Your team describes what it wants. Agents build it on one vetted, tested, secure stack. You decide at three gates. The output is production software that survives contact with reality, not a prototype that needs rescuing.
cyan dot = one feature · hollow ◆ = you decide
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.
Vibe coding hit 84% developer adoption in 2026 and minted a whole new class of non-engineer builder. The speed was real. So was the damage: insecure, unmaintainable, untested software shipped straight to production, at scale.
Generators produce output. Nobody owns its lifetime. No one is accountable for maintainability, security, or architecture across the run, so the bill arrives later, as rescue engineering.
LUM owns the lifetime. Security, tests, architecture, and one stack, every run.
Three parts, one product. A bounded foundation, a disciplined run on top of it, and the platform that drives both. Governance is built in from line one, not bolted on.
The same shape, every project.
TypeScript, Postgres, a shared library of capabilities with contract tests, written principles. Every project starts the same and stays maintainable, so anyone, human or agent, can fix any of it. The moat compounds with every capability added.
One fixed path, every feature.
A coordinator drives explorers, designers, builders, reviewers, and a witness, each a role with its own model and effort. Idea to pull request, test-first, security-reviewed, witnessed, with you at three gates.
Shows the work, keeps the output.
Starts each step, shows it live in a rich view, and keeps what the run produces. Agents run on your own machine via the lum program; your sign-in never leaves your computer.
LUM isn't a prompt box. Every feature travels one fixed path: agents do the work, you decide at three gates, and the platform shows and keeps everything.
The agent questions you, set by set, until what to build is settled.
You confirmIt writes the spec, with research and a threat model when the work crosses a trust boundary.
You approveSplit into the fewest tickets the blockers allow, each marked risky or not.
One builder per ticket, each in its own working copy, every new behavior test seen failing first.
Each ticket reviewed against repo standards and spec until clean; fixes by a fresh fixer.
A witness starts the app and shows each behavior the way its user would.
The PR opens as a report: decisions, fixes, proof, risk. Nothing hits main without it.
You mergeDrives the run end to end, dispatching each role and holding the thread from grill to pull request.
Read-only research for another role. Returns an answer with references, and writes nothing.
Turns the settled intent into the spec, the threat model, and the tickets.
One per ticket, in its own working copy. Writes the failing test first, then makes it pass.
Reviews each ticket against repo standards and the spec until it's clean.
A fresh pair of eyes that resolves review findings the builder shouldn't grade itself on.
Starts the finished app and demonstrates each behavior exactly as its user would, before you ever look.
Twenty-five years of combined production experience, poured into one bounded stack and rules enforced by machine on every run, not by a prompt an agent could talk its way around.
TypeScript, Postgres, a shared library with contract tests. Every project the same shape, so anyone, human or agent, can fix any of it.
Each new behavior is a failing test first. Coverage floors are checked by machine, every run.
Work that crosses a trust boundary gets a threat model and a security review before it ships.
Explicit errors with hints and a layered structure, enforced by lint and boundary checks, not by memory.
Every finding becomes a rule at the cheapest level that holds it. The system improves; the instructions stay short.
Runs any model with API access: Claude, GPT, Gemini, open-weights, on your own keys. Claude Code and Codex are today's harnesses. Never captive to one vendor's pricing or roadmap.
A clinic asks for a report of patients whose import email differs from their portal email, flagged, not merged. You settle it in the grill; the spec, tickets, and tests follow; the run works overnight.
The agent's output is constrained before a line is written, and the platform itself was security-tested end to end with the Mythos model.
Agents run on your own machine via the lum program. Each run gets an isolated folder, a guard hook on every command, and sandboxed execution. Your sign-in never leaves your computer.
Every model runs on your own API keys, behind one interface. You control the spend and the data path; LUM never sits between you and the model with its own markup.
The whole platform was independently security-tested end to end with the Mythos model, led by an Anthropic Cyber Security Certified engineer.
A tier isn't a feature list, it's how thorough the run is: grill depth, review rounds, builders in parallel, and whether a witness proves the work. Model cost stays on your own keys.
For tinkering. Two weeks free.
For solo builders shipping for real.
For teams shipping production software.
For the highest-stakes work.
Levels, not configuration. Compute scales with the tier; the model cost stays on your own sign-in, so you only ever pay LUM for the orchestration.
LUM is in early access, starting with founders and teams building production software that has to survive contact with reality. Tell us about yours and we'll get you in.
Prefer we build it with you? Talk to the Studio →