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ci-cd
39 postsProbelock: A Lockfile for LLM Tool-Calling Capabilities
Probelock measures an LLM's tool-calling capabilities with deterministic tests and halts CI when a model, quantization, or runtime swap causes a regression.
Kakehashi: run macOS ARM64 binaries on Linux aarch64, no JIT
Kakehashi is an experimental userspace layer that runs macOS ARM64 binaries natively on Linux aarch64 without JIT, aimed at cutting CI costs.
Building an Arch Linux Aarch64 Port for Holo Core
Collabora and Valve detail Holo Core, an unofficial aarch64 port of Arch Linux for Steam Frame, and the CI tooling needed to replay its build history.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.com17 PRs a Day, One QA: Automating E2E Failure Triage
How pdf.net automated e2e failure triage with a Claude-powered GitHub Action, letting one QA engineer keep pace with 17+ daily merges.
The physics of Docker build caching: three caches, one wave
A measured breakdown of Docker's three build caches — layer chain, mount cache, image store — and when each caching strategy actually helps.
eBPF and TCX bring line-rate network visibility to hostile CI jobs
Blacksmith explains how eBPF programs attached via TCX and a host-side DNS proxy deliver line-rate network observability for untrusted CI VMs.
30 Days as the Only Human in an AI Dev Team: 212 PRs, Broken CI
A 30-day AI-agent coding experiment shows how self-reported 'green' CI and unreviewed PRs let critical failures hide in plain sight.
Loop Engineering: Fixing a Guardrail That Fired Wrong
How to fix a misfiring guardrail check in an agent loop without deleting it—why weakening checks silently disables real catches.
PromptLedger v0.7 adds CI regression gates for prompt evaluation
PromptLedger v0.7 adds evaluation runs, metric comparisons, and policy-based regression gates for CI-safe prompt releases.
Why Using AI to Catch Design-Code Drift Is the Wrong Fix
AI-generated UI code is drifting from design systems, and using another AI model to catch it brings non-deterministic, costly and unexplainable results—here's a deterministic alternative.