The Product Manager vs. Software Architect Divide
The rise of tools like ChatPRD and standard ChatGPT templates has made generating product requirement documents fast. But there is a silent crisis happening across engineering teams: PRDs written for human Product Managers are poison for autonomous AI coding agents.
When a PM reads a requirement like "The system should handle payments reliably and calculate usage accurately," they nod in agreement. But when you feed that sentence into Cursor, Claude Code, or Devin, the coding agent is forced to guess:
- What happens when two webhook events arrive in the same millisecond?
- Are currencies represented as floating-point numbers or integer cents?
- What is the cryptographic TTL for session tokens?
- Does the API fail-open with an alert or reject requests with HTTP 429 when spending limits are reached?
Because the PM PRD omits these technical boundaries, the AI agent hallucinates its own answers. It invents database columns that do not exist, introduces race conditions, and writes code that technically compiles but causes catastrophic bugs under production traffic.
The Anatomy of a Production Spec Bundle
In Spec-Driven Development (SDD), specifications are not single monolithic prose documents. Instead, they are decomposed into four atomic, tightly-coupled markdown files engineered for machine consumption:
| File | Core Purpose | What It Solves For AI Agents |
|---|---|---|
| constitution.md | Architectural invariants, technology contracts, decision precedence | Stops architectural drift; prohibits anti-patterns (no raw SQL, no modifying committed migrations). |
| requirements.md | Functional & non-functional requirements in strict EARS+ syntax | Replaces vague "should" statements with deterministic WHEN/IF/WHILE acceptance criteria. |
| solution.md | Postgres schemas, API contracts, Mermaid sequence diagrams | Provides exact schema constraints (UUIDs, unique indexes, foreign keys) so agents do not guess data models. |
| tasks.md | Granular, sequential implementation steps with verification commands | Breaks implementation into context-window-friendly chunks with explicit test criteria. |
The Socratic Interview: Why Questions Matter More Than Answers
When developers start a project, they suffer from the blank page problem. They know what they want to build at a high level, but they haven't thought through the edge cases: concurrency, idempotency, rate limiting, and failure boundaries.
ChatPRD and standard ChatGPT prompts simply repeat the user's prompt back to them in a more verbose format. MySpec acts as an AI Senior Architect. Before generating a single line of specification, it conducts an automated Socratic interview:
- What is your offline capability requirement? Should receipts queue locally if network connectivity drops?
- When OCR confidence drops below 80%, does the system flag the record for human verification or fail the extraction?
- How do you handle multi-currency receipt conversions when the historical exchange rate is unavailable?
- What is your data retention policy for raw receipt images versus extracted transactional metadata?
By surfacing these edge cases before code is generated, developers eliminate 80% of downstream rework.
How to Feed Spec Bundles into Cursor and Claude Code
Once MySpec generates your 4-file bundle, you export it directly into your project repository. The standard convention is placing specifications under a committed specs/ directory (the MySpec MCP server mirrors downloads into a gitignored .specs/ working copy):
my-project/
├── .cursorrules
├── CLAUDE.md
└── specs/
└── billing-module/
├── constitution.md
├── requirements.md
├── solution.md
└── tasks.mdWhen prompting Cursor or Claude Code, reference the bundle directly:
"Implement Task 1 from specs/billing-module/tasks.md strictly according to the database schemas in solution.md and the invariant rules in constitution.md."
Frequently Asked Questions
Why shouldn't I just use a custom ChatGPT prompt for my PRDs?
Standard ChatGPT prompts produce monolithic, narrative text. They lack formal grammar constraints like EARS, don't generate Mermaid diagrams natively, and fail to split requirements into actionable task increments. MySpec drives the model with prompts, templates and reviewer passes built specifically around Spec-Driven Development.
Is MySpec free to use?
Yes. The Free plan needs no credit card: it covers 20 projects and 100 spec files with a monthly AI architect allowance, and you can export the full bundle as a ZIP at any time. Pro and Team multiply that AI allowance 5× and 10× per seat.
Can I edit specifications conversationally after they are generated?
Yes. MySpec features "Vibe Specify'ing" mode, allowing you to refine specifications conversationally (e.g., "Add rate limiting to all endpoints" or "Break down the auth tasks into smaller pieces"). The AI updates the underlying markdown files and maintains consistency across the bundle.
Stop Guessing. Start Specifying.
Transform your next feature idea into an airtight 4-file spec bundle in 2 minutes. Free during Open Beta.