ai fitness coach + first principle

Z / Runner 🏃🏻‍♂️

🏃🏻‍♂️ AI Fitness coach (v1). 4 main hypothesis (also 4 main tradeoffs).

• 🏃🏻‍♂️ 1st principle (MECE)

• dependable, sustained guidance from highly reliable trainers (off the chart for both us, we know mark, tracy, jeramey...)

• data we have, more than enough (16 channels & growing).

• ai-techniques & open source LLMs, sufficient to deliver consumer grade ai coach (no need to build/train from scratch, off-the-shelf is good enough).

• evals (a, b, c... = MECE).

• parasocial relationship: simulate someone you "look up to" (parasocial, n=1 anchoring vs. expert n -> ∞)

• coverage exhaustive, holistic 16x12 = 192 telemetry coverage

• fact checking authenticity (build on 80m peer-reviewed papers, RCTs, & top n professionals).

• human as ai, last 24 month exp; ai models are getting better, but plenty of holes/gaps

• 🏃🏻‍♂️ on voice or chat: 1). voice = the new keyboard for ai. 2). voice = a window into somatic intelligence (slurring, heavy breathing, anxiety, drained → real cardiovascular and cognitive states fitness apps & sensors fail to capture).

Stephen / Basketball 🏀

• 🏀 stating ranking on the levels of convictions / tradeoffs you keep mentioning?

• 🏀 what's the dependency / hierarchy?

• 🏀 yes, agreed; have other models / agents to verify before users.

• 🏀 evidence (a, b, c)?

• 🏀 1 (out of 10)? ok ok, parasocial is the very common today: any influencers + many friends as their hard-core followers.

• 🏀 10/10? exhaustive (16x12 metric) is impossible / impractical; even basic statistical analysis needs intentional selection of data – per "noise" below.

• 🏀 6/10? cite per source, but agentic – via gemini 3, claude, gpt5 with deep research, web search, tool use.

• 🏀 9/10? our journaling – which i am ok / curious to keep going (despite my recent doubts and rants).