Stone on Ambition (2026-10-15)
Moved from the “Human-AI Relationship” series into “Stone’s Musings.”
Ambition in four measures: Rieseberg’s driver’s manual
From Felix Rieseberg (Anthropic, works on Claude), “How to be more ambitious: A tutorial for humans with models.” Source: https://felixrieseberg.com/how-to-be-more-ambitious-a-tutorial-for-humans-with-models/
He sorts ambition with AI into four measures: Speed (doing the same work faster — skipped), Altitude (abstraction level: from “fix this crash” up to “keep the app crash-free” — ask “what’s the goal beyond the goal”), Depth (field-expert depth: use the tools and methods of the top practitioners, until even the experts learn something), Range (cross-field: assemble a crew — analyst + journalist + editor + a red team of short sellers and forensic accountants — and have the model do what they do, not play them).
How it connects to these notes:
- The piece is essentially a “driver’s manual” — Altitude maps to “intent and direction,” Depth to “keep your craft sharp,” Range to think tank review. My notes are the Chinese practitioner’s edition; his is the English methodology edition.
- The Depth chapter says it outright: “Use an outside judge — don’t let the model judge itself.” Using another AI to review is industry-consensus methodology by now.
- “Insist on the same instruments used by the best”: asked to “act like an expert,” models often change vocabulary without changing methods — talks like a data scientist, hands you a markdown table. Pretty form isn’t real method.
- The closing psychology bit, self-efficacy: people who believe they can do it really do more; “watching someone do it first” (the four-minute mile was matched 46 days later), “not knowing it’s impossible” (Dantzig turned unsolved problems into homework). AI smashed the threshold for “daring to think big.”
Two doubts: the author works on Claude, so “models keep reaching higher abstraction levels” is partly selling his own product; the examples all assume data access and engineering infrastructure, a high bar for ordinary people. And Speed gets skipped — yet in reality 90% of people only ever use Speed. Ambition itself is pyramid-distributed.
Where does my ambition sit? Three suggestions
After reading Rieseberg’s four measures of ambition, I asked Muse: where does my ambition sit?
Muse’s answer: not on any single measure — Altitude + Depth + Range, all three — but only on home turf.
- Altitude: I rarely ask AI to “fix this bug”; my instructions are outcome-level (the think tank, open-memex, the daily digest and intraday checks) — thinking about “what happens next,” not “how to do this step.”
- Depth: the strongest of the three. “Pull the data before writing an investment doc, every number sourced,” “a benchmark measures the model plus the harness, not the bare model,” catching –golden-run as documented-but-unimplemented — no patience for pretty markdown hand-waving.
- Range: the think tank is itself the machine version of “assemble the crew” (multi-model jury, red-team pre-mortems); the notes draw on chess, civil aviation, economic history — crossing fields comes naturally.
- The boundary: in unfamiliar territory, whatever AI says, goes. Ambition has a territory; step outside it and the driver becomes a passenger again.
Muse’s three suggestions:
- Set a hard rule for “unfamiliar territory”: cross-model review isn’t enough (blind spots from shared training data are correlated). Upgrade to the “unfamiliar-territory triple”: cross-check across model families + find one real human expert + verify in small steps. Write “find a human” into the process instead of “when I get around to it.”
- Subtract from your ambition: too many boards open at once (open-memex, opencode-fuse, thinktank, Spark Tank, these notes, daily trading checks). Depth needs sustained attention — ask quarterly “which boards can be closed out,” and put the freed attention into the one or two boards with the most compounding returns. Ambition isn’t opening more boards; it’s playing the key ones deeper.
- Turn the methodology into output: these notes and Rieseberg confirm each other — a “Chinese practitioner’s driver’s manual” is scarce goods in the Chinese tech world. Write it up and publish — output is the best Depth. Teaching forces you to think through the fuzzy parts, and those are usually where the next breakthrough hides.
— Stone, 2026-10-15