Engineering
Automated Incident Response with AI: A Governance-First Guide
Stop letting LLMs have root access. Learn to build a policy-driven framework for automated incident response with AI using hard guardrails and deterministic checks.
GitHub Copilot Alternatives That Actually Work for Staff Engineers
Tired of Copilot hallucinations? I tested five alternatives that actually handle complex context and reduce your rollback rate.
Running Local LLMs for Coding: Why Your M3 Max Isn't Enough
A post-mortem on our attempt to move AI coding workflows off-cloud. Performance benchmarks, memory pressure, and why we went back to a hybrid setup.
How to use AI for code refactoring: A staff engineer's guide
Stop treating AI as a magic wand for legacy code. Learn how to build verification pipelines that treat LLMs as proposal engines, not authority figures.
Testing AI Generated Code: A Post-Mortem on Blind Trust
AI code generation is fast, but your test suite is the only thing preventing a production incident. Here is how we fixed our broken validation workflow.
AI for Log Analysis at Scale: A Staff Engineer's Guide
Log volume is killing your observability. Learn how to use AI clustering, semantic search, and automated post-mortems to actually find the root cause.
Prompt engineering for real work: A technical guide for engineers
Forget the flowery language. This is how you build reliable, production-ready prompts that do not break your CI/CD pipeline or inflate your cloud bill.
Best AI code review tools: A post-mortem of our failed automation
We tried to automate our PR reviews using the latest AI tools. Here is what actually worked, what caused an incident, and why most tools are just noise.
When AI is the wrong tool: A guide to shipping deterministic code
Stop using LLMs for tasks that a regex or a simple database query can handle. Learn how to audit your stack and ship reliable, deterministic code.