The enterprise engineering org
You have 50+ engineers, compliance constraints (FedRAMP, HIPAA, FISMA), and a CTO who needs AI-assisted dev that does not break an audit. You need a methodology and a paper trail, not a Discord plugin.
JarviSWARM framework: open-sourcing soon · Curriculum: late 2026
From vibe-coded MVP to production at scale.
Vibe coding ships fast. Vibe coding also produces tech debt. Everyone knows it. Vibe Engineering is the bridge: AI-assisted development for teams that have to survive a code review, a production deploy, and a Tuesday-morning incident.
Powered by JarviSWARM, our open-source AI engineering framework. The methodology and toolkit we're using to ship LSA's own products, including under FedRAMP, HIPAA, and FISMA constraints.
Open-source frameworkCompliance-tested (FedRAMP, HIPAA, FISMA)Multi-provider, no lock-in
Lived experience, not theory
JarvisIM refactor
AI estimated 5 months. JarviSWARM rails took it from estimate to done in 9 days.
Compliance-tested
Shipped under FedRAMP, HIPAA, and FISMA constraints, long before vibe coding existed.
The curriculum is built directly on this work.
The framework behind it · Open source
Meet JarviSWARM.
Most agent kits give you commands. JarviSWARM gives you a methodology that the commands serve.
We used it to refactor our own production codebase in 9 days when the AI estimated 5 months. It's the bridge from “I shipped a vibe-coded MVP” to “my team ships at enterprise scale,” and it's the foundation under every Vibe Engineering engagement.
Request repo accessRepo opens to early access first · public soon after
Methodology, not just a toolkit
A /new-work → /implement → /close-ticket lifecycle with Ring 0 → Ring 3 ticket maturity and /feature-reconcile blast-radius updates.
Plain English for PMs
Product managers and product owners file work in plain English. The framework matures it through rings while engineering brings it to ready.
Multi-provider by default
Claude, OpenAI, Gemini, GLM. Optimize subscription credit usage across all of them. Pick the right tool, agent, and model per job.
On-prem-ready
Keep models like Gemma on-prem for speed, cost, and privacy. Claude ↔ OpenCode bridge built in. No provider lock-in baked into the foundation.
Compliance-aware
Built by engineers who have shipped under FedRAMP, HIPAA, and FISMA constraints. The audit trail is a first-class concept, not a bolt-on.
Lean, feedback-driven testing
TDD → live UAT → e2e regression promotion path. Retro files turn every fix into a learning the next agent inherits.
Who it's for
Built for the teams that have to make Vibe coding safe to ship.
Vibe Engineering is built for the people whose work has to survive a code review, a production deploy, and a Tuesday-morning incident, whether that's a solo product-owner-turned-engineer, a small team finding its rhythm, or a 50-engineer org with a compliance audit on the calendar. If you're still solo and getting started, the Vibe Coding tier is a great place to start.
The small eng team lead
You run a 3–8 person team. Your developers are using AI tools on their own and shipping things that are hard to maintain together. You want a shared playbook and a consistent baseline.
The product owner gone full-stack
You scoped, tested, and shipped a vibe-coded MVP yourself. Now you want to bring real engineering rigor without losing the speed, and stay in the loop without becoming the bottleneck.
The engineer adopting AI tools
You have a career and you are evaluating where AI-assisted dev fits in your stack. You want patterns from people who have shipped production systems, not a YouTube rabbit hole.
The scrappy CTO or fractional lead
You are running a tiny team that needs to ship like a much bigger one. AI is your leverage. You want patterns, not just vibes. And a framework you can hand to a new hire on day one.
What it'll cover
Four pillars. Built on JarviSWARM, pulled from real engineering work.
The curriculum is built directly out of what we've had to figure out on LSA's own products, including the dead ends. Every pillar maps to JarviSWARM capabilities you'll be able to pull off the open-source repo.
Pillar 01
Tests that AI can actually run
Red-test-first TDD with AI-generated implementations. Custom UAT harnesses where your QA agent puts the work on a screen so you can watch it run. A real promotion path: lean TDD → live UAT → locked-in end-to-end regression.
TDD with AIUAT harnessAgent-driven E2EPlaywright
Pillar 02
The /new-work → /implement → /close-ticket lifecycle
Plain-English commands that PMs and POs can actually use. Tickets mature through Ring 0 → Ring 3, with a /feature-reconcile that ripples updates to every related ticket the moment one closes. Jira stays current; engineers do not have to touch it unless they want to.
Slash-command lifecycleRing 0–3 maturityPM in plain English/feature-reconcile
Pillar 03
RAG, embeddings, and the hard parts
Multi-modal embeddings. PDF extraction (image-based vs text-based). When local embedding wins. Performance considerations. The unsexy work that makes AI features feel fast instead of broken.
Multi-modal embeddingsPDF extractionLocal vector DBs
Pillar 04
Multi-provider, on-prem-ready, no vendor lock-in
Optimize credit usage across Claude, OpenAI, Gemini, and GLM. Keep models like Gemma on-prem for speed, cost, and privacy. Pick the right IDE, agent swarm, and provider per job, without rewriting your foundation when the next great model lands.
Claude · OpenAI · Gemini · GLMOn-prem (Gemma)No lock-inClaude ↔ OpenCode bridge
Why us
Our own portfolio walked this exact path. JarviSWARM is what we built to make it survivable.
Every product LSA Digital ships started as a vibe-coded MVP and got re-engineered into something that runs in production, some of it under FedRAMP, HIPAA, and FISMA constraints. We don't teach this in theory. We lived it on each of these.
JarvisIM · the 9-day refactor
AI estimated this refactor would take until September. The JarviSWARM rails took it from estimate to done in 9 days. A 20-story feature (HASS-381) that rebuilt a vibe-coded MVP into a multi-user platform with real auth and durable embeddings. The curriculum is built directly on this work.
See the journeySquawk · vibe-coded to production
Started as a Friday-night content tool. Today it powers the LSA Digital editorial workflow with automated ingestion and a real publishing contract. Same arc your team will walk, without the cleanup tax.
See the journeyPopHealthMap · compliance-grade AI dev
Government and healthcare-grade compliance constraints (FedRAMP, HIPAA, FISMA), AI-assisted dev. We have shipped this kind of system since long before vibe coding existed, and brought those patterns into JarviSWARM.
See the journeyEarly access list
Get the framework and the curriculum, first.
One list, two things. We'll send you JarviSWARM repo access ahead of the public release, and the full Vibe Engineering curriculum the day it's ready, plus early-access pricing for our first wave of students. No spam, no drip sequence, just the launches.
Not on a team yet, or just getting started with AI tools?
Start with Vibe Coding