Happy New Year everyone.
I usually end the year with macro analysis and predictions for the year ahead.
This time, I want to focus on a paradigm shift in software that will quietly reshape how companies are built, how labor is valued, and how power moves in technology.
Every major technological step change removes a barrier people assumed was permanent.
When that happens, power does not redistribute gradually. It redistributes structurally.
That is what is happening in software right now.
The gap between thinking and building software has collapsed.
For most of the history of modern software, ideas were cheap and execution was scarce.
Coding software required specialized knowledge, coordination across teams, capital, and time. That scarcity shaped company formation, labor markets, venture capital, and entire industries.
Many had ideas. Very few could execute.
If you had an idea but no coding background, you had two real options. You raised money to hire developers, which often meant months of pitching before anything existed, or you convinced a technical cofounder to join you before there was proof the idea worked.
That scarcity no longer exists.
Last April, while walking the fascinating streets of Old San Juan in Puerto Rico with my 12- and 10-year-old sons, they kept asking about the history of the buildings we were walking past.
I started taking photos with my Iphone, prompting ChatGPT to explain each building in a way that would interest a 12-year-old, and then asking ChatGPT reading it out loud.
They were fascinated and wanted to do this for every building. After a while, I got tired. Then they had a simple idea.
Why not combine Google Maps, ChatGPT, and our AirPods so we could walk around and have a real time AI tourist guide explaining buildings as we passed them?
Surely, it was a moment of proud for a father. But it was even bigger.
When we returned to Washington DC, we opened an account on a vibe coding platform and built a prototype. The idea worked.
But shipping it still required an engineer. App Store deployment, cloud setup, backend orchestration, and LLM integration. Execution was still gated. We asked a friend to build but like most side projects, it stalled.
With the latest generation of AI native web coding tools, infrastructure, AI integration, backend logic, and deployment collapsed into a single workflow.
In the last five days, I built three products myself. One is live. One is close to launch internally for our company. One is actively helping a company I invested in.
I am not an engineer. I studied international affairs and business. Now, I am building software. It means everybody can.
What we are seeing now is the centaur model becoming the default. Human plus AI.
The human contributes what machines cannot: problem selection, market understanding, judgment, taste, and trade off decisions.
The AI handles what humans should not: code generation, system wiring, scaling, iteration, execution at machine speed, design support, and maintenance.
This is not AI replacing humans. It is AI removing artificial scarcity around execution. What remains scarce, and therefore valuable, is clarity.
AI would not come up with the tourist guide idea. A curious 12-year-old did.
When thinking and building converge, the unit of production becomes the individual mind.
For years, no code tools took users from zero to roughly 70 percent.
The remaining 30 percent, backend logic, APIs, deployment, still required real engineers. That preserved the old power structure.
We have now crossed from zero to 70 into zero to 95.
The remaining 5 percent is stabilization, security, and scaling. Important, but downstream of product existence. This flips the startup lifecycle.
Founders no longer need a technical cofounder to begin, capital to prototype, or large teams to validate ideas. They need conviction and precision.
At my own company, with my team, we rebuilt an internal Asana equivalent in a week, tailored exactly to how we operate based on our specific workflows.
That raises an obvious question. Why buy Asana or any pricy enterprise software without strong marketplace or network effects?
Generic SaaS exists because custom software was historically expensive.
That assumption has collapsed.
A supply chain company can now build software reflecting its actual products, routes, bottlenecks, and failure modes rather than an industry average. A media organization can build a multilingual digital newsroom with hundreds of AI agents ingesting sources, synthesizing narratives, generating visuals, and producing content continuously, overseen by a small human editorial team.
This is hyper customization at scale, and only the organization itself can do it correctly.
The most profound impact will not be on software companies. It will be on white collar labor.
Roles built around repetition, synthesis, coordination, and incremental analysis are being structurally repriced. Not eliminated overnight, but permanently devalued. Judgment scales. Presence does not.
This is not a cyclical downturn. It is a technological reset.
The same logic applies to venture capital. Capital historically mattered because execution was expensive. When experimentation costs approach zero, capital stops being permission and becomes acceleration.
Founders now have leverage. They can build MVPs independently, test real demand cheaply, iterate before fundraising, and delay or avoid institutional capital entirely. Venture capital does not disappear, but its leverage shifts later in the lifecycle. The early stage monopoly on momentum is gone.
What is changing is not tooling. It is the structure of advantage.
Entrepreneurs with real domain insight benefit. Operators who understand workflows benefit. Solo founders and small teams benefit. High judgment talent benefits.
Horizontal SaaS without moats does not. Replaceable white collar roles do not. Early stage capital as gatekeeper does not.
The pattern is consistent. Anything without proprietary insight, network effects, data, or algorithmic edge is vulnerable.
The practical advice is simple:
Entrepreneurs should experiment more aggressively. The cost of failure has collapsed. The cost of delay has increased.
They should be aware of the fact that the moat in the AI-era is key. When building is commoditized, you have to build and defend your moat if your goal is to become the ultimate tool in your field. This is why my firm Enquire.AI is building on these principles.
Developers should move upstream. Code is no longer the moat. Product ownership is. They focus less on tools and more on thinking. Tools commoditize. Judgment compounds.
Investors should add value beyond capital. Pattern recognition, access, and synthesis matter more than ever.
Everyone personal or commercial will think less about buying software and more about building it. That mindset shift is the tell.
The next billion-dollar unicorn may be built by a small team or even a single individual using AI native coding, cloud infrastructure, generative media, AI-agent force led automated marketing, and machine assisted decision making.
This is not the end of software. It is the end of friction between ideas and reality.
Once that friction is gone, everything else reorganizes around it.
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