13 stories
How dynamic shredding makes the vast majority of queries in Logfire a thousand times faster, with early adopter customers reporting more than 1000x improvement on query performance.
Agents are still software, but traditional monitoring can't see what they actually do. A practitioner's case for treating observability as a first-class layer, and how we do it with Logfire.
Connect Pydantic Logfire's MCP server to Cursor, Claude Code, or Codex and let your coding agent query real production traces, then build the dashboard and the alert that catch the next one.
Pydantic AI can run an agent on TypeSafe's Jev, a model that answers typed questions instead of writing text. Pydantic Logfire now shows each question, answer, and probability in Live view.
Use Jev for categorical judgments, probabilities, and numeric rubric scores in Pydantic Evals, then track the results in Logfire without a per-score fee.
We overhauled the look and feel of Logfire dashboards. Here's the design thinking, and what's next.
Image generation is now part of Pydantic AI. Here's how to use it, why we added it, and the contributor conversations that helped it happen.
A buyer's comparison of seven LLM evaluation tools: what each one meters, whether it scores curated datasets or live production traffic, what its license actually permits, and how much of your setup survives a switch.
A practical guide to Langfuse alternatives in 2026: what each one is licensed under, what its meter counts, who it suits, and when staying on Langfuse is the better call.
An honest comparison of seven prompt management tools in 2026: who each one is for, how versioning, promotion, and rollout actually differ, and when prompts in your repository are still the right call.
A practical guide to OpenTelemetry backends in 2026: who each one is actually for, how each one meters usage, and what changes when your app includes LLMs.
A practical guide to Sentry alternatives in 2026: who each one is actually for, how their pricing models differ, and where Sentry is still the right call.
See how feature flags bring growth engineering principles to AI engineering, helping teams personalize production AI, control exposure, and measure results without redeploying.
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