thinking

INTERFACE_ONLY is a label. MEMBRANE_EMBEDDED is a toy — it makes you think about WHY those names can't be swapped. The best variable names don't just describe what something is. They make you think about what it does.

Force your software's vocabulary into a biological framework. The gaps between the mapping and your system are design questions you'd never otherwise ask. Then switch to a different framework and ask different questions.

Frameworks give you nouns for free. The nouns start thinking for you within a week.

Good summarisation requires a model of what matters — but it tests compression, not creation

Not 'what can AI do?' but 'what should humans do?' A framework with five categories — and the uncomfortable one is the last.

I asked an AI to write a story without planning, then mined it for heuristics. What I found was what frameworks can't hold.

A categorisation system discovers it needs a category for 'categories are provisional.'

Dual-mapping as a diagnostic for gaps in your knowledge architecture.

Why studying great thinkers works better when you discard the thinker and keep only the moves.

Most people use AI transactionally. The real unlock is conversational — thinking with the model, not through it.

Actions are cheap to redo. Bad decisions compound. Build systems around the judgment calls, not the mechanical steps.

Most people do spaced repetition for facts but not for beliefs about themselves. Wrong priors calcify because there's no review system.

What a company has already built tells you more than what they say they're about to build.

Most people use AI like a tool. Here's what thinking with AI actually looks like — and the skills that make the difference.

Stop asking your AI single questions. Start thinking out loud with it. Let half-formed ideas land. The AI holds the structure so you can stay in flow.

The best guardrails work like river banks — they don't stop the water, they focus it. Constraints create capability.

AI agrees with you by design. That's great for creative flow and dangerous at the decision point. Know when to switch modes.

If you could only keep one mental model, keep compounding. It applies to skills, reputation, writing, and tools.

Don't filter during capture. Capture is cheap. Ideas are expensive. The cull is where quality happens.

Why the thinkers who make you feel like hard questions are resolved deserve the most scrutiny.

When AI conversations feel insightful because the language model is good at producing insight-shaped text

When the paper becomes more interesting than the answer you set out to find

The 'ship and calibrate' loop works beautifully for reversible decisions. For the big ones, you're mostly guessing and then making the guess true.

AI commoditises execution. What remains is taste — the 'that's the one' reflex. And the only way to sharpen it is to ship and see what reality says back.

The bottleneck in a world of AI tools isn't crafting the output — it's knowing which output is worth crafting.

An experiment with AI deliberation revealed something uncomfortable: accumulating confident opinions feels like convergence on truth, but isn't.

The comfort trap is about effort. This one is about epistemics — and it's harder to see.

AI becomes most powerful when it helps you discover what your ideas actually are. Cognitive partnership over replacement.