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10 Prompts I Reach for Every Week to Stay Unblocked as an Engineer

2026-06-08

10 Prompts I Reach for Every Week to Stay Unblocked as an Engineer

After five weeks of deliberately logging how I use AI during a normal engineering workweek, a clear set of patterns has emerged. Not the flashy demos — the quiet, repeatable ones that actually move work forward. Here are ten that have become muscle memory.

1. Translate a vague ticket into a scoped task list

Product tickets often arrive half-baked. Before I touch code, I paste the ticket text and ask:

You are a senior engineer helping me scope this ticket for implementation.
Given this ticket description: "[PASTE TICKET]"
Output: a numbered list of discrete technical tasks, any ambiguities I should clarify with product, and a one-sentence definition of "done".
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This takes 90 seconds and saves hours of mid-sprint confusion.

2. Write the test before the implementation

I stopped writing implementation code first. Instead I describe the behavior and ask AI to write the test contract:

Write a unit test suite for a function called `applyDiscount(cart, couponCode)`.
It should cover: valid coupon, expired coupon, coupon with a minimum cart value not met,
and a cart with zero items. Use Jest. Do not implement the function — only the tests.
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Having the test in front of me before I write a line of logic keeps the scope tight.

3. Generate the first draft of a PR description

Blank PR descriptions are a tax on your reviewers. I paste my diff summary and ask:

Given this list of changed files and a brief summary of what changed: [PASTE SUMMARY]
Write a pull request description with: a one-sentence summary, a bullet list of changes,
any areas reviewers should look at closely, and how to test it locally.
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4. Rubber-duck a design decision with structured pushback

Instead of a normal rubber-duck session, I want pushback:

I'm deciding between [Option A] and [Option B] for [specific problem].
Here's my current thinking: [reasoning].
Push back on my preferred option. What am I missing or underweighting?
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The forced devil's advocate framing produces better objections than a neutral "compare these two" prompt.

5. Explain an unfamiliar codebase section

When I land in a module I've never touched:

Explain what this code does, its likely inputs and outputs, any side effects,
and what could go wrong if someone modifies it without understanding it fully.
[PASTE CODE BLOCK]
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6. Draft an incident postmortem outline

When an incident closes, the postmortem doc gets written under pressure. I paste the timeline and ask:

Given this incident timeline: [PASTE]
Draft a postmortem outline with: summary, timeline, root cause, contributing factors,
impact, what went well, what didn't, and action items with owners TBD.
Keep the tone factual and blameless.
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7. Tighten a gnarly regex or SQL query

Rather than asking AI to write it from scratch, I show it what I have:

Here is a SQL query that's slow on large datasets: [PASTE QUERY]
Identify the likely performance bottlenecks and suggest a rewrite with explanation.
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This pattern is one of the ones I've packaged into The AI Leverage Playbook: 50 Prompts & Workflows for Engineers — but the version above is enough to get value on its own.

8. Spot missing error handling

I've started running a dedicated pass for error handling before submitting any PR:

Review this function for missing or inadequate error handling.
List each case where an unhandled error could cause a silent failure, crash, or bad user state.
[PASTE FUNCTION]
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The model catches edge cases I've mentally glossed over because I wrote the happy path first.

9. Write the runbook entry while the fix is fresh

Runbooks go stale because nobody writes them at the right moment. I do it immediately post-fix:

I just fixed this issue: [DESCRIBE ISSUE AND FIX IN 2-3 SENTENCES]
Write a runbook entry for on-call engineers. Include: symptoms, likely cause,
step-by-step remediation, and how to confirm it's resolved.
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10. Turn a Slack thread into a decision log

Long Slack threads where decisions got made are black holes. I paste the thread and ask:

Summarize this Slack thread as a decision log entry.
Include: the question being decided, options that were considered,
the decision made, who made it, and the rationale.
[PASTE THREAD]
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Three months from now, your future self will thank you.

The common thread

None of these are "write my code for me" prompts. Every one is about getting to clarity faster — tighter scope, better context, cleaner handoffs. The value isn't outsourcing thinking; it's compressing the parts of the job that drain time without demanding creativity.

Pick two of these to try this week. Keep the ones that stick.

I break down one workflow like this every week in The AI Leverage Weekly — practical, no fluff, free. It goes out every Monday and each issue is one concrete workflow you can use the same day. Subscribe: https://theaileverageweekly.beehiiv.com/subscribe?utm_source=devto&utm_medium=article&utm_campaign=long_w5

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