AINewsnow

Building a local-first decision engine that only calls the big model when it's worth it

Every AI agent I've built eventually hits the same wall: calling a big model on every request is too expensive, but a small local model is too dumb on the hard cases. Most teams pick one side and live with the consequences. I wanted a third option: run a small local model first, and escalate to a b…

Read the full story at DEV Community — Machine Learning ↗

Timeline · 1 report

  1. 2026-11-11 11:54 · DEV Community — Machine Learning
    Building a local-first decision engine that only calls the big model when it's worth it

More stories

  1. Anthropic IPO valuation could reach $1.4-1.5 trillion as demand surges — CNBC Technology
  2. OpenAI launches Businesses in ChatGPT beta with verified profiles and Business Agents — OpenAI News
  3. Nvidia spy scandal exposes Singapore networks in China's AI chip trade — New York Times AI
  4. OpenAI's quarterly revenue hits $10 billion, up about 50%, but losses persist — The Information AI
  5. AI data center buildout seen continuing through 2028 as fiber shortage strains other sectors — DigiTimes Asia
  6. Developers share workflows for running Claude Code and Codex together — r/ClaudeAI
  7. AI training startup Mercor raises $750M Series D at $20B valuation — Economic Times Tech
  8. Microsoft researchers show AI agents can be backdoored by editing fewer than 10 dormant neurons — Microsoft Research Blog

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