✅ Roles and Responsibilities

  • Clear separation of roles ✅
  • You staying in BA / product brain
  • ChatGPT = thinking partner / architect
  • Cursor = builder
  • Markdown BRD in repo ✅ (this is excellent)

This is already better than:

“prompt → code → chaos”


⚠️ What needs sharpening

1. Cursor is NOT a “Lead Developer AI”

Right now you’ve got:

Lead Developer AI (Cursor)

That’s slightly off.

Cursor is more like:

Senior engineer who executes and refines — not owns architecture

If you let Cursor lead:

  • it will optimise locally (per file)
  • not globally (whole system)
  • and you’ll get drift

2. Missing layer: Architecture Decisions (critical)

You need a place where decisions get locked.

Otherwise:

  • you’ll answer the same questions repeatedly
  • Cursor will make different assumptions each time
  • your system becomes inconsistent

✅ Refined version (this is your operating model)

Here’s a tightened version of what you wrote:


🧠 1. Business Documentation & Requirements (YOU – BA)

Owns truth of the system

Includes:

  • what data exists
  • what states exist
  • what rules exist
  • business / functional / behavioural / NFRs

Format:

  • Markdown in repo (/docs)
  • Written in structured use cases (your strength)

🏗️ 2. Solution Architecture (ChatGPT)

Owns system thinking

Responsibilities:

  • challenge requirements
  • identify gaps / risks
  • simplify complexity
  • define:
    • data models
    • system boundaries
    • service structure
  • propose:
    • user stories (build chunks)
    • testing strategy
    • implementation approach

⚠️ Does NOT write final code


📜 3. Architecture Decision Log (YOU + ChatGPT)

Owns consistency

Stored in:

/docs/architecture-decisions.md

Contains:

  • key decisions (e.g. “email must be unique”)
  • chosen approaches (e.g. “postcode validated via API X”)
  • trade-offs

👉 This is the glue of the whole system


⚙️ 4. Implementation Design (YOU + Cursor)

Translates architecture → buildable tasks

You:

  • feed structured prompts
  • include constraints from decision log

Cursor:

  • proposes file structure
  • suggests implementation approach
  • may ask low-level questions

💻 5. Code Generation (Cursor)

  • writes code
  • edits files
  • refactors

✅ 6. Validation (YOU + ChatGPT)

You validate:

  • behaviour matches requirements

ChatGPT helps:

  • test scenarios
  • edge cases
  • sanity checks

🔁 The actual workflow loop (this is the magic)

BRD → (ChatGPT) Architecture → Decisions Logged →
→ (Cursor) Design → Build → Validate → Repeat

🧭 Example using your current API

What just happened (slightly wrong flow)

You:

“build helper API”

Cursor:

writes code immediately


What should happen

You:

UC-1 Helper Registration

Me:

“You haven’t defined email uniqueness, postcode validation…”

You:

decide + log it

Then Cursor:

builds correctly first time


💡 One upgrade that will change everything

When prompting Cursor, always include:

Follow decisions defined in /docs/architecture-decisions.md

That single line:

  • prevents drift
  • keeps consistency
  • makes AI behave like a real team member

🧠 Final mental model (lock this in)

You are not:

“between two AIs”

You are:

running a structured software delivery system where AIs are specialists

  • You = product + governance
  • Me = architecture + challenge
  • Cursor = engineering execution

🚀 If you want next step

We can now take:

👉 Helper Registration (UC-1/UC-2)
and do the full loop:

  • extract decisions
  • create architecture
  • define schema
  • generate code properly

That will make this workflow feel real end-to-end.