Intents in. Working software out. Agents plan, build, review, and ship on rails, and a person approves every release. Three questions make it trustworthy. You own all of it.
cyan dot = one intent · hollow = a human decides
Every project, every agent, the health and spend of each, on one screen. It only asks you when a human is needed.
Illustrative example. Not a real dashboard, client, or results.
Any business can now generate an app in an afternoon. Almost none can trust what comes out: code nobody understands, that breaks in production, that no one can safely change.
Without a deep engineering bench, that leaves two bad options. Hire an agency that's slow, expensive, and owns your logic, or lean on AI coding tools that ship fast and hand you a maintenance liability you can't staff.
The bottleneck is no longer building software. It's trusting, owning, and maintaining it.
Writing code was never the hard part. These three are, and each is where a person, not a model, holds the line. Answer them, and cheap code becomes trustworthy software. This is what makes the platform different.
And is this the right thing?
An agent will build whatever you point it at. Deciding what deserves to exist, and why, is human judgment. It opens every loop, and the client and the team hold it together.
What can it change, and spend?
Set once per client and enforced by tools, not prompts: which agents may work, what each may change, how much time and money it may spend, and who approves a release. Rules an agent cannot step over.
Readable, fixable, and yours?
One vetted stack, a plan and tests before any code, and checks that fail work the moment it leaves the lines. So any person can pick it up and fix it, with or without an agent.
Between sessions, each agent does one job under hard limits on scope and spend. A person shapes the intent, approves the plan, approves the pull request, and promotes to production.
Given a spec, it writes the plan, the interfaces, and the tests that name the behavior, before any code.
Given a clear plan and tests that name the behavior, it delivers working code overnight.
Reviews every pull request against the principles, from a different model vendor than the one that wrote the code.
Watches production all night. Given logs and an alert, it finds the cause, drafts the fix, and hands the judgment call back to a person.
A read-only research role for another agent. Returns an answer with references, and writes nothing.
Twenty-five years of combined time building production software, poured into one bounded stack and rules enforced by tools, not prompts, so the code stays maintainable by a person.
A project never chooses its foundations; it configures them. Same shape every time, so anyone can pick it up.
The behavior is named as failing tests first. The builder only makes them pass.
Boundaries, naming, coverage, and a required review fail work the moment it leaves the lines, a gate, not a suggestion.
Every finding becomes a rule at the cheapest level that holds it. The system improves; the instructions stay short.
Agents work on their own branch, never on main, and can never widen their own budget or authority.
You decide which model runs each step: Anthropic, OpenAI, Google, or whoever is best next quarter. Roles name a job, not a vendor, so you can swap per step, per client, anytime.
A clinic asks for a report of patients whose import email differs from their portal email, flagged, not merged. You shape the intent; the plan and tests follow; the builder works overnight.
LUM is in early access for software teams and engineering leaders who want agent speed without the unmaintainable mess. Tell us about your team and we'll get you in.
Prefer we build it with you? Talk to the Studio →