Code is no longer scarce. 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Good code is. As AI makes code easier to produce, engineering value depends on maintainability, system complexity, and impact over time. ![](/assets/HfT49C7HgKAGgSYLaI9CE4u9JRI.B3_TdzAj_fgsiG.webp) ![](/assets/NkiThIEDcY7u0hU9E3jSSObfmhw.D4Vvpx7I_ZMAkJ4.webp)Dave Garcia·Founder and Co-CEO·Feb 12, 2026 ![](/assets/ieXEW9CiQPP4NH7J8MzoVBMFSss.Bt4vWA8g_Z1Xm28A.webp) The world is changing faster than most engineers want to admit. Writing code is no longer a scarce skill. Anyone can generate it. Bots can scaffold features, refactor files, and push pull requests in minutes. Code is everywhere now more than it ever was. And yet, something feels off. Teams are shipping more, but understanding less. Repos are growing, but systems feel heavier. Velocity looks great on paper, while maintainability quietly collapses underneath. This is the paradox of the new era: **code has exploded, but good code hasn’t**. The problem isn’t that AI writes bad code. The problem is that it writes *plausible* code. Code that works, passes tests, and looks reasonable at first glance while quietly increasing complexity, coupling, and long-term cost. As a several times CTO I can tell you how dangerous this becomes in the mid-term. For years, we used quantity as a proxy for progress. Commits, tickets, PRs. It was never perfect, but it sort of worked when code creation itself was the bottleneck. That bottleneck is gone. With coding agents, all kinds of code proliferate everywhere. The hard part now isn’t producing output. It’s telling the difference between: - code that reduces entropy and code that adds it, - systems that scale and systems that bloat, - real productivity and synthetic velocity. **Most people aren’t ready for that distinction.** As an individual contributor, this is where things get uncomfortable. Your value is no longer obvious just because you ship. Everyone ships now. Bots ship. Juniors ship. Scripts ship. **The only thing that really matters is quality.** But it is much harder to see. Quality isn’t aesthetic. It’s not about elegance for its own sake. **It’s about impact over time**. Does this change make the system easier to evolve? Does it remove future work or create it? Does it make other engineers faster or slower? In a world flooded with code, **quality beats quantity every time**. The problem is that most organizations don’t have a way to see it. Quality lives in structure, in decisions, in what *didn’t* break later. It doesn’t show up in raw counts or velocity charts. **That’s exactly the gap we built Pensero to fill.** Pensero doesn’t care how much code you wrote, or whether it was generated by a human or a bot. It looks at impact: complexity handled, systems moved forward, real contribution versus noise. It gives teams a way to distinguish durable progress from bloated output at scale, and without slowing anyone down. Because in this new world, the question isn’t “who shipped the most code?” **It’s: Who actually had the most impact?** And if you can’t answer that, you’re optimizing for the wrong thing. ## Get months of engineering performance data now Stop deciding on gut feel. Get 90 days of objective data in minutes. 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