Apr 13 · 4 min read · In the hype of the LLM era, everyone talks about model size, but seasoned developers talk about context. Think of context as your agent’s "working memory." If you clutter it with every single message
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Apr 13 · 4 min read · You know the drill - you've got a mountain of call transcripts, chat logs, and emails sitting around, full of gold (invoice numbers, contact details, intent signals) buried under layers of "umm, let m
Join discussionApr 1 · 5 min read · One of the more interesting things about building an open-source framework is that the community often knows what to build next before you do. When I started Neuron AI, I had a fairly clear picture in
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Mar 23 · 5 min read · There's a pattern I’ve noticed over the past year while working on Neuron AI: the decisions that matter most are rarely about chasing trends. They’re about quietly recognizing something that works, te
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Mar 17 · 4 min read · Introduction I've been testing Ralph loops recently for agentic coding. The idea is simple: spin up new Claude Code sessions for each task to get a fresh context until the agent achieves the goal, and
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Mar 5 · 6 min read · Introduction Last year, almost every organization rushed to deploy a chatbot. It felt necessary. Customers expected instant replies. Internal teams wanted quick answers. Leadership wanted to say, “Yes
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