🤖 AI Summary
Martin Fowler — veteran software engineer, Thoughtworks chief scientist and Agile Manifesto co-author — warned on The Pragmatic Engineer podcast that software engineering is in a "depression" driven by a broad pullback in business investment, even as an exuberant AI boom runs alongside it. He pointed to industry-wide layoffs (Layoffs.ai tracked roughly 114,000 tech job cuts so far in 2025 versus about 153,000 in all of 2024) as evidence that companies aren’t funding conventional software work, while AI spending feels “bubbly” and unpredictable. That split matters because it creates instability for teams, hiring, and long-term product investment.
For junior engineers Fowler’s core advice is practical: don’t ditch AI tools, but don’t rely on them uncritically — newer developers often lack the experience to judge LLM outputs — and actively seek senior mentorship. A seasoned engineer can validate model outputs, teach architecture and trade-offs, and help juniors build durable fundamentals that survive market swings. Technically, the implication is clear: emphasize code review, testing, system design and critical thinking over blind trust in autocomplete, and invest in human-centered practices (mentorship, peer review, tooling) to mitigate the risks of an AI-driven yet volatile hiring landscape. He remains optimistic that core software skills will continue to matter even if the AI bubble reconfigures roles.
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