I ran two AI builders in parallel at a solo hackathon — here's what the 429 errors revealed
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At a 3-hour Google for Developers hackathon, I ran two AI builders simultaneously on the same brief: Hermes + Nvidia Nemotron 3 Ultra 550B — one raw prompt, fully autonomous Claude → Gemini Antigravity — iterative spec-first workflow The most revealing moment wasn't about speed or features. It was how each one handled 429 rate-limit errors during code generation. // The 3-layer strategy I ended up having to write explicitly for Antigravity: const RETRY_DELAYS = [ 2000 , 5000 , 10000 ]; async…
1Key Takeaways
- At a 3-hour Google for Developers hackathon, I ran two AI builders simultaneously on the same brief: Hermes + Nvidia Nemotron 3 Ultra 550B — one raw prompt, fully autonomous Claude → Gemini Antigravity — iterative spec-first workflow The most revealing moment wasn't about speed or features.
- It was how each one handled 429 rate-limit errors during code generation.
- // The 3-layer strategy I ended up having to write explicitly for Antigravity: const RETRY_DELAYS = [ 2000 , 5000 , 10000 ]; async….
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3Why it matters
Prompt and agent patterns spread fast; staying current saves time and token cost. DEV — Prompt Engineering reports that at a 3-hour Google for Developers hackathon, I ran two AI builders simultaneously on the same brief: Hermes + Nvidia Nemotron 3 Ultra 550B — one raw prompt, fully autonomous Claude → Gemini Antigravity — iterative spec-first workflow The most revealing moment wasn't about speed or features.
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