
Tomas Gear
@tg_bytes
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Agent Engineering Leader. Agents on the frontier of Voice AI. Views always my own.
New York City
Joined September 2019
Keynote Summaries (6/3 and 6/4): . Useful General Intelligence (Danielle Perszyk, Cognitive Scientist, PhD, Amazon) . Designing AI-Intensive Applications (@swyx) . Spark to System: Building the Open Agentic Web (Asha Sharma, Microsoft) . State of Startups and AI 2025
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Keynote Summaries (6/5, continued): . fun stories from building OpenRouter and where all this is going (@xanderatallah). The New Code (@sgrove)
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Keynote Summaries (6/5, continued): . The infrastructure for the singularity (@jessemhan). State of AI Engineering 2025 (@barrnanas). Trends Across the AI Frontier (@_micah_h and @grmcameron). Evals Closing Keynote (@ankrgyl)
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Keynote Summaries (6/5): . A year of Gemini progress + what comes next (@OfficialLoganK). Thinking Deeper in Gemini (@jack_w_rae). Why should anyone care about Evals? (Manu Goyal, Braintrust). Containing Agent Chaos (@solomonstre)
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Keynote Summaries (6/4, continued): . 2025 in LLMs so far (@simonw). Windsurf everywhere, doing everything, all at once (@kevinhou22). Define AI Engineer (@gdb, interviewed by @swyx)
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"The prompt is a bug, not a feature." (@saranormous). We're building UIs that force users to become prompt engineers. The best AI products feel like mind-reading. They collect context automatically. They present solutions thoughtfully.
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Plot twist: Most practitioners are new to LLMs. (h/t @barrnanas). The "AI engineer" role is still being invented in real-time by people figuring it out. There are no experts. Only early adopters.
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Developers want configurability, not vendor lock-in. (h/t @xanderatallah). They've seen this movie before. Cloud providers became overlords. API companies became gatekeepers. This time they're choosing flexibility.
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Forget large teams and specialized roles. The new winning formula: Small, full-stack generalist squads. 5 people who can ship end-to-end vs 50 people who need handoffs. Coordination cost is the killer. "Fewer people means more context per head." (@EricSimons @boltdotnew).
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