ASO course · lesson 58 of 60

AI for ASO: research, writing and quality checks

Use AI to accelerate drafting and organization while retaining product truth, source accuracy and human approval.

By Gabriel Machuret · Editorial methodology

Before you start: An approved product brief, research evidence and a defined task.

See the worked example ↓

Module 10: Professional practice and capstone

An AI-assisted drafting machine routes output through human review.
Gabriel Machuret wearing an ASO Guru T-shirt, reviewing an AI-assisted draft on a tablet with a stylus.

Your instructorGabriel Machuret

About 18 minutes reading · 33 minutes practice

You will produce: A reviewed AI-assisted draft with prompt context, verification notes and a named approver.

Give the model a bounded job

Ask for alternatives, classification or editing against supplied constraints. Provide the audience, product capabilities, prohibited implications and output format. A generic request for winning keywords invites unsupported confidence. AI output is a draft or suggestion until its claims and usefulness have been reviewed.

Check evidence rather than fluency

Verify sources at the original destination and confirm that they support the associated statement. Recalculate numeric examples. Inspect translations with a qualified local reviewer. Do not treat a fabricated citation or confident explanation as evidence. Keep generated ideas separate from observed customer research.

Protect the approval process

Use only information appropriate for the approved working environment. Avoid including unnecessary personal or confidential customer data in prompts. Record meaningful AI assistance in the production notes and assign a human owner for publication. Automation should not bypass product, policy or language review.

Quick check · pick a response

Make the call before you scroll.

An AI tool predicts a 40% conversion lift from a new subtitle. What should you do?
Go deeper: practical decisions and tradeoffs

Separate source facts from generated possibilities

Give the model a verified product brief and label the evidence it may use. Ask it to distinguish supplied facts, inferences and new ideas in its output. A generated keyword suggestion is not a customer quote; a plausible statistic is not measured data. Keep the source material available to the reviewer. For tasks such as theme coding, inspect examples where the model may have merged different meanings. The tool can accelerate organization while still making errors that matter to the decision.

Use a repeatable verification pass

Check each important claim against the released product or a primary source. Open citations and verify both the destination and the specific support. Recalculate numeric examples independently. Review local language with a qualified person and inspect final artwork for text errors. If the model cannot support a claim, remove it, qualify it or turn it into a research question. Do not ask the model merely whether it is sure; confidence phrasing does not supply evidence.

Document the human decision

Preserve the task brief, useful prompt context, selected output and major edits when they explain the production decision. Assign a human approver for truth, language and publication. Use data appropriate for the approved environment and omit unnecessary personal details. A review checklist should apply equally to human and AI drafts, with extra attention to fabricated sources and plausible but unsupported capabilities. The final artifact should read as a coherent product message rather than exposing internal prompt machinery to users.

Platform references for this work: Apple — App Store search · Google Play — Metadata policy

Your turn · two-minute exercise

Try the scenario. Make your case.

Audit a draft containing a fabricated source, an unsupported feature and a correct arithmetic example. Explain why each requires a different check and why correcting one does not validate the others.

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Your step-by-step procedure

From observation to action
  1. Write a constrained prompt using verified product facts.

  2. Generate alternatives and label them as drafts.

  3. Verify claims, sources, calculations and local meaning.

  4. Approve the final artifact through the same production process as human-written work.

Completed example · use the reasoning

An AI draft with a fact check

Gabriel’s take: AI can write “offline GPS” in a second. Your developers still have to build it.

Constructed teaching material, not a client result. Adapt the evidence and product facts before using it for your app.

Prompt

Write a journal description using only photos, notes and trip folders. Export is paid. No navigation.

Bad output

Explore any trail with offline GPS and unlimited free exports.

Fact check

Offline GPS unsupported; free export claim false

Corrected

Save photos and notes from your walks, organize them into trips and revisit your memories. Journal export requires paid access.

Your turn · repair the decision

Make the call. Then compare.

Repair the bad output and identify the two facts you must verify.

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Explore the supporting case and interpretation

AI suggests “offline GPS navigation” for Trail Notes because the app is about hiking. The reviewer rejects it using the product capability list, then asks for journal-focused alternatives. The speed of generation does not make the unsupported suggestion suitable.

AI output: Offline navigation claim

Verification action: Compare with released capabilities

Disposition: Reject if unsupported

AI output: Source link

Verification action: Open and inspect relevant passage

Disposition: Keep only if it supports the claim

AI output: Keyword idea

Verification action: Check intent and provenance

Disposition: Add as research candidate

AI output: Numeric example

Verification action: Recalculate with explicit inputs

Disposition: Correct before publication

The verification action depends on the type of output. A source link cannot validate a product-specific capability, and a product demo cannot establish market demand. The reviewer must ask what evidence would actually support the claim. This discipline lets AI contribute speed without turning fluent guesses into the foundation of the course or a client recommendation.

Build a handover someone can use

Task context

Save the product facts, constraints and intended output given to the tool.

Draft status

Label generated ideas and distinguish them from observed research evidence.

Verification record

Document source, product, arithmetic and language checks relevant to the output.

Editorial decision

Explain important rejected or rewritten suggestions and the reason.

Approval

Name the human owner of the final artifact and its publication status.

Your ASO assignment

Use your own app and evidence, or work through the teaching case. Keep your observations separate from assumptions and explain the reasoning behind your decisions.

Build something · track your work

Your assignment checklist

Tick each item after you have produced the work. Reading it does not count. The strategy deck will survive.

0 of 3 tasks checked.

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Assess your work

  • Generated suggestions are not presented as customer observations.
  • Every important factual claim has verified support.
  • Human review remains responsible for the published result.

Common mistakes to catch

  • Publishing plausible citations without opening them.
  • Using AI confidence as a substitute for local-language expertise.

Sources and further reading

Platform references reviewed 29 September 2026. These sources support platform capabilities and constraints; the teaching frameworks, assignments and illustrative cases are original course material.

Your ASO lesson notes

Use this space for your assignment, evidence and handover. Your notes save automatically in this browser. Download a copy to take with you.

Notes stay on this device and are not submitted to ASO Agency.

Complete your assignment with the App store metadata checker.

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