7 sessions on transformers.js with a coding agent: the agent failed at least once in 6, and 0 finished without a human stepping in.
Takeaway: Next time I'd specify upfront that the model runs client-side so we should keep full semantic context (all synsets, full glosses) even under credit/perf constraints — the agent's instinct to shrink things for a WebGPU error nearly cost us disambiguation quality.
Takeaway: Next time I'd mention upfront that streaming/shuffling a chronologically-shaped HF dataset is unreliable for randomness, and just point straight at the local summary.json/transcripts.csv files I already had instead of letting the agent try three different remote sampling strategies first.
Takeaway: Next time I'd ask upfront how the HF dataset is sharded/ordered so we don't burn a whole session discovering that streaming shuffle only randomizes within a season-grouped window.
Takeaway: Next time I'd have it check for a working Python runtime and gradio version up front, since that cost several minutes of failed docs searches and PATH issues before it could even inspect the API.
Takeaway: Next time I'd tell it upfront not to bother with in-app browser or Playwright automation on this machine — just get the server running and let me check it myself in a real browser.
Takeaway: I'd specify upfront that mobile-responsiveness testing should rely on manual review or a known-working tool rather than have the agent hunt for a broken local Playwright install, since that ate time for no result.
Takeaway: Next time I'd mention upfront that local browser automation tooling (Playwright etc.) is flaky in this sandboxed Windows environment, so we don't burn a long stretch discovering that mid-session.