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What do you wish AI would keep improving for you?
WTF is an agent loop?: A loop is a task with a check.
You ask AI to fix something.
It gives one answer.
Maybe the answer helps.
Then you still have to check it, explain the failure, ask again, and push it toward the finish line.
That is fine for small tasks.
It breaks when the work needs repeated attempts.
Forward Future's new Loop Library, has 31 repeatable agent loops across engineering, evaluation, operations, content, and design. The useful idea is simple: a loop tells the agent what to do, how to check the result, what to try next, and when to stop.
That last part matters.
A loop still needs boundaries.
I am Alex, welcome to ShortCu8 by Innov8.
Lets Dive Deep 🐰
⭐Today's Shortcut
Do not tell AI to improve something.
Tell it how to know whether the improvement worked.
A useful loop needs five parts:
1. Goal
What should improve?
2. Check
How do we know it improved?
3. Step size
What is one small change?
4. Stop rule
When should the agent stop?
5. Human approval
What should never happen without you?If one of these is missing, the loop becomes expensive guessing.
1. Docs Sweep
Use this when your README, setup guide, API docs, or internal notes are stale.
Read the current codebase.
Find docs that no longer match.
Update only stale docs.
Verify each change against the implementation.
Open a reviewable PR.The important part is "verify against the current implementation."
Without that check, the agent may rewrite docs into prettier wrong docs.
2. Website Speed Loop
Use this when a site feels slow and you want measured progress.
Measure every page under the same test setup.
Pick the slowest page.
Make one speed change.
Measure again.
Keep it only if it helps.
Stop when every page is under the target.The target can be 50 ms, 500 ms, Lighthouse score, Core Web Vitals, or your own benchmark.
The number is less important than keeping the check fixed.
If the benchmark changes every round, the agent cannot tell if the work improved.
3. Production Error Sweep
Use this when logs are noisy and you want actual fixes.
Read production logs.
Find one actionable error.
Trace root cause.
Fix it.
Verify the fix.
Open a PR.
Stop if no actionable error exists.The no-op condition is the hidden power.
The agent is allowed to say:
No actionable error found. No change made.That is better than a random cleanup PR.
4. Quality Streak Loop
Use this for product testing, support bots, dashboards, onboarding flows, or AI features.
Run realistic scenarios.
When one fails, document it.
Add regression coverage.
Fix the cause.
Restart the streak.
Stop after N clean passes in a row.This works because the agent is not grading itself with a vague "looks good."
It has to survive repeated cases.
For a small product, start with five realistic cases.
For important workflows, use ten or more.
5. Ticket-to-PR Loop
Use this when you have a bug report, complaint, or failing behavior.
Reproduce the issue.
Prove the root cause.
Make the smallest credible fix.
Run the original reproduction again.
Run regression tests.
Finish with cause, changed files, before-after proof, risks, and PR summary.This loop stops the agent from turning one bug into a full refactor.
If it cannot reproduce the issue after two serious attempts, it should say that and stop.
No fake confidence.
No unrelated cleanup.
Copy This Loop Template
Use this in Codex, Claude Code, Cursor, Devin, Factory, or any agent that can edit files and run checks.
When [trigger], inspect [fresh inputs].
Choose one in-scope action using [criteria].
Make only that change.
Run [acceptance check] under the same conditions.
Record:
- what changed
- evidence
- next step
- blocker if any
Repeat only while progress is measurable and [budget] remains.
Stop when [success gate] passes.
Stop without changes when [no-op condition] is true.
Ask me before [risky action].
Never [forbidden action].
Finish with [PR, report, artifact, or handoff].Example:
When I say "run docs sweep", inspect the repo and docs.
Choose one stale doc section at a time.
Update only that section.
Run links check and verify the changed text against current code.
Record changed files, evidence, and any docs you skipped.
Repeat while stale docs remain and the budget is under 45 minutes.
Stop when no stale docs remain.
Stop without changes if docs already match.
Ask me before deleting any doc.
Never change product behavior.
Finish with a PR summary and remaining risks.When To Avoid Loops
Do not loop everything.
Use a normal prompt for:
one simple answer
one rewrite
one explanation
one quick comparisonAvoid loops when:
the goal is unclear
there is no check
every step needs human taste
the action touches money
the action touches production data
the agent can message customersThe Loop Library safety page says loops need limits: time, cost, retry count, iteration count, and affected scope.
That is the part people skip when they get excited.
Now go build something great.
The ShortList
🛠️Cool Tools of the Week:
Vercel Eve: An open-source agent framework for building, running, and scaling agents.
Unreal Engine 5.8: The 3D design platform now has experimental MCP server support.
Claude Design: Anthropic's AI design tool has gotten an overhaul, including a fix to how fast it burns through tokens.
ChatGPT: OpenAI's flagship chatbot now has a faster, more reliable, and easier to manage scheduled tasks.
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