ReAct tool-calling issue: Orchestration model computes internally instead of usi

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s1ckkm/why_llms_sound_right_but_fail_to_actually_do/"> <img alt="Why LLMs sound right but fail to actually

<!-- SC_OFF --><div class="md"><p>I've been messing around with local models to see when they fail silently or confidently make stuff up. One test I came up with is a bit wicked

<!-- SC_OFF --><div class="md"><p>Beginner here, now I have a good GPU and ollama using docker. Pulled the Gemma4 weights and was able to add it to cursor using ngrok. </p>

<p>Claude's tool use (function calling) API is what separates toy chatbots from actual agents. I've built production agents with it — here's what reliable tool use looks like when

<!-- SC_OFF --><div class="md"><p>everyone's focused on the benchmarks (14 state of the art evals, beats mythos on terminal-bench, etc) but i think the actual story of 5.5 is what

<!-- SC_OFF --><div class="md"><p>Read a piece this week where the author admitted she built what she was confidently calling an agent — RAG-based, tool-aware, natural language

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s0d7ps/tool_call_write_code_in_think_failed/"> <img alt="&lt;tool_call&gt; write code in &lt;think&gt;

<!-- SC_OFF --><div class="md"><p>I’m working on an LLM agent setup (using Qwen-style chat templates with tool calling), and I ran into a design trade-off that I’d like to get