60 articles tagged #Prompt Engineering
ChatGPT can suggest useful database indexes, but it routinely misses compound index opportunities and column ordering rules. Here's how to prompt it correctly and catch the gaps before they hit production.
ChatGPT can generate memory leak detection scripts fast, but vague prompts produce noise-heavy tools that cry wolf on every GC pause. Here's how to prompt for precision and get scripts that catch real leaks.
ChatGPT's default CORS configs reach for wildcards the moment the prompt gets vague — and wildcards in production are a real security problem. Here's how to prompt precisely and get configs you can actually ship.
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.
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.
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 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.
ChatGPT can generate structured logging configs fast, but without the right prompts, you end up with fields that shift between services, missing required keys, and parsers that break in production. Here's how to fix that.