Practical guides on using AI tools like ChatGPT, GitHub Copilot in your workflow
101 articles
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 scaffold Celery configs fast, but it often misses retry logic, acks_late settings, and visibility timeout traps that let tasks disappear without a trace. Here's how to prompt your way to configs that actually hold up in production.
Scikit-learn pipelines are excellent for preventing data leakage and simplifying preprocessing, but they can sometimes transform your target variable (y) in unexpected ways. Learn why this happens, how it affects model performance, and how to prevent subtle training and evaluation bugs.
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 can scaffold rate limiting middleware in minutes, but the default output skips distributed counters, race conditions, and bypass vectors that will bite you in production. Here's how to prompt your way to middleware that actually holds up.
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 WebSocket handlers fast, but the default output skips reconnection logic, drops messages during disconnects, and ignores backpressure entirely. Here's how to prompt your way to production-ready code.