AI SDLC · 2 min read
What an AI SDLC actually looks like
Adding a coding assistant to an old process is not an AI SDLC. Here is the lifecycle we run instead, stage by stage.
Founder-led product studioAI SDLC / Harness engineering
Enterprise platforms, built at AI speed. Proven on every change.
A senior engineer directs AI virtual engineers through a disciplined AI SDLC to build and run platforms for commerce, logistics, SaaS infrastructure and data — with a regression harness around every commit.
- context · conventions loaded✓ passed
- unit · contract · e2e (5,612)✓ passed
- secrets · dependencies · SAST✓ passed
- human review · design & riskin review
- products
- 9
- accelerators
- 17
- automated tests
- 5.6k+
- products in the portfolio
- 9
- reusable accelerators
- 17
- features mapped across the portfolio
- 342
- automated tests across two platforms
- 5.6k+
01 — Engagements
Take a platform. Or have us build yours.
License a platform
Start from a tested product, configure it for your business and launch on your brand — on your cloud or ours, extended with the accelerators you need.
Pricing: [YOUR PRICING MODEL]
See the productsBuild with our AI engineering team
A principal engineer leads, AI virtual engineers build and the harness proves it — on your codebase or a new one.
- Pilot — one scoped outcome in [X] weeks
- Build — a product team on a fixed roadmap
- Run — operate, monitor and extend after launch
Index of platforms
02 — ProductsSix platforms, built and tested, ready to run on your brand.
- Commerce 360Conversational and omnichannel commerce — storefront, chat, voice ordering, an order desk and agent-ready APIs for buyers’ AI.
- BackstockInventory, purchasing and store P&L for multi-location operators — one live view of what’s on the shelf and what it earns.
- ShipTrackShipment tracking, returns and fraud rules for brands and 3PLs. A HIPAA edition for healthcare shipping is on the roadmap.
- ShipyardProvision, bill and operate multi-tenant SaaS on Google Cloud — tenant lifecycle, Stripe Connect billing and edge routing.
- InsightProAsk your data in plain language. Natural-language analytics, dashboards and voice-of-customer in one workspace.
- FeatureIQFeature flags and remote config with per-tenant rollouts. Pairs with Monarch Experiments for A/B testing.
NeoMonarch Labs TradePro (live beta) · Financials (concept)
The model is the engine. The harness is the engineering.
03 — MethodFrame
Founder and client agree the outcome, the constraints and what “done” means.
Specify
Requirements become machine-readable specs and acceptance tests.
Build
AI virtual engineers work in parallel lanes, reviewed by a senior engineer.
Prove
Regression harness, security scans and performance checks gate each change.
Ship & run
Deploy to your cloud with monitoring, then keep improving it.
“I started NeoMonarch to prove that one experienced engineer, directing AI with real discipline, can build what used to take a department — and show the receipts.”
From the build log
All 8 articles
Harness engineering · 2 min read
Harness engineering: the discipline that makes AI code shippable
The model is the engine. The harness — context, tools, guardrails and checks — decides whether it gets you anywhere.
Harness engineering · 2 min read
Why every AI-written commit needs a regression harness
AI makes code cheap. It does not make correctness cheap. A regression harness is how you keep the second from slipping while you enjoy the first.
04 — Start a build
Have something to build?
Tell us what you’re working on. You’ll hear back from the founder directly — not a sales team.
[hello@neomonarch.com]