AI in production. Reliability in practice.
Latest edition ·The latest analysis
Understand Hermes Agent, its origins, models, memory and skills. Choose a setup, try two checkable examples, and learn where its limits matter.
Read the storyFrom the publication
Understand the model marketplace and gateway, compare chat and API workflows, and choose a useful route through its models, providers, costs and privacy controls.
What a model does when you ask a question, how we got here, and how to choose between local and hosted inference without confusing fast text with useful work.
The global auto mode is only part of the permission decision. Follow per-tool overrides, directory scope and restored settings through a copied-runbook exercise.
Scion reduces repeated repository work for online agents. Its cache hierarchy explains why warm checkout speed and fleet recovery need different tests.
Field guides
Follow a request. Review the code. Find out what actually happened.
Explore the guidesKeep the traces that explain a failure
Tail sampling selects recorded traces by error, latency and other evidence. A checkout timeout shows how routing, waiting time and memory affect the trace a responder can retrieve.
Give AI code review a useful job
CodeRabbit brings AI feedback into pull requests, editors and the CLI. A retry loop that exceeds its caller’s deadline shows the kind of finding that can repay review time.
Recover when a tool call times out
A missing response can leave a worker already created. Durable operation IDs and the destination’s idempotency contract let a replacement executor recover the original request.
Put it into practice
Free reliability tools. No account needed.
Open the workbenchThe AI tools guide
Coding assistants, code review and agent supervision.
Browse the guideCompanies & products
