Chatgpt for coding is best used as a fast collaborator for debugging, explanation, and review. It can accelerate iteration, but it should not replace verification.
What to do before using chatgpt for coding
Provide context first: stack, runtime, constraints, and error output. Without context, answers become generic and less reliable.
Step-by-step workflow or setup
Use a three-pass loop: ask for diagnosis, ask for a patch proposal, then ask for risk review and test suggestions. This catches shallow fixes early.
Best prompts, examples, or templates to start with
Try: “Given this traceback and snippet, propose a minimal fix, explain tradeoffs, and list tests to run.” This fits well with how to use chatgpt for work and what is gpt-5.5.
Common mistakes and how to avoid them
Common failures are accepting code without tests, ignoring security implications, and pasting partial context. Always run and review before merging.
When this approach works best and when it does not
It works best for bug isolation, refactor ideas, and review framing. It works poorly for compliance-critical code without strict validation. Use official OpenAI documentation for current capabilities: OpenAI Help.