AI-generated code now accounts for roughly 41% of all code written globally, and 84% of developers use or plan to use AI coding tools, up from 76% in 2024. Production capacity for software has expanded faster in three years than in the previous twenty.
Whenever a production constraint disappears, the value in the system relocates. Understanding where it went is the difference between benefiting from this and being flattened by it.
The historical pattern
Scarce in 2020
Scarce in 2026
Engineering capacity
Knowing which problem is worth solving
Access to tooling
Distribution to a specific buyer
Technical execution
Credibility with a cautious buyer
Time to first prototype
Evidence the prototype was worth building
This has happened before in other industries and the pattern is consistent. When printing got cheap, the scarce thing became editorial judgement. When distribution got cheap, the scarce thing became attention. When manufacturing got cheap, the scarce thing became design and brand.
In each case the people who owned the old scarce resource lost position, and the people who owned the newly scarce one gained it. The transition was uncomfortable for everyone and obvious only afterward.
Where value went this time
Three things became scarce as code production became abundant.
“When you could build one thing a quarter, choosing badly cost you a quarter. When you can build one thing a week, choosing badly costs you a year.”
First, knowing which problem is worth solving. When you could build one thing a quarter, choosing badly cost you a quarter. When you can build one thing a week, choosing badly costs you nothing individually and everything cumulatively, because you can now spend a year shipping fifty things nobody wanted.
Second, distribution. If everyone can build the tool, the person who reaches the buyer wins, and reaching the buyer got harder rather than easier over the same period. Organic reach on the main B2B channel fell between 60% and 80% from its peak.
When you could build one thing a quarter, choosing badly cost you a quarter.
Third, trust. A buyer facing ten similar tools built by unknown vendors selects on credibility, and credibility is not something that can be generated. It comes from having done the buyer's job, from named customers, and from being specific in a way that only genuine experience allows.
Turn what you know into what you own.
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Join the WaitlistWhat this means for the abundant skill
Being able to produce software is now roughly as differentiating as being able to produce a document. It is a competence, not an advantage. Treating it as an advantage is the single most common error among technically capable founders in 2026.
The corresponding error among non-technical founders is treating the inability to code as a disqualification. It stopped being one, and the thing they usually do have, specific knowledge of a broken workflow, is now the scarce input.
The practical consequence
Spend proportionally more time on problem selection than you think is reasonable. A week spent confirming that a workflow is genuinely broken, quantifying the loss, and finding three people who would pay is worth more than a month of building, and it is the step people skip because building feels like progress.
The validation tracker approach covers how to do that without spending anything. The insight engine is the structured version.
What to do if you are technical
Pair with domain knowledge rather than trying to acquire it quickly. The fastest route to a durable venture for a technical founder in 2026 is finding someone who has spent a decade inside a broken workflow, not researching one from outside. The knowledge asymmetry is real and it does not close through reading.