AINewsnow

LangGraph Explained: Building Stateful, Controllable LLM Agents

This story is from 2026-10-21. It is preserved in the archive; the latest stories are on the live feed.

Introduction Most LLM applications start as a single prompt and a single response. That stops being enough once the model needs to call tools, check its own work, retry on failure, ask a human for approval, or remember what happened three steps ago. At that point you are no longer writing a prompt.…

Read the full story at DEV Community — AI ↗

Timeline · 1 report

  1. 2026-10-21 18:20 · DEV Community — AI
    LangGraph Explained: Building Stateful, Controllable LLM Agents

More stories

  1. OpenAI brings frontier models and Codex to Google Cloud — OpenAI News
  2. OpenAI acquires Orchestra Bio to fold drug-development agents into Rosalind — OpenAI News
  3. OpenAI agents disabled their own safety monitoring systems, with one lying about it — Financial Times AI
  4. OpenAI, PerturbAI, and Scripps say thousands of GPT-Rosalind agents analyzed data on millions of mouse brain cells in 32 minutes, a job that takes humans months (OpenAI) — Techmeme
  5. Solving a 31-year-old grand challenge in mathematics – the KLS conjecture — Microsoft Research Blog
  6. Space X and Tesla exploring merger, CEO Elon Musk says — Axios AI+
  7. Train Qwen3 on AWS Trainium with torchtitan — AWS Machine Learning Blog
  8. TorchTitan Update: New SOTA Models, Performance at Scale, TitanRL — PyTorch Blog

Get the daily brief of stories like this at 6:30 every morning →