@Ryrenz: Most people using coding AI just say “help me fix this bug,” then spend half an hour wrestling with it. Change the phrasing and it gets it right the first time. 1. Have it look before acting “Don't write code yet. Read the relevant files and tell me how this feature currently works; I'll confirm before you change it.” 2. Stuck bug “Don't guess. Add log…

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Summary

A practical tip on how to use coding AI more effectively. It lists 12 concrete prompt examples—such as having the AI read the code before modifying it, changing only the necessary parts, and writing rules into AGENTS.md—to reduce back-and-forth and make the rules stick long-term.

Most people using coding AI just say “help me fix this bug,” then spend half an hour wrestling with it. Change the phrasing and it gets it right the first time. 1. Have it look before acting “Don't write code yet. Read through the relevant files and tell me how this feature currently works; I'll confirm before you make changes.” 2. Stuck bug “Don't guess. Add logging to print out the intermediate state, run it, locate the problem based on the real output, and only then make changes.” 3. Prevent it from making a bunch of unrelated changes “Only change what's necessary to make this test pass. Don't touch other files or any formatting.” 4. Taking over an unfamiliar project “Assume I'm on day one in this repo. Tell me where the entry point is, how data flows, and which files are core. Don't change anything yet.” 5. Let it find work on its own “Run the tests and type checks, and list all failures in order of severity. I'll pick which ones you fix.” 6. Refactor without breaking things “Before refactoring, add tests to lock down the current behavior. Once the tests are green, change the structure and rerun after every step.” 7. Cure its verbosity “From now on, only give conclusions and changes in your answers. Don't restate my requirements, and don't summarize what you did.” 8. Make it admit when it doesn't know “If you're not sure about something, just say you're not sure. Don't give me a plausible-looking answer. I'd rather you ask me.” 9. Write commit messages “Look at the git diff and the style of the last ten commits, and write this commit message in the same tone and format.” 10. Making technical decisions “Give me two options. For each, clearly explain the cost and under what circumstances you'd regret it. Finally, give a recommendation and the reason. Don't list pros.” 11. Keep long tasks on track “Before you start, write me a plan, step by step. After each step, stop and wait for my confirmation before moving on.” 12. Make rules last long-term “Write the agreement we just made into the project's AGENTS.md, and follow it every time from now on.” The last one is the most valuable: what works isn't the prompt—it's turning effective prompts into project rules so you don't have to say them again every time.
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Cached at: 08/05/26, 08:29 PM

Most people, when using programming AI, just say “Help me fix this bug,” and then spend half an hour going back and forth with it. Change your wording, and it’s right on the first try.

  1. Make it look before it acts “Don’t write code yet. Read through the relevant files first, tell me how this feature currently works, and I’ll confirm before you change anything.”

  2. Stuck bugs “Don’t guess. Add logging to print out the intermediate states, run it once, locate the issue from the real output, then fix it.”

  3. Keep it from casually changing a bunch of unrelated stuff “Only change what’s necessary to make this test pass. Don’t touch other files, and leave any formatting alone.”

  4. Taking over an unfamiliar project “Assume it’s my first day in this repo. Tell me where the entry point is, how the data flows, and which files are core. Don’t change anything yet.”

  5. Let it find work on its own “Run the tests and type checks once, list all failures sorted by severity, and I’ll pick which ones you fix.”

  6. Refactoring without derailing “Before refactoring, add tests to lock in the current behavior. Once the tests are green, then change the structure, and rerun after every step.”

  7. Curing its chatty responses “From now on, only give conclusions and changes in your responses. Don’t restate my requirements, and don’t summarize what you did.”

  8. Get it to admit when it doesn’t know “If you’re not sure about this part, just say you’re not sure—don’t give me a seemingly reasonable answer. I’d rather you ask me.”

  9. Writing commit messages “Look at the git diff and the style of the last ten commits, and write this commit message in the same tone and format.”

  10. Making technical decisions “Give me two options, spell out the cost of each and in what scenarios you’d regret it, and end with one recommendation and your reasoning. Don’t just list advantages.”

  11. Keep long tasks on track “Before you start, write me a plan broken into steps. Pause after each step and wait for my confirmation before moving on.”

  12. Make rules stick long-term “Write this agreement we just reached into the project’s AGENTS.md, and follow it from now on.”

The last one is the most valuable: what works well isn’t the prompt itself—it’s turning effective prompts into project rules, so you don’t have to say them again every time.

Qiaomu Ge’s sharing is well worth referencing:

  1. Put together a set of impressive, high-value content in one domain.
  2. Keep at it consistently and show up on schedule.
  3. Manage your posting volume and timing well—mealtimes and weekends are good for long-form content.
  4. Product posts must be personally tested; share experiences that exceeded your own expectations.
  5. After reading enough good content, you’ll naturally want to think, test, and comment—just post it directly.

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