Custom software, carried from requirements to production deploy by a multi-agent AI pipeline
Architected, built, independently reviewed, and gated like a senior engineering org would gate it. Most AI-assisted dev is one model writing code that the same model then reviews — My Jian Developer is different: typed agent contracts across every phase, a second, independent model bound to catch what the first missed, and a deploy gate that cannot be talked past.
One pipeline, eight gated phases
Every build moves through the same gated sequence. Requirements freeze before architecture starts; architecture freezes before contracts are cut; contracts freeze before a line of application code is written.
Existing app, not a new build? Phase U handles it — a reported issue is reproduce-gated first, localized file→symbol→line with a cited rationale, then run through the same F–G pipeline. High-risk or contract-breaking changes pause for your explicit approval.
Mechanisms with runtime enforcement, not process slides
Each one is a specific, real thing the pipeline does on every single build — not a policy someone is trusted to follow.
Adversarial Cross-Model Review
After self-validation, an independent model family does a second, binding traceability pass on requirements and architecture — a genuinely different reviewer, not the same model re-reading its own work. Proven on a real run: it caught a missing platform tenancy tier, a wrong-tier compliance binding, and a domain model directly contradicting the locked spec — gaps routine self-review missed entirely.
Hard Quality Gates
Full test suite, Semgrep static analysis (2,000+ rules), npm audit and .NET vulnerability checks all run before deploy is even considered. A failed gate routes to remediation, capped at 3 loops before the pipeline halts and escalates to a human. The deploy step carries a hard runtime assertion — it cannot execute unless the gate result is a verified pass.
Rollback-First Deploy
Rollback logic has to exist before deploy logic is even allowed to run — a hard design rule, not an afterthought written after an incident. Every deploy step is logged; a failure triggers an immediate, automatic rollback and alert.
Compounding Memory
Every session writes what it learned — patterns, mistakes, fixes — back to a persistent, git-tracked memory. The next build on the same or a different project starts smarter, instead of re-discovering the same issue from scratch.
Real builds, not simulations
My365 — multi-tenant M365 backup & management platform
95 API routes, 34 handlers, 19 screens — a full tenant/job/RBAC/billing admin console, built and shipped in two weeks flat. A comparable traditional build runs an estimated ~19 weeks.
ChatAI-v8 — enterprise multi-tenant AI chat platform
489 API operations across 79 controllers, 371 screens — a live production SaaS platform with seven LLM providers wired in. A comparable traditional build runs an estimated ~19 months.
Methodology: timelines above are real, git-verified build windows on Technijian's own product suite. Traditional-equivalent figures apply standard industry effort benchmarks (hours per screen, per API operation, plus typical PM/QA/architecture overhead) at general U.S. market rates for the same delivered scope.
Scoped & quoted per project — not a fixed price list
Every project is different — different integrations, different compliance domains, different starting point (greenfield vs. an application already live). So we don't quote off a menu; we quote off your actual requirements pack, the same one the pipeline itself will build from.
Discovery
A scoping call to understand the application, integrations, and compliance domains in play.
Requirements Draft
Phase A runs for real — an actual intake pack, not a sales estimate.
Scoped Proposal
Architecture-informed estimate against the real requirements — fixed scope, before any commitment.
Gated Delivery
Work begins only once the proposal is signed — then the full eight-phase pipeline runs.
Want a different engagement model instead?
If your project fits better as a fixed-scope build, time & materials, staff augmentation, or a managed application-services retainer — without the full gated pipeline — see My Dev.
Questions we get asked about My Jian Developer
How is My Jian Developer different from My Dev?
My Dev offers flexible traditional engagement models — Fixed-Scope, Time & Materials, Staff Augmentation, Managed Application Services — using AI-assisted tooling to move faster within those models. My Jian Developer is a distinct, more structural offering: the same underlying multi-agent pipeline (SDLC v7.0) delivered as its own product, with typed contracts between every phase, a binding independent-model review, and a hard deploy gate baked into the process itself, not just faster typing.
Why is there no published pricing for My Jian Developer?
A subscription tier can honestly price a fixed monitoring cadence; it can't honestly price a custom build, because the real investment driver is the application itself — its integrations, its compliance surface, and whether it's a new build or a live system already carrying real risk. Every quote is produced from a real Phase A requirements draft, not a menu.
What actually stops a broken build from shipping?
A runtime assertion on the deploy step itself — it cannot execute unless the quality gate (full test suite, Semgrep static analysis across 2,000+ rules, npm audit, .NET vulnerability checks) returns a verified pass. A failed gate routes to remediation, capped at 3 loops before the pipeline halts and pages a human, rather than looping forever or shipping anyway.
What's an independent model review, and does it actually matter?
After a model self-validates its own requirements and architecture work, a genuinely different model family does a second, binding traceability pass — not the same model re-reading its own output. Tested side by side on a real run, only the independent pass caught a missing platform tenancy tier, a wrong-tier compliance binding, and a domain model directly contradicting the locked spec — gaps routine self-review missed entirely.
Does this only work for new applications, or can it fix something already live?
Both. Phase U handles existing applications: a reported issue is triaged and must be confirmed reproducible before any automatic fix runs, then localized file→symbol→line with a cited rationale before a frozen change spec is written and run through the same build/gate/deploy pipeline. High-risk or contract-breaking changes always pause for explicit human approval.
Have something that needs building, or already needs fixing?
Start with a discovery call — scoped in days, on the same engine that runs Technijian's own product suite.