NestJS is a TypeScript natural fit for fintech. GreatCTO auto-detects both — adds the fintech archetype overlay, wires fintech-specific gates, and runs 83 specialist agents around your existing NestJS workflow.
GreatCTO reads your package.json and detects nestjs + fintech archetype from signals: imports, file structure, env vars, README hints.
Attaches the fintech archetype overlay: PCI-DSS scope detection, SOX ITGC gates, KYC / AML hooks, idempotency review. Override if your specifics differ; the defaults are sensible for NestJS-style projects.
qa-engineer runs tsc --strict / eslint / vitest --coverage; security-officer checks for prototype pollution + XSS sinks; performance-engineer reviews bundle size + cold-start times.
Bugs you've hit before in other NestJS projects (connection-pool exhaustion, ORM N+1 queries, retry storms) — the agent's Step 0 includes the prior detection order. MTTR drops 94 % on second occurrence (methodology).
$ cd my-nestjs-app && npx great-cto init ✓ scanning manifests… found package.json ✓ stack: nestjs (TypeScript) ✓ archetype: fintech ✓ overlay: applied ✓ 83 agents ready $ /start "add Stripe subscription endpoint" ▸ architect drafting ARCH-fintech.md… ▸ pm decomposing into beads tasks… ⚐ gate:plan — your approval needed
Approve → 3 senior-devs run in parallel worktrees → 5 reviewers fan out in parallel → gate:ship → deploy. One real run walked stage-by-stage: /proof.
This is the shape of what senior-dev drafts for "Stripe subscription endpoint" — auth first, schema validation, and the audit line the fintech reviewer requires before gate:ship opens.
// src/fintech/fintech.controller.ts — reviewed by 5 agents
@Controller('fintech')
export class FintechController {
@Post()
@UseGuards(AuthGuard) // security-officer: auth before handler
async create(@Body() dto: CreateFintechDto, @User() user) {
const result = await this.service.handle(dto, user); // qa: class-validator enforced
await this.audit.log(user.id, 'Stripe subscription endpoint', result.confidence); // gate:fintech
return result;
}
}fintech overlay.Payment and ledger services with idempotency proofs.
KYC / AML onboarding flows with sanctions screening.
Lending decisions with ECOA fair-lending evidence.
No black-box "AI does it all" loop. GreatCTO is a deterministic state machine — 8 stages, 22 nodes, 2 human gates. Every node maps to a real agent on GitHub. Inspect the state machine →
$ npx great-cto init
Free, MIT, runs locally. Built as a Claude Code plugin — install with one command.
Eight stages, two human gates, four memory layers. Why this exact shape, and what I tried that didn't work.
One run, one feature, from prompt to merged PR. Time, cost, and gate-by-gate breakdown — no marketing math.
Regex vs LLM-based archetype detection, the false-positive count, and why I keep rejecting the obvious fix.
The bottleneck in agentic SDLC isn't model quality — it's process governance. Here's the state machine that closes the gap.