Practical guides on using AI tools like ChatGPT, GitHub Copilot in your workflow
96 articles
ChatGPT can scaffold Prometheus alerting rules fast, but generic outputs routinely misfire in production. Learn how to prompt precisely and validate outputs before they page your on-call team at 3 a.m.
ChatGPT can scaffold transaction code in seconds, but it routinely gets isolation levels wrong — leaving you exposed to phantom reads you won't catch until production. Here's how to prompt it correctly.
ChatGPT can generate event-driven architecture configs that look correct but silently wire consumers to the wrong topics, duplicate subscriptions, or miss dead-letter routing. Here's how to prompt your way past those phantom consumer bugs.
Ensemble learning is designed to improve predictive performance by combining multiple machine learning models. Yet many teams discover that their production ensemble performs worse than even its weakest individual model. Learn why this happens, how production environments differ from offline
ChatGPT can produce regex patterns that look convincing but silently miss edge cases, match too broadly, or break on Unicode. Here's how to prompt your way to patterns you can actually trust in production.
Ensemble models are expected to outperform individual models by combining their strengths, yet many production deployments perform worse than even their weakest component model. Learn why this happens, how production conditions differ from offline evaluation, and how to build ensembles that remain
ChatGPT can draft distributed lock code fast, but split-brain bugs hide in the details — expiry races, unsafe release patterns, and missing fencing tokens. Learn the prompts that surface the real failure modes before they hit production.
ChatGPT can write retry code fast, but its default backoff strategies often miss jitter, cap limits, and context-aware delays — turning a resilience feature into a thundering herd. Here's how to prompt it correctly.
ChatGPT can generate mutex and locking code that looks correct at a glance but silently deadlocks under load. Learn the prompting techniques that force it to produce safe, production-ready concurrency code.
ChatGPT can draft SQL migrations fast, but the default output often contains ALTER TABLE statements that lock your production tables for minutes. Here's how to prompt it correctly and avoid downtime.
ChatGPT can scaffold DI containers fast, but it often gets the wiring wrong — circular deps, missing scopes, or services registered in the wrong lifetime. Here's how to prompt your way to configs that actually work.
ChatGPT can draft Elasticsearch queries fast, but without your actual index mapping it guesses field types and analyzers — and those guesses break at runtime. Here's how to get accurate queries every time.