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9h ago · 7 min read · Most teams building AI agents hit the same inflection point. The first prototype works — a single agent, a single prompt, a single conversation. Then requirements pile up: "Can we add a research step?" "Can it hand off to a specialist?" "Can two agen...
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1d ago · 6 min read · The most interesting agents won't have a chat interface. They'll run in the background — processing data, executing multi-step workflows, calling tools, returning structured output — all without a user typing a single message. The industry is startin...
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2d ago · 7 min read · You've shipped a bug before where you added a console.log, saw the wrong value, fixed the line, and moved on. Thirty seconds, done. Now try that with an agent. The agent called the wrong tool. Why? Because the model interpreted the user's message dif...
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3d ago · 6 min read · Getting an agent to work in a demo takes an afternoon. Getting it to work in production takes months. The gap between those two states is where most teams stall — and it has almost nothing to do with the model. The prototype loop is tight: pick a mod...
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4d ago · 8 min read · Most agent tools are written once for one agent and never used again. They're inline lambdas, glued to a specific session, shaped by whatever the LLM happened to need that day. When a second agent needs similar functionality, someone writes a second ...
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