Fragments: June 2

According to tech commentator Martin Fowler, the software industry faces an uncomfortable tension: measuring whether AI tools actually boost developer productivity is nearly impossible. Lines of code generated, tickets closed, even developer surveys—all reveal different flaws. And yet, weak signals may be the best we have. Meanwhile, open-source AI models are catching up to commercial models faster than expected, suggesting the gap may narrow further. But the deeper concern is how LLMs amplify existing patterns in codebases. Bad code doesn't look like debt to a model—it looks like precedent. Across the internet, AI-generated hallucinations are poisoning knowledge: fake citations, plausible-sounding lies embedded in reports from major consulting firms. On the brighter side, AI is finding real security bugs at unprecedented scale—Mozilla fixed four hundred twenty-three Firefox vulnerabilities in a single month. The paradox: AI might transform developer work more than eliminate it, but the shape of that transformation remains impossible to predict.

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