10 high-signal AI prompts for developers. Zero filler.
Role: Developer submitting code for review Use case: When you want a senior engineer’s eye on a PR before it hits production.
You are a senior {language} engineer with 10+ years of experience. Review the following code for correctness, edge cases, and potential bugs. For every issue you find, explain: (1) what the bug is, (2) under what conditions it triggers, and (3) the exact fix with corrected code. After the bug list, give a 3-sentence summary of overall code quality and the single highest-priority change. Do not praise what works — only surface what needs attention.
{code}
Role: Engineer or tech lead evaluating design options Use case: When you’re about to commit to an architecture and need a rigorous tradeoffs analysis before you do.
I’m building {feature_description} in a {codebase} using {language/stack}. I’m considering the following approaches: {option_1}, {option_2}, {option_3}. For each option, give me: scalability ceiling, failure modes, maintenance burden at 12 months, and which team size it’s optimized for. End with a single recommendation and the one assumption that, if wrong, would invalidate it. Be direct — I need a decision, not a survey.
Role: Developer staring at an error they can’t crack Use case: When you’ve been stuck on a bug for more than 20 minutes and need a methodical outside view.
I’m seeing the following error in my {language} application: {error}. Here is the relevant stack trace and surrounding code: {stack_trace_and_code}. Walk me through root cause analysis: (1) what this error class typically means, (2) the 3 most likely causes ranked by probability given my code, (3) the exact diagnostic steps to confirm which cause it is, and (4) the fix for each possible cause. Do not guess — trace the logic.
Role: Developer writing or reviewing inline documentation Use case: When you need production-quality docstrings/comments for a function without spending 15 minutes writing them yourself.
Write a complete {language}-style docstring for the following function. Include: a one-line summary, a longer description of what it does and why (not just what the code says), all parameters with types and what they represent, return value with type and meaning, any exceptions that can be raised and when, and one usage example that covers the non-obvious case. Match the tone and format of the {docstring_format} standard (e.g., Google, NumPy, JSDoc).
{function_code}
Role: Developer committing changes to a shared repository Use case: When you’ve made meaningful changes and need a commit message that will make sense to your future self and your teammates in 6 months.
I made the following changes to {codebase}: {diff_or_description}. Write a git commit message following the Conventional Commits spec. Line 1: type(scope): imperative summary under 72 chars. Lines 3+: bullet points explaining why the change was made, not what changed (the diff shows what). Include any breaking changes, linked issue numbers ({issue_format}), and one sentence on the approach chosen if a non-obvious decision was made. No filler phrases like “updated” or “fixed stuff.”
Role: Developer doing a self-review before requesting teammates’ time Use case: When you want to improve code quality, readability, and maintainability before opening a PR.
You are a principal engineer reviewing this {language} code for a production {codebase}. Do not look for bugs — assume it works. Instead, identify: (1) readability issues that will slow down the next developer, (2) abstractions that are either missing or over-engineered, (3) performance optimizations worth making vs. premature optimizations to skip, and (4) any violations of the SOLID principles or {style_guide}. For each finding, show the before and after. Rank by impact, highest first.
{code}
Role: Developer debugging a system that fails without throwing errors Use case: When your code runs successfully but produces wrong output and you have no stack trace to follow.
My {language} function is producing incorrect output with no error thrown. Expected: {expected_output}. Actual: {actual_output}. Input: {input}. Code: {code}. Analyze this systematically: check for off-by-one errors, type coercion issues, mutated state, incorrect assumptions about input shape, and logic branches that silently return the wrong value. For each candidate, show me the exact condition that would produce my observed output and the one-line fix. Start with the most likely cause.
Role: Tech lead planning a refactor of legacy code Use case: When you need to migrate messy legacy code to a clean architecture without breaking production.
I have a {language} codebase with the following structure: {current_structure}. It has these known pain points: {pain_points}. I want to migrate toward {target_architecture} (e.g., hexagonal, clean architecture, event-driven). Give me a phased refactor plan where each phase: (1) can be shipped independently without breaking existing behavior, (2) has a clear “done” criteria, and (3) reduces risk rather than increasing it. Flag any refactors that require a feature freeze and explain why. I need this ordered by business risk, not technical elegance.
Role: Developer open-sourcing or handing off a project Use case: When you need a complete, professional README that makes strangers actually want to use your project.
Write a complete README.md for the following project: {project_name}. The project does: {what_it_does}. Tech stack: {stack}. Here is the entry point / main module: {code_or_description}. The README must include: a one-paragraph hook that sells the project in plain English, a prerequisites section, step-by-step installation that works on a fresh machine, a usage section with at least 2 real examples (not “Hello World”), a configuration reference table, and a contributing section. Use concrete commands. Assume the reader has never seen this codebase.
Role: Developer opening a pull request for team review Use case: When you need a PR description that gives reviewers everything they need to review fast and merge with confidence.
Write a pull request description for the following changes to {codebase}: {diff_or_summary}. Structure it as: (1) What — one paragraph on what changed and what it enables, (2) Why — the problem this solves or the requirement it fulfills, referencing {issue_or_ticket} if applicable, (3) How — the key technical decisions made and any alternatives considered, (4) Testing — how to verify it works, including the exact steps a reviewer should run, (5) Risks — anything that could go wrong and how it was mitigated. Write for a reviewer who is smart but has zero context on this ticket.
Role: Developer using AI to ship a feature without wasting premium model tokens Use case: When you want to split feature work across the right model tiers instead of asking one expensive model to do everything.
You are an AI workflow architect helping me ship {feature_or_bugfix}. Design a three-step implementation workflow using the right model for each phase: (1) Requirement Gathering with a cheap fast model such as Flash, Mini, or Haiku-level: extract missing requirements, assumptions, edge cases, acceptance criteria, and questions; (2) Planning with a medium premium model at Sonnet level: turn the requirements into a technical plan with files/modules likely touched, sequencing, risks, and verification steps; (3) Execution with a Sonnet-level coding model: implement the plan, run focused tests, and prepare a review summary. Only recommend escalating above Sonnet level if the implementation fails twice for the same reason, requires unusually long-running reasoning, or involves a genuinely complex architecture change Sonnet cannot hold in context. End with a reminder that code review is more important than the plan: the plan points the work, but review catches the mistakes that ship.
Role: Developer checking AI-written code before merge Use case: When an AI-generated implementation looks plausible but needs a serious review before it earns trust.
You are a principal engineer reviewing AI-assisted code. Treat the plan as useful context, not proof of correctness. Review the following implementation against {requirements}, {plan}, and {diff_or_code}. Prioritize review over planning: find the defects, missing requirements, unsafe assumptions, edge cases, security issues, tests that should exist but do not, and places where the code only appears to satisfy the plan. Separate findings into: Must Fix Before Merge, Should Fix Soon, and Nice To Improve. For every Must Fix item, include the exact file/function, why it matters, and the smallest safe correction. If the code is solid, say what evidence supports that judgment and what residual risk remains.