Spring Boot is a Java natural fit for enterprise saas. GreatCTO auto-detects both β adds the enterprise-saas archetype overlay, wires enterprise-saas-specific gates, and runs 83 specialist agents around your existing Spring Boot workflow.
GreatCTO reads your pom.xml / build.gradle and detects spring-boot + enterprise-saas archetype from signals: imports, file structure, env vars, README hints.
Attaches the enterprise-saas archetype overlay: archetype-specific reviewer + compliance gates. Override if your specifics differ; the defaults are sensible for Spring Boot-style projects.
qa-engineer runs ./gradlew check / SpotBugs / JaCoCo coverage; security-officer scans for deserialization sinks + Spring SpEL injection; performance-engineer profiles JVM + GC patterns.
Bugs you've hit before in other Spring Boot projects (connection-pool exhaustion, ORM N+1 queries, retry storms) β the agent's Step 0 includes the prior detection order. MTTR drops 94 % on second occurrence (methodology).
$ cd my-spring-boot-app && npx great-cto init β scanning manifestsβ¦ found manifest β stack: spring-boot (Java) β archetype: enterprise-saas β overlay: applied β 83 agents ready $ /start "add enterprise-saas feature" βΈ architect drafting ARCH-enterprise-saas.mdβ¦ βΈ pm decomposing into beads tasksβ¦ β gate:plan β your approval needed
Approve β 3 senior-devs run in parallel worktrees β 5 reviewers fan out in parallel β gate:ship β deploy. One real run walked stage-by-stage: /proof.
This is the shape of what senior-dev drafts for "enterprise-saas feature" β auth first, schema validation, and the audit line the enterprise-saas reviewer requires before gate:ship opens.
// src/main/java/.../EnterpriseSaasController.java β reviewed by 5 agents
@RestController
@RequestMapping("/enterprise-saas")
class EnterpriseSaasController {
@PostMapping
@PreAuthorize("isAuthenticated()") // security-officer: auth before handler
ResponseEntity<Result> create(@Valid @RequestBody EnterpriseSaasRequest req,
Principal user) {
var result = service.handle(req, user); // qa-engineer: bean validation enforced
audit.log(user.getName(), "enterprise-saas feature", result.confidence()); // gate:enterprise-saas
return ResponseEntity.ok(result);
}
}
enterprise-saas overlay.Multi-tenant platforms with row-level-security isolation.
SSO (SAML / OIDC / SCIM) and immutable audit logs.
Tier-gated features with admin-impersonation safety.
No black-box "AI does it all" loop. GreatCTO is a deterministic state machine β 8 stages, 22 nodes, 2 human gates. Every node maps to a real agent on GitHub. Inspect the state machine β
$ npx great-cto init
Free, MIT, runs locally. Built as a Claude Code plugin β 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 β 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 β it's process governance. Here's the state machine that closes the gap.