Project 9: App Submission and Production Hardening

Convert a working app into a publishable, supportable, and review-ready product artifact.

Quick Reference

Attribute Value
Difficulty Advanced
Time Estimate 2-4 weeks
Main Programming Language N/A (process + automation)
Alternative Programming Languages TypeScript for CI checks
Coolness Level Level 4
Business Potential Critical Launch Lever
Prerequisites Prior app implementation, CI familiarity
Key Topics Submission quality, metadata clarity, runbooks, release gates

1. Learning Objectives

  1. Build a submission readiness checklist with evidence links.
  2. Encode quality gates in automated checks.
  3. Produce trust and privacy documentation aligned with implementation.
  4. Create incident response and rollback playbooks.

2. All Theory Needed (Per-Concept Breakdown)

Production Readiness for ChatGPT Apps

Fundamentals A publishable app is defined by reliability, trust, and operational clarity, not only feature completeness. Submission reviewers and users both evaluate whether behavior is safe, useful, and predictable.

Deep Dive into the concept Readiness has four pillars: contract clarity, policy compliance, operational resilience, and supportability. Contract clarity includes accurate metadata and truthful capability descriptions. Policy compliance requires safe interaction design and explicit boundaries for sensitive actions. Operational resilience includes monitoring, synthetic checks, and rollback criteria. Supportability requires clear runbooks and user-facing error guidance.

A common failure mode is documentation drift. If metadata promises behavior not reflected in runtime traces, trust collapses quickly. Keep documentation generated from validated checks where possible.

Build a release scorecard with blocking and non-blocking gates. Blocking gates should include auth flow integrity, error envelope conformity, and deterministic smoke tests for core journeys.

Minimal concrete example

release scorecard:
- auth flow integrity: PASS
- metadata completeness: PASS
- synthetic journeys: PASS (20/20)
- rollback rehearsal: PASS

3. Project Specification

3.1 What You Will Build

A complete submission package and production hardening workflow.

3.2 Functional Requirements

  1. Automated checklist runner.
  2. Metadata and policy evidence pack.
  3. Synthetic smoke tests for core user journeys.
  4. Incident and rollback runbook.

3.3 Real World Outcome

$ npm run check:submission
[ok] metadata integrity
[ok] auth recovery path
[ok] error taxonomy conformance
[ok] synthetic user journeys
score: 95/100

4. Solution Architecture

CI pipeline -> quality gates -> evidence artifacts -> release decision -> deploy + monitor

5. Implementation Guide

5.1 The Core Question You’re Answering

“What evidence proves this app is ready for real users and platform review?”

5.2 Concepts You Must Understand First

  1. Blocking vs advisory quality gates.
  2. Documentation-as-evidence strategy.
  3. Rollback triggers and incident communication.

5.3 Questions to Guide Your Design

  1. Which checks must fail the release?
  2. How do you prove privacy claims technically?
  3. What metrics trigger rollback?

5.4 Thinking Exercise

Design a release policy for three severity levels of production regressions.

5.5 The Interview Questions They’ll Ask

  1. How do you automate submission readiness?
  2. What makes metadata high-signal?
  3. How do you test auth and recovery before release?
  4. How do you choose rollback thresholds?
  5. How do you keep runbooks actionable?

5.6 Hints in Layers

  • Hint 1: Start with one synthetic journey.
  • Hint 2: Convert checklist items into CI checks.
  • Hint 3: Add scorecard outputs.
  • Hint 4: Run a tabletop incident drill.

5.7 Books That Will Help

Topic Book Chapter
Production discipline “The Pragmatic Programmer” Automation and feedback
Clean operational boundaries “Clean Architecture” Policy/control boundaries
Engineering quality “Code Complete” Testing and verification

6. Testing Strategy

  • Synthetic end-to-end checks.
  • Release scorecard validation.
  • Runbook drill simulation.

7. Common Pitfalls & Debugging

Pitfall Symptom Solution
Checklist not automated Last-minute surprises Move checks into CI
Vague metadata Review rejection risk Use concrete capabilities and limits
No rollback plan Slow incident response Define objective rollback triggers

8. Extensions & Challenges

  • Add staged rollout with canary scoring.
  • Add policy drift detector.
  • Add weekly reliability report automation.

9. Real-World Connections

  • Production release governance
  • Compliance-ready AI product launches
  • Platform partner readiness workflows

10. Resources

  • OpenAI app submission guidelines
  • OpenAI optimize-metadata docs
  • OpenAI security-privacy docs

11. Self-Assessment Checklist

  • I can produce a release scorecard with evidence.
  • I can map failures to rollback decisions.
  • I can keep metadata and behavior aligned.

12. Submission / Completion Criteria

Minimum Viable Completion

  • Submission checklist runner and evidence artifacts.

Full Completion

  • Includes CI gating, synthetic journeys, and rollback rehearsal results.