Guide
How to Make AI Return Valid JSON Every Time
AI models return broken JSON more often than you'd expect. Here's how to structure a prompt so the output parses cleanly, plus what to check before you trust it.
← Back to AI Output Validator
Guides for AI Output Validator
Explore all 14 guides related to AI Output Validator.
14 guides
Guide
How to Stop AI From Inventing Missing Data
When a source is missing a field, AI tends to fill the gap with a plausible guess instead of saying it isn't there. Here's how to make the model mark missing data explicitly — and check the result before you trust it.
Guide
How to Keep AI Output Format Consistent
The AI nails your format once, then the next output adds a "Sure, here's…" wrapper, renames a field, turns the table into bullets, and drops a section. Here's how to write the format as a contract and catch the drift when it happens anyway.
Guide
How to Extract Data From Documents With AI Without Losing Evidence
AI pulls the fields you asked for, but hands back a flat list with no way to tell which values it read from the document and which it guessed. Here's how to make each extracted value carry its source quote, location, and a review flag — so you can check the result instead of trusting it.
Guide
How to Review AI Output Against a Source Document
An AI summary reads perfectly, but you can't tell if every sentence is in the source or whether a "may" hardened into a "will." Here's how to review AI output claim-by-claim against the document it came from, so unsupported and overstated claims surface before you rely on them.
Guide
How to Make AI Follow Acceptance Criteria
The output reads well and answers the question, so you almost ship it — then you notice it broke a rule you cared about and skipped a section you needed. "Looks good" was never the test. Here's how to give AI the acceptance criteria up front and check the output against them before you rely on it.
Guide
How to Revise AI Output Without Breaking What Already Works
The draft is 90% right and you ask AI to fix the one thing that's wrong — and it hands back a whole new version with the good parts rewritten worse. Here's how to ask for a targeted edit that fixes what's broken and leaves the rest exactly as it was.
Guide
How to Find Gaps in an AI-Generated Plan Before You Use It
The plan AI hands you reads clean and complete — until you try to execute it and hit the missing rollback, the unnamed owner, the decision nobody made. Here's how to run a separate gap-review pass that surfaces what's missing, risky, or unclear before you act on it.
Guide
How to Make AI Separate Facts, Assumptions, and Recommendations
Ask AI to analyze something and it hands back one smooth paragraph where you can't tell what you told it from what it assumed from what it's recommending. Here's how to make it split the answer into visible layers — facts, assumptions, inferences, recommendations, and what still needs checking.
Guide
How to Create an AI QA Checklist Before Using Generated Content
AI hands you a polished email, landing page, or support reply that looks ready to send — and only after you send it do you find the claim you can't back or the audience you got wrong. Here's how to build a reusable QA checklist and review generated content against it first.
Guide
Define Fields So AI Fills Them the Same Way Every Time
You ask AI to fill a table — issue_type, priority, reason — and the same column gets filled by different logic each row: priority as urgency here, sentiment there. Here's how to define each field's meaning, allowed values, and include/exclude rules so AI fills them consistently.
Guide
How to Design a Database Schema With AI
Four sentences of requirements go in, a confident schema comes out — and it quietly decided three things nobody decided. Here's how to turn real domain rules and access patterns into a reviewable database schema, with the modeling gaps named as open questions instead of guessed.
Guide
How to Write a README With AI From Your Project Facts
Your README works perfectly on the one machine where the tool was already installed. Everyone else hits a missing prerequisite in the first ninety seconds. Here's how to build a README from your real setup facts — and the clean-machine run that decides whether any of it is true.
Guide
How to Evaluate an AI Agent With a Scorecard
Build an evaluation scorecard two people can apply to the same agent run and reach the same number — dimensions that don't measure each other, anchors you can point at, and the failures that shouldn't average out.