57 articles tagged #Prompt Engineering
ChatGPT can sketch pagination logic in seconds, but it consistently stumbles on off-by-one errors, incorrect total-page calculations, and edge cases like empty result sets. Here's how to prompt your way to correct, production-ready pagination every time.
Large Language Models don't distribute attention evenly across a prompt. Researchers have discovered that certain early tokens can act as "attention sinks," attracting disproportionate attention and influencing outputs in unexpected ways. Learn how attention sink tokens work, why they affect model
ChatGPT can draft retry logic fast, but the default output often misses jitter, ignores maximum attempt caps, or quietly creates infinite loops. Here's how to prompt it correctly and validate what it gives you.
ChatGPT can draft gRPC proto files fast, but it routinely gets field types, service method signatures, and streaming patterns wrong. Here's how to prompt it correctly and catch the mistakes before they hit your build.
ChatGPT can scaffold OAuth 2.0 flows fast, but it often skips PKCE, exposes tokens in URLs, or mishandles refresh logic. Here's how to prompt it correctly and catch every security gap before it ships.
ChatGPT can scaffold logging middleware in seconds, but the default output often silences exceptions instead of surfacing them. Here's how to prompt your way to middleware that actually preserves error context.
ChatGPT can draft migration rollback scripts fast, but it often misses destructive-change traps, data-loss edge cases, and framework-specific conventions. Here's how to prompt it so the output is actually safe to run.
ChatGPT frequently generates Kubernetes manifests with deprecated apiVersions that will fail on modern clusters. Learn the exact prompting patterns that force it to produce valid, current manifests every time.
ChatGPT can generate Nginx configs fast, but a single misplaced location block or wrong proxy_pass value silently breaks routing. Here's how to prompt it precisely and validate what comes back.
ChatGPT can scaffold a JWT auth flow in minutes, but the default output often skips token expiry checks, uses weak algorithms, or stores tokens unsafely. Here's how to prompt your way to production-ready authentication code.
ChatGPT confidently writes GraphQL queries with fields that don't exist in your schema. Here's how to give it exactly what it needs to produce accurate, runnable queries every time.
ChatGPT can draft Makefiles fast, but it consistently gets dependency chains wrong, mixes phony targets with real files, and ignores your actual build graph. Here's how to prompt it so the output actually works.