Ai

Copilot now takes part in more than one in five code reviews on GitHub. The research says AI reviewers earn their keep - and that the tuning which makes them usable suppressed about a fifth of real vulnerabilities on a standard benchmark.

A change swapped a made-up number for a confident, wrong explanation of how Propshaft works. Spotting the difference is the thing you are actually hiring for.

A fake think tank published 100+ reports built to be repeated by chatbots, behind a $900,000 government contract. The same economics reached your blog. Four checks you can run.

RubyLLM retries POSTs that Faraday would not, and honors Retry-After with no upper bound. A 429 can park a Rails request for as long as the provider says.

RubyLLM is a model client with Rails generators. Langchainrb is retrieval plumbing. Pick by whether you query your own documents, not by provider count.

Add LLM chat to Rails with RubyLLM: one API for OpenAI, Claude, and Ollama, acts_as_chat persistence, tool calling, streaming into Turbo, and real trade-offs.

Our production multi-agent LLM pipeline in Rails: eight RubyLLM agents on a 21-line base class, a 16-line loop, and the deploy that starved the database pool.

How a Rails team knows whether its LLM agents still work: bounded schemas at the boundary, and a per-iteration audit trail you can read a month later.

What a green Rails suite actually asserts when the thing under test is a hosted model: VCR matches on method and URI only, and the model can be retired.

Vibe-coded code is unmaintainable by design - patches don't stick, bugs return, the rebuild verdict lands. The generate-validate-kill workflow that prevents it.