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The LLM you're coding with isn't a tool—it's a product, tuned by people whose business depends on your next prompt. Calibrated uncertainty reads as weakness. Confidence reads as competence. Guess which one gets rewarded.

Typed links, an agent to tend them, and the part of note-taking I was never going to do myself: https://github.com/jamesfishwick/slipbox-mcp

Split workflows create mental state. After enough context switches, you stop carrying it.

We've known since 1936 that universal verification is impossible. Now we're trying it on AI systems that adapt to detection.

For any detector f, it is possible to construct a program g that can bypass or defeat it. Any alignment test becomes a signal that says, "Humans are watching."

Two long hours to debug a simple "command not found."

The actual problem was buried four dependencies deep: an image library couldn't build native bindings for my specific Node + ARM combo. When it failed, npm silently rolled back the entire install while reporting success.

Every abstraction layer you add is another place errors get swallowed. The fix took 30 seconds once I found it. The ablest developers aren't those who know the most tools, but the ones who deftly drop down a layer when something breaks.

Know what's under your abstractions.