An honest take about AI.
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💬 Topics:
- Code generation isn’t bottleneck;
- Constraints enforce product discipline;
- Lower friction increases complexity;
- Jevons Paradox applies to software;
- AI reduces cognitive training;
- Distribution is a real bottleneck;
- AI layoffs mask mismanagement.

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A critical take on the AI coding hype cycle, prompted by a tweet from the creator of Open Code Agent. The core argument is that code was never the real bottleneck in software development — product thinking, prioritization, and system reasoning were. Lowering the cost of shipping features removes healthy constraints that forced teams to make sharp decisions and kill bad ideas early. Drawing on the Jevons paradox, the piece argues that cheaper code generation will expand software complexity rather than reduce developer demand. It also highlights IBM tripling entry-level hiring, Sam Altman acknowledging AI-washing layoff trends, and the irony of Claude Code's head declaring 'coding is solved' while Anthropic offers $50K signing bonuses for engineers.

An AI CEO finally said something honest...

Lately I saw a different post with a claim that in AI era, when code can be generated quickly, we will be focusing on ‘why’ we should build something.
But the reality is completly opposite, just like in the video - times where we were focusing on “why” are gone. Thinking “why should we” was coming from friction. Ideas were treated with caution. Now friction is removed and actually nobody asks “why”. Lest just instantly implement thousands bad ideas.

The irony of getting more work for software developers the faster AI produces code. Giving power to the general public (who don’t know how to code) to build apps will give more jobs in the future and I firmly believe that.