Project 10: AI Productivity Suite Capstone

Integrate planning, analytics, and mutation workflows into one production-grade ChatGPT App.

Quick Reference

Attribute Value
Difficulty Expert
Time Estimate 4+ weeks
Main Programming Language TypeScript
Alternative Programming Languages Python, Go
Coolness Level Level 5
Business Potential Very High
Prerequisites Projects 1-9, system integration mindset
Key Topics Multi-tool orchestration, shared contracts, production readiness

1. Learning Objectives

  1. Compose multiple tool domains into one coherent app.
  2. Maintain shared contracts across features without drift.
  3. Enforce trust boundaries for read/write operations.
  4. Deliver a submission-ready capstone with operational evidence.

2. All Theory Needed (Per-Concept Breakdown)

Cross-Feature Orchestration at Production Scale

Fundamentals As apps grow, the main risk shifts from individual tool correctness to cross-tool consistency. Capstone success requires coherent data contracts, shared IDs, and robust failure handling across feature boundaries.

Deep Dive into the concept Design orchestration as a graph of capabilities, not a monolithic flow. Each capability (planning, dashboarding, form mutation) has its own tool set and invariants. Define shared core entities and schema versions so one feature cannot silently break another.

Use correlation IDs across every tool call in a user journey. This enables end-to-end debugging and rollback decisions. For human trust, every mutating action should provide a concise preview of side effects and a post-action receipt.

Operationally, include chaos tests that combine failures: token expiry during dashboard refresh, stale cache during submit, external timeout during planning call. Capstone quality is measured by graceful behavior under compound failure, not perfect conditions.

Minimal concrete example

journey trace:
trc_122
- list_incidents -> success
- suggest_plan -> success
- update_task -> auth_expired
- reconnect -> success
- update_task retry -> success

3. Project Specification

3.1 What You Will Build

A productivity suite with:

  • planning assistant
  • incident dashboard
  • task mutation workflows
  • submission-ready hardening artifacts

3.2 Functional Requirements

  1. Unified workspace with shared identity and context.
  2. Cross-tool orchestration with deterministic receipts.
  3. Auth-aware write paths and safe retries.
  4. Full release scorecard and runbook evidence.

3.3 Real World Outcome

User asks for weekly plan.
App collects incidents, backlog, and priorities.
Widget presents plan with editable actions.
User confirms updates; receipts returned.
Release checks pass and app is submission-ready.

4. Solution Architecture

conversation intent -> orchestration router -> domain tools (plan/metrics/mutate) -> unified result model -> workspace widget

5. Implementation Guide

5.1 The Core Question You’re Answering

“Can I compose many reliable capabilities into one trustworthy assistant experience?”

5.2 Concepts You Must Understand First

  1. Shared schema governance.
  2. Orchestration error recovery.
  3. Operational release gating.

5.3 Questions to Guide Your Design

  1. Which entities are shared across all features?
  2. How are cross-tool failures surfaced without losing context?
  3. What are your launch-blocking quality metrics?

5.4 Thinking Exercise

Draw a capability dependency graph and mark failure blast radius.

5.5 The Interview Questions They’ll Ask

  1. How did you avoid integration drift across features?
  2. How do you debug cross-tool failures quickly?
  3. What trust boundaries did you enforce for writes?
  4. What launch metrics did you require?
  5. How do you roll back safely under active traffic?

5.6 Hints in Layers

  • Hint 1: Build one vertical end-to-end flow first.
  • Hint 2: Add shared schema package and version checks.
  • Hint 3: Add trace correlation across tools.
  • Hint 4: Run compound-failure chaos drills.

5.7 Books That Will Help

Topic Book Chapter
Architecture composition “Fundamentals of Software Architecture” Tradeoff analysis
Boundary discipline “Clean Architecture” Component boundaries
Delivery reliability “The Pragmatic Programmer” Automation and observability

6. Testing Strategy

  • End-to-end orchestration replay tests.
  • Cross-tool contract compatibility tests.
  • Compound-failure recovery tests.

7. Common Pitfalls & Debugging

Pitfall Symptom Solution
Schema drift One feature breaks another Versioned shared contracts
Missing correlation IDs Slow incident triage End-to-end trace IDs
Weak failure UX User abandons workflow Clear partial/failure recovery states

8. Extensions & Challenges

  • Add role-based collaboration mode.
  • Add recommendation quality evaluator.
  • Add automated weekly health report.

9. Real-World Connections

  • Enterprise AI operations assistants
  • Cross-team productivity copilots
  • Incident-to-action orchestration systems

10. Resources

  • OpenAI Apps SDK reference
  • OpenAI submit/test/troubleshoot docs
  • MCP specification and auth docs

11. Self-Assessment Checklist

  • I can design shared contracts across capabilities.
  • I can recover from compound failures gracefully.
  • I can justify launch readiness with evidence.

12. Submission / Completion Criteria

Minimum Viable Completion

  • Integrated multi-domain app with deterministic receipts.

Full Completion

  • Includes production hardening, chaos results, and submission-ready evidence pack.