ExplainerAI in production
How AI got from rules to reasoning models
Follow the changes in learning methods, data and compute that led to today’s models, and see why newer does not always mean better for a task.
AI in production. Reliability in practice.
Latest edition ·The latest analysis
OpenCode 2.0: from a failing test to a fix you can check
What changed in OpenCode 2.x, how to install it, and a small retry bug you can reproduce, repair and check yourself.
Read the storyFrom the publication
The latest
ExplainerPlatform engineering
Linux history: how the kernel became a complete system
Unix, GNU, the Linux kernel and distributions explain the cooperating layers you operate today, including what a container actually shares.
GuideAI in production
Tokens and context windows: what your model actually receives
Inspect the assembled request, count text tokens, reserve output space and shorten context without losing the condition that changes the answer.
GuideAI in production
Embeddings and vector search: finding the right passage
Encode a small document collection, inspect similarity results and distinguish a relevant passage from one that applies to your system.
Field guides
Get closer
to the evidence.
Follow a request. Review the code. Find out what actually happened.
Explore the guidesKeep the traces that explain a failure
GuideObservability
OpenTelemetry tail sampling through a checkout 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
GuideAI in production
CodeRabbit: how to use AI code review
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
GuideAI in production
Recovering an automation write after a timeout
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
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More working plan.
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Find the right AI tool for the job.
Coding assistants, code review and agent supervision.
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