Project 5: Form-Based Data Entry App

Build a safe, auditable form workflow with draft/save/submit boundaries and deterministic validation.

Quick Reference

Attribute Value
Difficulty Intermediate
Time Estimate 1-2 weeks
Main Programming Language TypeScript
Alternative Programming Languages Python, Java
Coolness Level Level 3
Business Potential Very High
Prerequisites Validation design, transactional thinking
Key Topics Draft state, commit safety, provenance receipts

1. Learning Objectives

  1. Separate draft and commit operations.
  2. Enforce consistent client/server validation.
  3. Provide explicit confirmation for side effects.
  4. Return auditable receipts for commits.

2. All Theory Needed (Per-Concept Breakdown)

Mutation Safety in Conversational UIs

Fundamentals Forms in ChatGPT Apps are high-risk because chat context can obscure what has and has not been committed. Draft and submit must be explicit states, and all side effects must be traceable.

Deep Dive into the concept Data-entry reliability starts with state partitioning: transient input state, validated draft state, and committed record state. Validation must be deterministic and shared between UI and server contract. If these diverge, users see false confidence. Add confirmation summaries before submit and expose exact side effects.

Receipts are critical. Every successful mutation should return stable IDs and timestamps for support and audit trails. Implement idempotency on commit operations so retries do not duplicate records.

Minimal concrete example

submit result:
{ status:"accepted", record_id:"vnd_20441", committed_at:"2026-02-11T19:42:10Z", trace_id:"trc_51a" }

3. Project Specification

3.1 What You Will Build

A multi-step onboarding form with draft autosave, validation, review, and submit.

3.2 Functional Requirements

  1. Validate each field with actionable messages.
  2. Save drafts without committing.
  3. Require explicit confirmation for submit.
  4. Show receipt details after successful submit.

3.3 Real World Outcome

User completes 3-step form.
Validation warnings shown and corrected.
User confirms submit.
Receipt card appears with record ID and timestamp.

4. Solution Architecture

input events -> validator -> draft tool -> review state -> submit tool -> receipt renderer

5. Implementation Guide

5.1 The Core Question You’re Answering

“How do I prevent silent data corruption in a conversational form workflow?”

5.2 Concepts You Must Understand First

  1. Shared schema validation.
  2. Draft vs commit transaction boundaries.
  3. Idempotent submit patterns.

5.3 Questions to Guide Your Design

  1. Which fields are required for draft vs submit?
  2. What side effects are listed in confirmation summary?
  3. Which failure reasons should user correct directly?

5.4 Thinking Exercise

Design a form state machine including retry-after-failure transitions.

5.5 The Interview Questions They’ll Ask

  1. How do you avoid validation drift?
  2. Why split draft and submit tools?
  3. What data belongs in commit receipts?
  4. How do you make submit retries safe?
  5. How do you audit form mutations?

5.6 Hints in Layers

  • Hint 1: Build schema once and reuse everywhere.
  • Hint 2: Add save-draft before submit.
  • Hint 3: Include explicit confirmation summary.
  • Hint 4: Attach trace IDs to commit receipts.

5.7 Books That Will Help

Topic Book Chapter
Reliable workflows “Clean Architecture” Use case boundaries
Defensive validation “Code Complete” Validation chapters
System consistency “The Pragmatic Programmer” Automation and testing

6. Testing Strategy

  • Field validation tests.
  • Draft persistence tests.
  • Commit idempotency tests.

7. Common Pitfalls & Debugging

Pitfall Symptom Solution
Drifted schemas Passes UI, fails server Shared schema source
Missing submit confirmation Unintended writes Confirmation gate
Non-auditable commits Hard support triage Return receipt + trace ID

8. Extensions & Challenges

  • Add attachment upload flow.
  • Add policy-check simulation step.
  • Add collaborative edit handoff.

9. Real-World Connections

  • CRM onboarding
  • Vendor enrollment
  • HR intake workflows

10. Resources

  • OpenAI MCP server docs
  • OpenAI testing and troubleshooting docs

11. Self-Assessment Checklist

  • I can explain draft/submit boundaries.
  • I can enforce consistent validation.
  • I can produce auditable mutation receipts.

12. Submission / Completion Criteria

Minimum Viable Completion

  • Working draft + submit form with deterministic validation.

Full Completion

  • Includes idempotent commits, receipt tracing, and failure recovery UX.