Opinionated scaffolding
Ready-to-go templates with tests, CI, and pinned versions. Speed, consistency, and lower risk across your application portfolio instead of a pile of one-off apps on mismatched stacks.
Scarlet Develop · Add-on for Lead & Accelerate
We make your engineers fluent in AI — and keep them shipping.
Your engineers are already using AI to write code. The question isn't whether — it's whether they're shipping production-grade work with it, or generating tech debt at unprecedented speed. Scarlet Develop is the add-on we offer to Scarlet Lead and Accelerate clients entering app development as a real line, not a side project.
$3,000–$8,000/mo · price reflects teaching lift, not code volume
How we deliver
We arrive opinionated. We bring recommended tech stacks with ready-to-go scaffolding — a React + Supabase template that spins up with one command, carrying tests, integration tests, Playwright tests, pinned library versions, and a test database already in place. For autonomous agents, a LangGraph template ready to extend.
We hand you the scaffolding, walk you through it, coach through first iterations, then shift to code review and methodology. Your team builds. We make sure they build well.
Ready-to-go templates with tests, CI, and pinned versions. Speed, consistency, and lower risk across your application portfolio instead of a pile of one-off apps on mismatched stacks.
Custom skills, slash commands, MCP servers, plugins — including workflows that embody entire end-to-end development lifecycles. Some generic, some customized for your MSP type.
Our recommendation carries weight — we bring experience you don't have. But the decision is yours. If you go your own way, we're honest about the tradeoff: 2–4× slower, more risk.
The teaching progression
The same sequencing we use across every Scarlet engagement. Scarlet Develop goes deep on layers three and four — but nobody gets there without the foundation.
Prompting best practices, context engineering, generative AI bias mitigation, and AI risk awareness. The base nobody skips.
Skills, MCP servers, plugins, and agent tool use. The building blocks before the buildings.
Right-sizing judgment — matching the solution to the problem. A custom application is a normal and correct answer for many problems, not a last resort. The skill we build is choosing well, then building well.
CI/CD, testing strategy, secure and maintainable code generation, deployment, monitoring, triage, and database design. A large part of this work is teaching engineering itself, not only AI. The human discipline is the hard part, and AI does not remove it.
What we cover
AI coding tools are getting better every month. What doesn't change is what production code requires: tests, reviews, security, shipping discipline. We help teams build the practice that makes the tools earn their seats.
Cursor, Copilot, Claude Code, agentic editors — picked and configured for the work your team actually ships. Plus custom skills, slash commands, and MCP servers embedded in the workflow itself.
How to prompt, scope, scaffold, refactor, and unblock with AI. The rituals that separate "engineer with leverage" from "person generating tech debt at unprecedented speed."
A different muscle than reviewing human-written code. We help your engineers spot the failure modes AI tools hide and the gaps that pass tests but break in production.
Tests, CI, staged rollout, observability. The unsexy infrastructure that turns AI-assisted velocity into AI-assisted reliability instead of AI-assisted incidents.
Where AI tools most commonly cut corners. Auth flows, secrets handling, dependency hygiene, and the prompt-injection surface most teams haven’t thought about yet.
Pairing, knowledge sharing, AI literacy across seniority levels. And the judgment to know when a reusable prompt, skill, or MCP server solves the problem better than a custom application.
The long game
Early on, the human stays closely in the loop. Over time we help your team build increasingly autonomous AI solutions — where people orchestrate by setting clear intentions and verifying outcomes, while AI agents handle coding, testing, deployment, and PR generation. That progression is where the largest gains in speed, consistency, and capacity come from.
The progression
1 · Foundation
AI literacy, tooling, scaffolding, and engineering discipline. Ship cleanly with human review on every change.
2 · Repeatable
Workflows codified in skills and templates. AI handles boilerplate, humans handle judgment calls. Velocity compounds.
3 · Autonomous
AI agents code, test, and deploy. People set intentions and verify outcomes. Trust earned incrementally, not declared.
Availability
Every MSP that comes to us — even one wanting “just help our devs use AI” — needs the foundation first: leadership alignment, AI fluency baseline, and an adoption strategy. That's why Develop requires an active Scarlet Lead or Accelerate engagement.
Let's make sure the answer is yes.