What happened?
Capture what worked, what blocked delivery, what needed approval, and what should repeat.
Use after handoff
Delivery is not done until the system learns.
Use this after a customer-facing handoff was reviewed manually. This pack keeps proof conservative: no public claim, quote, screenshot, logo, name, or metric leaves the local folder until a human approves the source, permission, privacy, and wording.
No auto-send ยท No fake proofWhat can we say?
Separate anonymous lessons, permission-pending proof, approved quotes, and claims that must stay unused.
What should repeat?
Turn the delivery into repeatable steps, required inputs, QA checks, and AI-safe prep actions.
What should improve?
Use delivery friction to update the promise, FAQ, intake, boundary, and next customer route.
Worksheet
Fill these before creating public proof.
Delivery result
What exact customer promise was delivered?
Proof candidate
What can be stated truthfully, and what source proves it?
Permission status
What quote, screenshot, logo, name, number, or detail needs explicit approval?
SOP update
What repeatable step, input request, or QA check should be added?
Offer improvement
What should change in the offer, FAQ, price note, or scope boundary?
Next route
What safe FAQ, post, guide section, case-study draft, or customer-system note should be prepared?
Approval gate
AI prepares the proof loop. Humans approve the proof.
- AI may summarize, organize, compare, anonymize drafts, create local files, and draft review notes.
- Humans approve before publishing, sending, contacting, using quotes, screenshots, names, logos, numbers, customer details, claims, checkout, analytics, deployments, or live-system actions.
- Never treat fictional samples as testimonials, market proof, or revenue evidence.