stressed

• Michael doesn’t look forward to his therapy sessions

• Michael calls Charlie and vents with Kim (office admin)

• Naturally Michael will also make more mistakes on the sheet

• Kim has to chase each person that did not pay

• Kim has to track past collected payments

• Kim is often frustrated and annoyed

• Kim complains to Charlie, sometimes calls him

• Charlie receives evening phone calls

• Charlie has to track Kim’s tracking

• Charlie feels stressed

This is a simplified cause and effect breakdown, but here is the main point that most people do not realize when they are thinking about workflow optimization.

Michael’s stress became Kim’s stress which became Charlie's stress. All three defend their habits in disguise, thereby unable to find a solution.

The approach is so simple, it doesn’t occur to many owners, managers, sole-entrepreneurs, side hustlers and creators. Focus on the stress, gently and gradually remove it and the ripple effects can break the Chain of Stress for an entire organization.

Yes, the solution to all of this involved technology. In the end that is what this publication is all about. But technology is the easy part. It is maybe 15% of the process. The important 85% is the focus on how the people feel in their work life in the first place. All the answers are always there.

Transformation Principle #3: Stress propagates through the entire organization. Identify the root cause of stress and eliminate it.

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The Technological Changes For Michael

When Michael and I were finished talking he thanked me for listening to him so empathically and carefully. We laughed about the fact that I was basically running a “work optimization” therapy session with a therapist. But in a way that is what I do. I tune into people's feelings at work.

Michael led me out of the room, shook my hand, showed me his kind smile again, and said: “I really look forward to seeing how you will help me with all this mess”. That is when I knew that my mission with this conversation was accomplished. Michael and I were on the same team now.

There were two more conversations with Michael over the course of the next week. I spent some time watching him do his workflow, I timed everything he did so that Charlie would have a detailed return on investment and I took a lot of notes. But this is the easy part, because Michael was more than happy to show me. And yes, of course I talked to Charlie more and I also spoke to Kim.

In the end here is what we ended up fixing in the process. Really, we changed the entire thing.

1. I moved the word document to a google sheet. Old school word documents not only can’t be accessed by my automations, they need to be dated and emailed around. Very cumbersome, lots of room for error.

2. I kept the structure of the document the exact same. When I formatted the google sheet I made sure that it looked 1 to 1 like the word document. When possible I do this every time so that the new “software” feels familiar and ideally identical. Plus, since it is now on a Spreadsheet, I have automation access to every single cell.

3. I connected Zapier to the Sheet. Zapier is where the actual magic happens. I am but a conduit. Now I was able to track automations based on data in the sheet or add data to the sheet based on an automation, which is what I ended up doing.

4. Attendance record archiving via Google Drive. First I let the automation copy each sheet and save it in an archive, thereby creating an automatic record for Kim's tracking in timestamped folders. Needless to say she loved that.

5. Connected Square to the Sheet via Zapier. Now I created a trigger automation to run at 6am on the day before the therapy session. This found every email in the sheet and auto-sent invoices. No more payment collection verification required on Michael's part.

6. Adjusted the flow of the Xs. Each time someone paid, another automation triggered and marked the X in the sheet. Now Michael had to only mark the attendance. He really liked that.

7. Send invoice reminder to missing X’s. I then had an automation run at 11pm each night, it found the missing X’s on the paid column and sent them a reminder to pay via Square. Kim was quite happy.

There was more we ended up doing over the course of the next year. Remember that when you introduce changes gently and gradually, make the employees realize that their work life is now better, they are open for more change in the future. This usually happens. My coaching and involvement with my clients is rarely a one off.

The Transformation Of Michael

When this system ran for the first week I came to visit Michael. I found him in his office having a snack. Speeding up his chewing, he put his food down and waved me in. He stood up, shook my hand and seemed content. He looked lighter somehow, like a weight was lifted off his shoulders.

He had 9 total therapy sessions with the new system. He told me that the last two sessions were the first in a long time where he felt excited to work again. It always takes a bit of time to see the automatons in action and feel their impact. This is the part where the brain is adapting to its new routine. This can be hard and it is important to follow up with people about how they are doing.

Michael confessed that he actually felt more apprehensive in the first week. This is normal, because there is a change, he doesn’t know how the “magic” behind the scene works, so he had to get used to it. Again this is not technology, this is human nature. Patience and empathy is the key.

It was wonderful to see Michael feeling in his element again. Likewise it was great to see how much more time Kim could now spend talking to patients when they walked in the door. And of course it felt nice when Charlie called me and expressed his gratitude, because he is so much less stressed.

The Final Business Outcome: Money, Time And All That Stuff

As you know I always time the original workflows. In Zapier, I always built an execution tracker. Every time an automation fires, I add a 1 to a tracking sheet. On that sheet we have hourly pay rates for everyone. This enables us to have a clear picture of the monetary / time savings the Workflow Optimizations generate.

In the beginning of the story we identified 15 to 30 minutes for administrative tasks for Michael. That alone ended up generating 7,200 minutes (120 hours) or $9,000 in annual savings. In the end after all was said and done the adjustment we created for Michael generated over ~$35,000 in total annual savings. Needless to say, we worked on more optimizations in the future.

Depending on how managers value their own time, track the phone calls they now do not have to answer and how they value the stress reduction of their experience, these savings go much higher, quite quickly. It is difficult to measure stress reduction quantitatively of course.

But that is exactly what is so rewarding about what I do.

The most important outcomes are priceless.

Anxiety and A Bad Dream?

Dani suddenly jerked awake. It was 6am on Saturday morning. She was anxious. Did she have a bad dream?

She was supposed to go on a long weekend, hiking, enjoying the mountains, and feeling the fresh air. Focusing on herself and her husband.

But when she opened her eyes, she realized she couldn’t yet leave, because she forgot to ensure the ads her company was running had the latest custom audience.

This kind of thing happens all the time.

Dani’s company sells events; when a new booking is received, she needs to add the email address to the Facebook Ad excluded audiences so ad spend isn’t wasted.

She got up, made herself a cup of coffee, and got to it. It “only” took her 30 minutes, but after a stressful start to her weekend.

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The Main Challenge My Clients Face

The main challenge is that we accept what we are used to because we are not aware that there is a better way. My primary role with clients is creating the awareness even though mostly they don’t even know that this is happening.

But I didn’t know Dani's workflows when we met. I don’t know most of my clients businesess when I first start. I guided her to identify the inefficiencies.

She did it, I then automated it. Anyone can learn how to do this themselves, because technology is only 15% of the process. The real secret is that 85% is a mental shift.

Listen To Your Minds Alert System

Ever experienced this: Someone you know is buying a new car. You have heard of it, but you never really noticed it. Now, seemingly all of a sudden, this car is everywhere.

In Neuroscience this is called “Priming.” A form of implicit memory. Google it (or however you do that these days). When your brain is given new information, it activates the neural network responsible for information association. It is not that “all of a sudden” this car is everywhere; you are simply aware of it now.

Your mind does this every day at work. When you feel frustrated, annoyed, bored or distracted your mind is alerting you. And you should listen.

We mostly ignore this because we have been conditioned to think that this is “just how it is.” We tell ourselves “I just had a bad day at work” or “today was a bad day“. So we go home, kiss our spouse, hug our kids and the feeling fades into the background and then it’s gone.

Make Priming Part Of Your Routine

To make a lasting change in your work routines make priming a consistent part of your day. Integrating AI into your work doesn’t make as much sense when you are not aware of where to integrate it. It just becomes another attention grabber, though a very cool one.

The way you prime consistently is by taking notes.

Write the following down daily, and you'll be amazed by the results within a week:

• Tasks that made you feel stressed, anxious, bored etc.

• All tedious and/or repetitive tasks.

Don’t judge what you do; the goal is simply to write it all down as part of your normal process.

Here is the secret formula:

Priming -> Consistency -> Awareness -> First Key To Change

Talking About Dani’s Stress Created The Automation

When I began working with Dani, I just did the “Prime -> Consistency” part for her, by talking to her about her stress and what was going on in her work life. That’s when she was able to recognize that her morning jolt was not “just how it is.”

Only then was I able to open Zapier, create an automation that takes every new email, places it into her CRM and then into her custom audience on Facebook. Took me 1 hour. But the main work happened in Dani’s mind. I just guided her along.

That is why you can do this yourself.

Priming caused Dani to save 30 minutes a week (26 hours a year). We did this same process for many other tasks, saving her lots of time in the process. But ultimately, the great achievement was removing stress from her life, and that is priceless.

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World First Gene Editing Therapy Patient, a Baby

https://www.pennmedicine.org/news/news-releases/2025/may/worlds-first-patient-treated-with-personalized-crispr-therapy

Incredible advances in science. A baby cured of an incurable disease with Gene Editing Therapy

AI Agent Automations

https://www.uipath.com/platform/agentic-automation

The world will have two types of businesses soon. The ones with AI integrated and the ones without AI

Waymo Recalls Software Due To Minor Collisions

https://techcrunch.com/2025/05/14/waymo-recalls-1200-robotaxis-following-low-speed-collisions-with-gates-and-chains/

Software recalls for hitting gates and fences

Humans don’t get recalls for drunk driving, accidents, deaths

The news often makes it sound so horrible that these self-driving cars are hitting gates, how dangerous. Ehhhhhh have you seen us humans drive?

Better Vision for Humanoid Robots
https://interestingengineering.com/innovation/atlas-electric-humanoid-robot-lg-eyes

Security Guards

Distribution Centers
Inventory Stocking

Operating time = 4 to 10 hours (this will improve)

Charging time = 10 min to 3 hours

Human work Shift: 8 to 12 hours
Min 2 humans per shift, assuming no vacation, off time etc

Google Alpha Evolve Summary
https://deepmind.google/discover/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/

It creates programs that it evaluates through tests and then improves on them. So anything that it can measure, where the outcome can be clearly defined it excels at. For example math, hardware design, computing infrastructure. It already improved data center scheduling and Chip rewrites for example.

Institutions & Central Banks Are Adopting Crypto
https://cointelegraph.com/news/central-banks-smart-contract-tokenization-pilot-bis

OpenAI’s proposed DataCenter in Abu Dhabi will need 5 Nuclear Reactors of power
https://techcrunch.com/2025/05/16/openais-planned-data-center-in-abu-dhabi-would-be-bigger-than-monaco/

Saudi Arabian Mining Company Signs Deal with MP Materials Corp
https://mpmaterials.com/news/maaden-and-mp-materials-collaborate-to-establish-full-value-chain-for-rare-earth-magnetics

Wood that is stronger than steel
https://techcrunch.com/2025/05/12/inventwood-is-about-to-mass-produce-wood-thats-stronger-than-steel/

They are starting with the skin of the building hoping to eventually move into the entire structure

material that has 50% more tensile strength than steel with a strength-to-weight ratio that’s 10 times better

AI Agent Adoption is already happening (use for tomorrow’s post)

https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-agent-survey.html

AI Agents vs Agentic AI: A Conceptual Taxonomy
https://arxiv.org/pdf/2505.10468

Netflix & Google brings AI Ads
https://blog.youtube/news-and-events/brandcast-2025/

https://about.netflix.com/en/news/netflix-upfront-2025-the-center-of-attention

What Happens When You Put AIs into a Room?
https://www.science.org/doi/10.1126/sciadv.adu9368

They develop social conventions much like humans do

NVIDIA update to foundational model to help robots reason more like humans
https://nvidianews.nvidia.com/news/nvidia-powers-humanoid-robot-industry-with-cloud-to-robot-computing-platforms-for-physical-ai

The implications are clear, factory workers, manufacturers, you need to learn skills to work with robots
Manufacturing is coming back to the USA, but not in the way you think

Robots to help weeding farms better than humans

https://spectrum.ieee.org/ground-control-robot-insects

Robots are taking on security jobs
https://www.straitstimes.com/singapore/who-let-the-bots-out-robot-dogs-on-the-job

Patroling, detecting intruders, guiding the vision impaired

$2,700 cost

The can understand verbal commands like: “take me to the grocery store”.
AI is even competing with humans best friend

China could lose 120M jobs to $35K robots
https://www.journee-mondiale.com/en/chinas-robot-workforce-threatens-123-million-jobs-as-prices-drop-below-35000/

Replace China with USA

Replace 123M with 29.7M

Learn to interact with Voice controlled AI now. They are trained on the same models

In addition the amount or Robots china is building is wild.
We are approaching an insane world.

Azure AI Foundry Let’s Multiple Agents Work Together
https://azure.microsoft.com/en-us/blog/azure-ai-foundry-your-ai-app-and-agent-factory/

China launches first of 2,800 satellites for AI Computing constellation in space
https://spacenews.com/china-launches-first-of-2800-satellites-for-ai-space-computing-constellation/

Doji lets users try on clothes with virtual avatars
https://techcrunch.com/2025/05/15/doji-raises-14m-to-make-virtual-try-ons-fun-through-ai-avatars/

Malls, Stores

FutureHouse Automatic Science Discovery Models Are Attacking the Cure For Blindness
https://www.futurehouse.org/research-announcements/demonstrating-end-to-end-scientific-discovery-with-robin-a-multi-agent-system

Since AI is reshaping the world, why not take advantage of it? Why not use it to make your business better? Why not eliminate all the tedious task you and your employees do on a daily basis? It is not hard, you may just not be seeing what’s possible.

The Story of Mike

I felt surprised the other day. Actually, I felt shocked. When you have been doing something for a long time you get to a point where you think you’ve learned all there is to learn. Not true.

I spoke to a former client of mine the other day. His name is Mike. Actually he was the employee of my client who was in charge of working with me to implement a workflow automation system built around their point of sales system and quickbooks. He is an accountant and bookkeeper by trade, in his mid 50s.

While we worked together he saw first hand how quickly you can automate workflows, business processes and build systems around the employees favorite ways to work. I mean, he basically learned by proxy right? Nope, wrong.

When we spoke the other day he told me about how his marriage is going, the life changes he has and updated me on what’s been happening with him. And then he mentioned to me that his new job is just so stressful. There are so many tedious tasks he constantly has to do and that he’s feeling burned out.

It blew my mind. He worked with me in automating an entire system and there he was not realizing that he can just do the exact same thing for himself in a few hours. It would solve his frustrations and free up his time.

Most People & Businesses Owners Are Simply Not Aware That This Is Possible

They are the frogs in the pot of water and they are not realizing that the water is heating up. They are not aware that the world is shifting underneath their feet.

I read a fantastic article which described a survey done for larger businesses who are adopting AI and serious automations into their processes. I am going to give you the secret to how you can reclaim your time and harness the power of workflow automation and AI.’

This is the first thing you need to realize. When you read about the progress AI is making you read things like:

• Solved a 50 year old math problem

• Helped synthesize proteins for pharmaceuticals

• Developed augmented vision features to help vision impaired people see

• Developed novel diagnostic tools for cancer

And you wonder: well how on earth does this relate to me? This doesn’t affect my accounting firm or my law firm. But oh yes it does.

You see AI is already past the ability to change small businesses. It can already do that. That is not what is interesting to the big companies. Changing small businesses is not what AI is made for, it is a side effect.

The technology to radically change your business and your day to day work is already there. You are just not seeing it.

New Companies In All Industries Will Be Built On AI

Andrew Wilkinson recently gave an interview in which he said something so incredible it’s hard to wrap your head around. When he merged three companies he was quoted $75,000 to $100,000 for the legal fees.

As a test he used Deep Research AI to draft the documents, then went to the same law firms, told them this was made by another law firm and instructed them to review the documents and make sure there are no glaring issues.

The final bill was $2,000.

If this does not shake you awake, I am not sure what will.

Idea #1:
You need to understand that it is no longer business as usual, that the technology is already there and that it is ready for you to use it. All you have to do is sign up.

Remember, you are the Frog. If you wait in the water, you may die. You need to understand that there is no more time to lose. You need to act and begin implementing AI. Here is an example everyone will understand:

Remember Borders Bookstore when the internet came out? What did they not do? Where are they now?

If you do not use AI you are Borders. Companies using AI are Amazon.

They are adopting, learning and they are going to crush it. Just from a unit economics perspective they are going to win the game.

Businesses, employees and workers as well as freelancers need to move with intention and adopt AI. You need to learn it and be comfortable with it. It’s a skill, like any other you had to learn for any job or any business. It is not magic.

Idea #2:
You need to accept that you have to learn a new skill. Go through the initial resistance, put in one hour a day and begin implementing AI into your business.

What happened to Mike?

At the end of our conversation I told Mike: “Hey why don’t you just use Zapier and automate these tasks like we did when we worked together?” He said: “I don’t know, I just got caught up in the daily grind you know?”

Learning the technology is not hard. Mike knew it, that is the easy part. It is becoming aware of how much it can do for you. That is the difficult part.

Here are some super simple action steps you should implement into your daily routine:

1. Look at every task, each tedious repetitive thing you or your employees do daily, as an opportunity to automate and reclaim time. Don’t think about whether you can automate it. Just look at everything. You’d be surprised.

2. Write it down! I cannot overstate the importance of writing it down. Otherwise you get caught up in the daily grind. The psychology of writing it down makes it real for you. You become aware (Idea 1).

3. Think of AI as an assistant, an employee. It is quite similar. You can give it tasks to do, jobs to complete, it will learn how to get better.
   
   AI is meant to enhance, not replace. I have many examples of automations I have built for clients where the savings were used to make employees happier in their job.

   Remember AI will not replace most things directly. People who use AI will.

4. Set aside time each day to learn https://zapier.com. There are other tools, but it is super easy. It is the perfect gateway to begin learning how to use automation and AI. If you want to go a bit more advanced learn https://lindy.ai (Idea #2).

Taking the first step is the hardest part. But I know you can do it.

So long, until next week.

References
https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-agent-survey.html

Internal Email From Mark Zuckerberg About The Cultural Relevance of Facebook

Internal Tech Emails

Facebook's "cultural relevance is decreasing quickly"

Welcome to Internal Tech Emails: internal tech industry emails that surface in public records. 🔍 If you haven’t signed up, join 50,000+ others and get the newsletter…

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a year ago · 45 likes · 4 comments

Wonderful insight into the depth with which Zuck thinks about his business. He knows the trends and metrics inside and out.
SNAP,

FB losing cultural relevance

Steps he is willing to take

Klarna is reverting back to Human Customer Service Reps from AI

https://www.customerexperiencedive.com/news/klarna-reinvests-human-talent-customer-service-AI-chatbot/747586/

One of the first to go all in AI

Reverted back to a mix of both
The trend is continuing: Humans who manage the AI will take all the jobs in the future

How To Win the Future Of War

Incredible interview with Joe Londsdale, Founder of Palantir

How Philosophy is the most studied subject at Palantir

First Principles Thinking
How many specialized autonomous ships have better unit economics than our current Navy

How it is cheaper to deliver missiles to targets from Space than use a fighter jet

Early Research Into Cement as a Battery
https://www.chemistryworld.com/news/cement-like-building-material-doubles-up-as-an-electrolyte-in-rechargeable-battery/4021469.article

While there are still limitations during certain chemical reactions, early research is interesting

Something to keep an eye on.

AI will likely be able to help run chemical simulations

How Humans & Robots will work together
https://techcrunch.com/2025/05/11/amazon-offers-peek-at-new-human-jobs-in-an-ai-bot-world/

Vulcan offers a peak at the new future

AI controlled Robots will work alongside fewer humans

These humans will require specialized AI knowledge

OpenAI is acquiring customers faster than the competition
https://techcrunch.com/2025/05/10/openais-enterprise-adoption-appears-to-be-accelerating-at-the-expense-of-rivals/

Interesting to note that OpenAI is still the leader in many respects. Though Google is catching up ever so gently.

LLMs are going to get cheaper and the competition is high at the moment
LLMs will not be like cloud I think, it till have lower margins until we catch up the energy costs

Alibaba ZeroSearch poses a big potential risk for $GOOG
https://venturebeat.com/ai/alibabas-zerosearch-lets-ai-learn-to-google-itself-slashing-training-costs-by-88-percent/

This is very good news for Startups
You can train a model without needing to use Google Search API or build your own crawler.
This will reduce costs for LLMs further

France to build Robot Army by 2040
https://www.straitstimes.com/world/europe/french-army-hopes-for-combat-ready-robots-by-2040

This just cements the trend we have been seeing

AI controlled Robots will be the norm soon
Since France wants the army, they will likely be open to easier regulations on the civilian robot front
Notably they also have the largest European LLM company in Mistral

Improving Naval Ship Acquisitions

Construction Physics

Improving Naval Ship Acquisition

This is a policy proposal written by Austin Vernon and myself for improving US naval shipbuilding. It was produced for Rebuilding.tech, a techno-industrial policy playbook curated by IFP, FAI, and American Compass…

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a year ago · 88 likes · 17 comments · Brian Potter and Austin Vernon

Fasticinating read

Goes hand in hand with the Joe Longsdale interview

Ship Building can come back to the USA, but it will be quite different
Andruil is making autonomous submarines, jets and drones.
The world will look differently

And the jobs that will come back to the USA are not in the factories, they will be in creating the AI and robots to run the factories

Andrew Wilkinson from Tiny

Great interview

He sees a future where generative AI will be so good and custom tailored to our individual likes that we will only want to consume it. Especially younger generations I feel will be like that. They will not hang on to the nostalgia of wanting to consume human content

Vargas Space Company - Microgravity Pharma

A fascinating company, concept, anything Space intrigues me.

Google AlphaEvolve Scientific & Math Discoveries

https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/AlphaEvolve.pdf

AlphaEvolve improved Strassen's 1969 algorithm, solved 20% of 50+ outstanding math issues with better solutions than humans.

Small businesses and workers really need to get ready for what is to come.
We hear about these innovations and are in denial. We sort of hold on to hope that it won’t affect us, but it will.

When I first started investing I had no idea what I was doing and lost $15,000

I read all the famous books, I watched every YouTube video from Buffett I could find and I read every shareholder letter that was publicly available. I did all the steps that everyone always talks about.

I made myself a list. I knew that I had to:

1. Be a voracious reader. Every legend reads a lot

2. Read lot’s of 10ks. They are the bread and butter

3. Clone other investors and figure out why they made the investment

4. Be dispassionate and rational. Everyone talks about how I need to leave my emotions at the door.

So I started reading about Aluminum companies, costco, coca cola, I read about all the great companies from the past, studied 100 Bagger 10ks to find commonalities, began cloning and …..

Well, I started losing money.

And then I realized that one reason I was losing money is because I was investing in areas outside of my circle of competence.

But I did not know it! I fooled myself

When you are trying to figure out a problem: INVERT

Here is a surefire way to know that you are not in your Circle Of Competence

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Introducing the Circle Of Passion

Investing requires synthesizing a lot of information. Investing into $UBER requires you to know about:

1. Mobility & Transportation trends

2. Regulations pertaining to Taxi services

3. Autonomous Vehicles, trends and their future

4. Competition in the entire world

5. Freight and Shipping trends

6. Food Delivery

7. Doordash

The list goes on. If you want to be knowledgeable about all of these things, there is only one way to get there:

You must be passionate about the topic

Passion is scientifically proven to improve your information retention, understanding and synthesis. Your reward system is more active when you love what you are reading, which directly influences your desire to learn more.

Passion therefore is proven to increase your understanding of your circle of competence.

Invert Your Circle of Competence

Here is the surefire checklist you should think about all the time when you’re researching, when you’re cloning or when you’re screening.

If the answer to any of these questions is yes, then drop it and move on:

1. Am I bored with what I am reading?

2. Am I often re-reading the same passages over again?

3. Am I getting distracted easily by unimportant things?

4. Are my thoughts drifting, though there’s nothing else major going on in my life?

5. Do I keep thinking about something else to do right now?

6. Would I rather read a different 10k?

If your reading does not pass the Circle of Passion filter you are guaranteed not within your circle of competence.

Check your COP and then worry about your COC.

What You Should Do Next

I preach this all the time. Keep a journal. Write down:

• what you’re feeling,

• experiencing,

• thinking,

• doing,

• when you’re distracted,

• what topic you were reading when you felt X,

• Write down Everything

Writing it down brings awareness you otherwise often miss. Also scientifically proven by the way. Google it, Check ChatGPT with some deep research it’ll confirm it.

“You cannot improve what you don’t measure”. You do it in the Gym, do it here too.

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Or should I add my comments and a quick summary underneath?

META CTO About The Next Paradigm Post iPhones

Google Breakdown of How To Power American Innovation In the Future

https://static.googleusercontent.com/media/publicpolicy.google/en//resources/powering_new_era_of_american_innovation.pdf

AI Scientist Joins The Hunt For Alien Life

https://www.nature.com/articles/d41586-025-01364-w?

META partners with Groq to Increase API Speed

https://www.techrepublic.com/article/news-meta-llama-api-groq/

OpenAI Statement About Reverting ChatGPT4o for Being Too Agreeing

https://openai.com/index/expanding-on-sycophancy/

Detailed Breakdown Of Solar Panel Alignment With The Sun (long)

https://terraformindustries.wordpress.com/2025/04/29/the-future-of-solar-doesnt-track-the-sun/

Open Letter From Tech Leaders On Wages In the AI Age

https://csforall.org/unlock8/open-letter

The Incredible MOAT of SpaceX

Amazon launches Vulcan: Robot with Sensory Touch

https://www.aboutamazon.com/news/operations/amazon-vulcan-robot-pick-stow-touch

Drone That Attracts Lightning

https://group.ntt/en/newsrelease/2025/04/18/250418a.html

Solar In Space Startup

Chinese Drone Tech Can Induce Rain

https://interestingengineering.com/science/china-drone-powered-cloud-seeding-rain-xinjiang

Expands It’s Partnerships With Autonomous RoboTaxi Companies

https://techcrunch.com/2025/05/07/uber-invests-100m-in-weride-to-fuel-robotaxi-expansion-across-15-more-cities/

Everything from the All-In-Podcast
https://www.youtube.com/@allin

AI Designed DNA controlls Genes

https://www.sciencedaily.com/releases/2025/05/250508112324.htm

In early 2022 something rare happened. $META began an 8 months long 70% decline. In the world of investing that is a rare opportunity.

In the early stages the narrative was that people didn’t understand the Metaverse. Why would we all want Avatars of ourselves in virtual worlds?

In the middle stage it was analysts and media outlets being baffled by $60 billion in Capital Expenditures. Why would Zuckerberg spend so much money on a virtual cartoon world that people will not spend that much time in?

In the last stage towards the winter of 2022 all of a sudden social media as we know it is over and META might be a value trap. TikTok is overtaking META with short form videos, a change Zuckerberg did not see coming.

As these things unfold, it is difficult to not be influenced by the headlines and negative stories. And of course you should be conscious of the narrative, because we need to investigate the reasons. After all, in 2007 several companies also began a gradual decline and they never recovered.

What made all the difference in my determination, and why I was able to continuously buy META shares throughout the uncertainty and worry I was feeling, was not some incredible knowledge I had over others, or some analysis I did that was better. No.

It was Passion

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The Incredible Power of Passion

You see, passion drove me to read all annual reports, quarterly reports and earnings call transcripts from 2018 all the way to Q1 of 2022. I loved the reading, because it felt good to learn about what was going on. With this passion I learned that 75% of the Capital Expenditures were for physical hardware to build out the computer infrastructure to “own the next paradigm” shift and to make headsets.

My passion for wanting to know about the competitive landscape helped me understand that META has withstood other competition in the past. META beat MySpace and outlived SNAP quite nicely. In response to TikTok META already announced and launched Reels and said it will build it, learn the customer behavior and then monetize it in a year or two.

My passion made me realize that the Metaverse everyone in the media was freaking out about, was a small part of a much larger investment into AI and infrastructure. So with an extensive amount of reading it seemed much more likely that a company that makes billions of dollars a quarter in Free Cash Flow, despite the CapEx will likely not go bankrupt anytime soon.

It was my passion that has now made 4x my money in a company that has so much un-monitized potential.

Passion To The Rescue

Many of you are now looking at a similar situation with Google. The media is blasting us with headlines and stories about how AI is attacking Google Search, how Google is losing Browser search share in Safari for the first time and how their cash flow generation will be impacted.

If you feel passionate about search and AI, about autonomous vehicles, about AI advancements in science and you have watched how powerful YouTube is, you will have already realized that the future of Google is not in immediate danger.

Waymo is doing 250,000 RoboTaxi rides a week, while Tesla is just talking about it. YouTube’s ad revenue of $36b is growing annually, it has TV subscriptions, streams movies, sports and has 125 million subscribers.

Did I mention that Google's AI can translate Dolphins and synthesize protein structures to help create better medicine in the future? And they have their own AI search that works exactly like ChatGPT, it just is being rolled out more carefully to transition current legacy search customers? And that this is not all

The Art Of Investing Is Emotional In Nature

You can learn everything about how to think about investing from Books, Buffett and YouTube. If you’re motivated you can do that in 3 months. But to fully understand how your emotions will affect your decision making, cannot be learned from books alone. It requires self-awareness, guidance and most of all a desire.

How To Be More Successful In Investing

Create a passion filter

If you are reading an annual report and you have to re-read the same paragraph three times, stop reading and move on.

If you need to make yourself study an industry, stop and move on.

If you are not interested in autonomous vehicles, but feel this urge to follow up on GOOG, don’t. Stop, move on to what you care about.

There are endless companies to study and endless industries.

The most assured way to become good in a few and to build a solid circle of competence is to feel passionate about researching and reading about it.

Do This Every Day From Now On

1. Get a notebook (digital or paper, either way)

2. Journal your investment journey every day

3. Focus specifically on what makes you bored, tired, is difficult to read, what distracts you and what makes you feel excited, curious etc.

4. Build your passion filter

This is the first step in becoming more self-aware as an investor. It is all so important, because without it, your heart and mind are not working together and you will make a lot of costly decisions.

Trust me, with the awareness alone, your process will naturally adjust and become more effective.

Wanna go the extra mile?

Journal how you feel about the news you see and read every day. Start becoming aware of the effect your information environment has on you.

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If your business needs you all day it is just a stressful job with more responsibility. The core operation should run without you, otherwise you will not grow

Here is everything you need to know about my publication “Intellectual Wandering“ in a few minutes.

My Mission

My single minded goal is for you to build Optimize Your Workflows so that your business, career and entreprenurial ambitions are as efficient as possible.

The age of AI enables us to harness a new kind of technology, one that can engance our operation in ways that weren’t possible before.

Investigate | Innovate | Automate

What Nobody Will Tell You

Burried deep underneath the daily News Headlines about the fast paced progress of AI lies a truth that you will not hear often: AI augments you. It amplifies who we already are. Consequently it will enhance the business workflows, routines and habits that already exist.

AI is no magic bullet. It can only solve the problems that you know you have. The first step in any workflow optimization therefore is analyzing your current processes (routines / habits).

In this publication you will:

• Read inspiring stories of people who replaced their old processes with ‘Power Habits’ and then supercharged them with technology. Generating workflow optimizations is 85% a mental shift and 15% technology. Every Tuesday this publication guides you on how to integrate both into your business, work and life.

• Read about my own personal journey and how I trained others. Over the past 10+ years I have helped businesses and entrepreneurs generate $1M+ in savings. I will share with you how I did it.

• Subscribers will also receive Subscriber-Only content. As a subscriber you will be the first to know about new techniques, new processes and technologies I use with my clients.

If you are reading this then you want to build Power Workflows, you want to optimize your routines and habits. I will help you build a successful business and use technology to supercharge it. You are in the right place.

Let’s get optimizing.

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About Me

The cliffnotes version

I began my own journey in 2011. I just became a Flight Instructor of a Flight School I would eventually lead as the CEO. Flying was like an adventure that combined an intellectual challange with thrill and I knew I was in the right place.

But I almost lost my job. My boss said I had the talent and I had the love for flying, but I had no discipline. He sent me home for a long weekend and asked me to think seriously about what I want out of life. That was the wake up call I needed. It was the moment when I realized, if I want to be successful, I need to have a mindset that supports my dreams.

That is where the idea of Power Habits was born, which would later transform into my approach to Workflow Optimization.

When I implemented ‘Power Habits’ into my daily life everything changed. Since then I trained many Airline Pilots, became the Chief Flight Instructor in 2013 and began to realize that I wanted to help bring the entire school to the next level.

With an insatiable hunger for knowledge and a nack for technology I implemented cloud systems and automations and rebuilt most of the processes of the the entire flight school operation. This is where I learned the next valuable lesson.

This is when I began seeing opportunities for helping other businesses.

So in 2015 I launched my first Work Optimization & Software Development company Abixweb and in 2021, after being the Flight School CEO from 2019 to 2021, I launched Saiwala.io with the stuborn, single minded focus to help people optimize their time.

Throughout my journey I have generated $1M+ in Savings for business, entrepeneurs, creators and employees. These savings can flow straight to a businesses bottom line or be allocate to something else. And I am especially proud that most of my business clients have given this time back to their employees.

Here is what I will do for you

I will pour my heart and soul into giving you tools to supercharge your productivity.

• Together we will challenge conventional thinking about work by not accepting the common “this is just how it is“ mentality.

• I will teach you how the mental shift required to begin optimizing your routines, processes and workflows.

• We will use science to build ‘Power Habits’ into your daily actions that will build the foundation to supercharge your ‘Workflow Optimizations’.

• I will give you insight into my personal story and my clients stories to show you the impact my coaching / training had on their lives.

• Together we will explore innovations, software tools and resources to help you take your ‘Power Habits‘ to another level. The level of Workflow Optimization.

• Most importantly: I will tell you the truth even if you may not want to hear it

What I need you to do is to be open minded and be ready to take decisive action, because we are about to change your world.

I am an ‘Audacious Optimizer’ and I welcome you to join me. Let the optimizing begin.

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