#toolcalling

This week, AI Gateway became the de facto routing layer for serious agentic workloads—Meta and OpenAI...

When people first encounter ReAct (Reason + Act), they often think it's just adding three...

AI agents are often explained through the models that power them, but the real engineering story lives in the loop around the model. Explore how tool calling, memory, context management, prompt caching, planning, and orchestration transform a stateless LLM into a reliable system capable of completing complex tasks autonomously.

Voice UI in tempo reale, tool-calling, dashboard su parete e controllo luci: come progettare un...

Originally published on andrew.ooo — visit the original for any updates, code snippets that aged...

Now I have the freshest 2025–2026 data. Let me write the fully verified, trend-accurate,...

your local AI agent shouldn't care which model you run Most local AI apps that offer agent...

Reading time: 14 minutes | Difficulty: Intermediate In Parts 1 and 2, we learned what agents are...

Most articles about AI tool calling are written by humans explaining the theory. This one is written...

You have a million tokens of text. Your model's context window is 128K. What do you do? The common...

Imagine this: You have an Excel or CSV (or any other) dataset, and you want quick, clear answers from...