Tricks That Actually Save Time: Coding, AI, and Developer Productivity
Most developers waste hours on tiny habits that simple tricks can fix. Want to write cleaner code, ship faster, and stop chasing the same bugs? This page collects practical tricks from coding, Python tips, debugging moves, and AI shortcuts you can use today.
Fast coding tricks that stick
Use small, repeatable habits. First: learn and use your editor's shortcuts—search, multi-cursor, and jump-to-definition cut context switches. Keep a snippet library for common patterns (auth checks, API calls, tests). In Python, prefer f-strings for readability, enumerate instead of manual counters, and tuple-unpack in loops to avoid index mistakes. Add unit tests for small functions as you write them—five-minute tests catch the majority of regressions.
Automate the boring stuff. Add linters and formatters (like Black, ESLint) to pre-commit hooks so style never eats your time. Use code generation wisely: templates and AI assistants can scaffold repetitive code, but always review generated code for edge cases and security holes.
Debugging and performance tricks
When a bug blocks you, narrow scope fast. Reproduce with a minimal input, then use git bisect to find when the issue appeared. Use logging with structured fields (user_id, request_id) so you can filter without guessing. For tough performance problems, attach a profiler and focus on the top 10% of slow paths—80/20 applies to CPU time too.
Learn to read stack traces quickly: follow the call path from the error line back to your code, not into framework internals first. Add assertions for critical assumptions—fail early and clearly. And keep a personal “gotchas” note: weird edge cases you hit once are likely to appear again.
Practical AI tricks you can use now
Treat AI like a teammate for boring work. Use prompt templates for consistent outputs, and store the best prompts as part of your repo. For business tasks, use AI to draft summaries, extract key facts from documents, or generate unit test cases from examples. For code, use AI to explain unfamiliar functions or suggest refactors, but validate suggested logic and dependencies before merging.
Focus on cheap, high-value wins: automated ticket triage, draft responses for customer support, or a search index that uses embeddings for better docs lookup. These usually cost little and save real time.
If you want one next step: pick one habit—editor shortcuts, pre-commit hooks, or a small AI prompt library—and apply it for two weeks. Small changes compound faster than big rewrites.
