LangGraph's Routing Is LLM-Guessing. I Wrote 50 Lines of Code to Make It Determi

<p><em>Disclosure: I maintain <a href="https://github.com/Fast-Editor/Lynkr" rel="noopener noreferrer">Lynkr</a>, an open-source router whose design decisions this post explains.

<h1> I Stopped Paying GPT-4 for Simple Queries </h1> <p>You know that feeling when you send "What's 2+2?" to GPT-4 and watch $0.03 vanish?</p> <p>I was burning through my OpenAI

<ul> <li>GitHub repository: <a href="https://github.com/gezilinll/agent-grove" rel="noopener noreferrer">https://github.com/gezilinll/agent-grove</a> </li> <li>Online

<p><em>And why your router is about to become your bottleneck</em></p> <p>You're a developer. You've built something that works—a system with multiple agents, each specialized,

<p>Your agent passed all the tests. It's been running in production for three weeks. And it has been quietly wrong the entire time.</p> <p>This is not a hypothetical. Galileo's

<p><em>Originally published on <a href="https://aideazz.hashnode.dev/multi-model-llm-routing-why-76-of-your-inference-shouldnt-touch-gpt-4" rel="noopener noreferrer">AIdeazz</a> —

<p>"The Reasoning Trap." The line the authors won't quite say out loud is that the smarter your model gets at reasoning, the more likely it is to fabricate a tool that doesn't