Small AI Teams with Huge Impact
summary
Datalab scales revenue 5x to seven‑figure ARR while keeping headcount at four and 40K GitHub stars for repos surya and marker. A 500M‑parameter OCR model ships with 90‑language support, character‑level bounding boxes and PDF line‑level grounding, hitting ~99% on internal benchmarks. Codebase favors server‑rendered HTML with HTMX/Alpine, modular repos for AI edits, and hiring uses a paid 10‑hour $1,000 trial to vet senior generalists who own end‑to‑end work.
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chapters (20)
- 0:00Introduction
- 0:41Datalab
- 0:58Todays focus
- 1:27Data Quest
- 2:07The 4 hypotheses
- 3:07The golden period
- 3:59Answer AI
- 4:37Culture
- 5:15Example
- 6:17Context
- 6:59Why AI
- 7:12More people doesnt equal more productivity
- 8:28How do you architect this
- 9:02Keep everything simple
- 9:24Fill in the edges with models
- 10:03When does the model fail
- 10:46Role overlap
- 11:16Politics
- 12:37Scale productivity
- 13:07Change the culture
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