The Age of the Idea Guy
AI is lowering the barriers to building businesses with technology. The distance from zero to one is shrinking. Welcome to the age of the idea guy.
We all know them. Maybe you’re even one of them.
The idea guy (or gal).
They itch for new information and tinker incessantly. They look for the gaps and margins in life—the unmet needs, the missing services, the extra edge to be gained or utility to be added. They have a constant need to point the things that could be just a little bit better in the systems and services around them.
It’s that friend at the dinner party who can’t help but pitch everyone their latest app idea. Or the neighbor who keeps insisting there’s money to be made in a new franchise opportunity. Or the uncle who keeps telling you he’d invest if you’d just build that website business he won’t stop talking about at family gatherings.
Here’s the thing about idea people—until recently, most couldn’t execute the ideas on their own, especially technology ideas (which, let’s face it, most ideas today have some tech component required).
Except for a limited group who could bridge deep business, design, and technology expertise, idea people have been reserved to the side lines. Their work contained within pitch decks, design diagrams, and prototypes. They gravitate toward strategic, creative, or business roles rather than builder/founder roles, where ideas are currency and execution can be left to others.
If they were lucky, they might find their way into R&D or innovation roles. Or become founders. And when idea people did become startup founders, it often required a technical cofounder to be taken seriously and bring the idea to life.
But the times are changing. And the idea guys are starting to catch on.
The AI Revolution
Through AI (and especially LLMs) the power to bring ideas to life through technology has never been more accessible.
Not only can websites, apps, widgets, plugins, extensions, etc. be created on the fly with AI, but the business models and marketing plans needed to sell them can now be generated and augmented using AI too.
The time from zero to one has exponentially decreased from months of time and tens of thousands of dollars, to days or hours and a few hundred dollars.
AI: The New Abstraction Layer
Technology is like an onion. There are a lot of layers—and AI is the latest layer.
Binary is abstracted by Assembly → Assembly is abstracted by programming languages such as C, C++, Java, JavaScript, and Python → High-level programming languages are abstracted by libraries and frameworks like Ruby on Rails, the Java Standard Library, Django for Python, and React for JavaScript → Libraries and frameworks are abstracted by application software such as web browsers, word processors, and games → Application software is abstracted by user interfaces and user experience design.
You get the picture.
What’s important here is that each layer of abstraction in the stack makes it increasingly easier to build with the layers below it (without having to really know anything about those underlying layers). By rolling up functionality, adding new capabilities, and improving usability, abstraction layers allow more people to make use of technology in new ways.
Higher abstraction → broader accessibility → more builders
No-Code and Low-Code tools are the latest attempt to further abstract web and software technology. Squarespace, Webflow, Shopify, etc. removed the need for creators to know code in order to build effective business websites, e-commerce brands, and web apps.
But they fell short. They were half-steps. They compromised important things like customization and ownership in exchange for drag-and-drop layout editors. Useful for those committed to building a website without code, but still clumsy and cumbersome at scale. Too much so for most average users, and too little for bigger businesses.
Enter AI. Like many layers before it, AI enables a new level of technology access and further removes the need for proficiency in the underlying tech stack layers (ie. software engineering and web development). At the same time, it returns direct ownership of the code and customization by allowing a user to ask AI to manipulate the code according to preferences.
But AI is also VERY different. It not only abstracts the technology stack, but it does the same across almost every aspect of the business stack too.
Let that sink in for a moment.
Suddenly, a single individual with a clear idea can execute a working app, business plan, press release, launch strategy, marketing campaign and content, SEO strategy, and pitch deck in less than a week. And if done correctly, with vision and focus, effective prompting, and iterative improvement, one can reliably achieve above average results compared to that of most professional office workers.
This is a game changer. The hardest part of building a business once you have a valid idea is creating the momentum—for yourself and for your idea. First to articulate and understand the idea. Then to get something built, tell the world about it, and iterate and grow as people engage (or not). As someone who has done this many times on both big and small projects, it is hard. And it is common to hit roadblocks that kill your momentum mid flow and destroy the idea before it’s ever had a chance.
AI eliminates these problems. It can be used to augment weaknesses and automate the tasks that typically distract and derail the creative process.
It unlocks the ability to move at the speed of your idea (or closer to it). This creates a new kind of momentum in idea building that can result in more outputs at consistently higher qualities.
The New Model
The age of the idea person is giving rise to a new class of solopreneurs and startup teams.
These are individuals or small teams of AI-augmented human specialists with broad generalist knowledge combined with deep expertise in multiple subject areas. Think Ironman and Marvel’s Avengers, but using AI to orchestrate and execute business ideas faster, more effectively, and with less external support than ever before.
Rather than seeking big fundraising rounds and measuring headcount, they are rapidly scaling cash-flowing businesses in record breaking time. Rather than pitching ideas and half-built MVPs, they are launching fully functional applications and services out of the box.
Examples
The following companies are small teams or solopreneurs that reached $1M ARR with AI products in less than a year’s time, and often without going the traditional route of venture-backed startup building (see the list on Twitter/X).
Levelsio (solopreneur)
Danny Postma (solopreneur)
Many of these business ideas are relatively small, niche, and what you might call GPT wrappers—but that’s the point. The smaller ideas that used to be impossible to build profitably are suddenly within reach and have massive revenue potential.
People don’t want to do the hard work of iteratively interacting with AI to get to the desired result—they’d much rather pay a small price to have someone else dial in those AI capabilities for them, and just deliver the desired outcome.
People mostly just want the “easy button.”
Predictions
What’s to come in a world where anyone can build an app or a website? What happens when anyone can be a software developer?
Frankly, who knows. But I have a few hunches:
Influencer software companies
One of the greatest current untapped opportunities in digital product development is in influencer communities. These are dedicated followers, engaged around common interests, needs, and motivations with shared tastes and preferences.
We’ve seen influencers get into CPG brands (e.g. Prime), beauty and fashion (e.g. Fenty), cryptocurrencies, games, and much more. These are often great businesses, but they typically remain focused in the expected sports, cpg, fashion, entertainment, and sponsorships. We haven’t yet seen influencers build more serious, long term businesses, especially technology and software companies. AI will change this.
Being an influencer today means being tech-savvy and being a solopreneur or (if you’re lucky) working with a small expert team to orchestrate and execute projects. You cannot create digital content, edit it, post it, manage multiple communication streams, and build a successful social media brand without knowing your way around technology products. So it’s only natural that influencers will begin to have an opinion about what tech products might be useful for themselves and their audiences. And with existing follower communities eagerly ready to test and launch new offerings, the stage is set for new influencer-led business ecosystems to emerge.
Mr. Beast, is an early mover in this category. He and his team recently announced the launch of ViewStats, an analytics software company aimed at serving fellow video content creators. He’s the best in the world at making YouTube videos and understanding what his viewers want to see—and he’s launched a software tool to help others better understand their YouTube audiences.
It’s so painfully obvious, you wonder why no one else is doing this kind of thing.
Hyper-personalization
AI will change the meaning of “customized software” and “user centered experience.”
Surface level improvements are already here. LLMs naturally possessing the ability to tailor themselves to the implied nuances, moods, attitudes, and motivations when we interact with it. Algorithms already know what we’re going to buy before we do.
But moving forward this will go even further. This new level of hyper-customization will unlock individualized software and hyper-specific solutions in which the entire functionality and user experience is tailored to the specific needs of the individual or small community using it.
It will start with dynamic and adaptive interfaces. Data and content will adjust even more than it already does to tailor to your preferences and needs. Then the full stack will liquify through AI, becoming more like clay to be molded and torn down for each user than the current brick and mortar internet infrastructure we see today.
The early building blocks for this can be seen in emerging generative UI frameworks and new Ai product experiences—like Perplexity’s “Pages” feature which builds wikipedia-like pages for any subject on the fly using AI to aggregate and summarize content from across the internet.
Launching with a prototype working product
More founders will launch with working betas, rather than attempting to pitch investors on mockups and prototypes. AI increases the velocity at which you can create, and this means moving faster and further with ideas before needing outside assistance.
More shots on goal = greater chances of scoring.
AI reduces the distance from zero to one for idea creators and company builders. This means building more upfront, getting to market sooner, learning more for customers, and iterating faster to find product-market fit.
Companies like Replit are making this possible, and more are following suit.
Democratizing innovation
It seems almost silly to write the phrase “democratizing innovation” because the idea has been used so many times to describe so many different technology advancements in the past. But it’s true. AI is democratizing business and technology innovation in ways we previously only imagined.
Now anyone with a computer and an internet access can tap into a system that provides intelligence, at college graduate and post-graduate levels, across a wide spectrum of knowledge areas and fields of study. In other words, all the expertise you could probably ever need to run a basic business, in your pocket—but only if you know how to use it.
As more people master the capabilities provided by AI, we will see new research and new ideas emerge as people are able to explore information in new ways and focus on problems not previously within reach.
Single use or “disposable” software
When a resource becomes cheap enough, humans stop caring whether the resource is conserved. Software is expensive because it is expensive to build and maintain. We covet it and tend to it because it is expensive to build and maintain.
As AI code writing improves, this cost will drop. As costs decrease, so too will our expectations that software be the grand constructions of intelligence and expertise that we’ve seen in the past decades. Sure, there will still be behemoth tech companies powering massive ecosystems and infrastructure. But the cheap parts—first the UI and the content, then more of tech stack—will begin to be thrown away when we are done with them instead of kept to sit on a server. More accurately, our AI’s will throw away its own code when done using it to complete whatever task we’ve requested.
The economics will be the ultimate driver, but the personalization and need-specific solutions will be the fuel that speeds up change. Software is becoming a commodity, and the idea people, powered by AI, are set to take advantage.
The catch
The rules of the game are changing.
The success of an idea increasing depends less upon the ability to access capital or possess advanced technical knowledge. More and more it will depend on the ability to traverse a wider range of subjects at a deep enough level to know what to build and how to accurately describe it to AI.
The broader and deeper you can go, the faster you can bridge disparate ideas into meaningful outcomes. Really, it’s about learning to learn and adapt. Fuzzy problem solving at scale.
While AI can handle much of the heavy lifting, the idea person must still understand the nuances of their industry, audience, and the problem they are solving. They need to be adept at asking the right questions, providing the right prompts, and making critical decisions based on AI’s output.
The role of the idea person is evolving. They are no longer just the dreamers (or “that person” at the party); now they are becoming the doers. The future belongs to those who can harness the power of AI to turn their ideas into reality, quickly and efficiently, while continuously learning and adapting along the way.
The age of the idea guy has arrived.