GuidesBuilding a Changelog Generator People Actually Read
Restating commit subjects is not a changelog. How to pick the right input, separate classification from writing, handle reverts, and keep regeneration deterministic.
ReadNotes on models, agents, and what inference costs
Practical writing for developers building with large language models — how they work, how to pick one, and how to keep the bill predictable.
Hands-on setup for the tools developers actually use.
Guides
GuidesBuilding a Code Search Tool That Beats grep
Semantic code search only pays off if you beat ripgrep on the queries it fails. Chunking at symbol boundaries, hybrid retrieval, incremental indexing and honest evaluation.
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GuidesBuilding a Docs Chatbot That Refuses to Guess
A docs bot fails on the gap between what is documented and what users ask. Version-aware chunking, hybrid retrieval, forced citations, and abstention that actually fires.
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GuidesBuilding a Postman Collection for OpenAI-Compatible APIs
A reusable Postman or Insomnia collection for any OpenAI-compatible endpoint — environments, streaming, tool calls, saved examples, and sharing it without leaking keys.
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GuidesBuilding a PR Summariser Reviewers Do Not Skip
Most PR summary bots restate the diff and get ignored within a fortnight. What reviewers actually need, how to select the diff, and how to keep cost per PR predictable.
ReadGuidesBuilding a Prompt Library People Actually Reuse
Most prompt libraries become a graveyard of untested snippets. What makes one worth maintaining: ownership, discoverability, contracts and a deletion policy.
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GuidesBuilding an Incident Assistant On-Call Engineers Trust
Automate the first ten minutes of context gathering, not the diagnosis. Read-only tools, evidence-linked output, a latency budget, and why a wrong answer at 3am is expensive.
ReadGuidesBuilding an LLM Code Review Bot People Do Not Mute
Wiring a model into pull request review: what to send it, how to post comments that land, and the signal-to-noise threshold that decides whether the bot survives.
ReadGuidesCalling an LLM API from Jenkins Without Leaking the Key
A declarative pipeline stage that calls an OpenAI-compatible endpoint, handles credentials properly, fails loudly on errors and does not bankrupt a shared build server.
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GuidesCircuit Breakers for LLM APIs: Failing Fast on Purpose
How to build a breaker around an inference provider: what to count as a failure, where to set thresholds, how half-open probes work, and when to fall back instead of failing.
ReadGuidesConnection Pooling for LLM APIs: Sizing the Client Right
Long-lived streaming requests break the assumptions behind default HTTP pools. How to size keepalive connections, avoid pool starvation, and stop creating a client per call.
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Guidescurl Recipes for LLM APIs: Debug Before You Write Code
A working set of curl commands for OpenAI-compatible endpoints: streaming, timing, tool calls, error bodies, and building JSON safely with jq.
ReadShowing 1–12 of 77 articles