For humans. For agents. By design.
McMtn Labs builds modern software for the AI era. A small expert team works alongside AI assistants to ship software that's beautifully designed for the people who use it, and reliable for the AI tools that increasingly do too. Fast, careful, no corners cut.
Two systems.
One way of building.
Every project runs through two systems we built ourselves. Basecamp is our quality playbook: the rules every AI assistant follows before changing anything. Summit is our project hub, the tool we use to plan, build, and ship your project from the first idea to the live app.
Basecamp
Basecamp is our quality playbook: the rulebook that makes building software with AI safe and reliable every single time. It's the foundation every project starts from, no exceptions.
Foundations are the big, hard-to-change decisions we make at the start so nothing important gets re-litigated later. Patterns are specific ways AI-built software can go wrong, each paired with a rule and an automatic check that prevents it. Decision Records save the reasoning behind every major choice, so we never lose track of why something is the way it is. Skills are reusable AI checklists for the most important work: reviewing code, checking security, testing accessibility, making sure AI features still work after updates, and improving the rulebook itself over time.
Every rule has an automatic check that runs before any change goes live. These aren't guidelines we hope our AI assistants follow. They're checkpoints work can't get past without meeting. Every single one, automatically, every time.
Summit
Summit is where ideas become finished software. It's the single tool that covers everything from the first conversation about your idea, through the design, planning, and building, all the way to your software running in the real world.
Most tools handle one slice of that journey. Summit handles the whole thing. Capturing ideas. Designing with AI. Planning the work. Coordinating the AI assistants who do the building. And watching over everything once it ships: checking reliability, security, and performance from the very first day through every day after.
Summit is a Mac app we built ourselves, with direct, real-time access to files and tools on the computer in ways web-only tools can't match. And because we built Summit using Basecamp's own rules, every part of our playbook has been proven in real use. Basecamp wasn't built in theory. It was tested by building Summit itself.
From first idea
to finished software.
Every project moves through five stages. At each one, our small expert team and our AI assistants work side by side (humans setting direction and making the important calls, AI doing the structured work), all guided by Basecamp's rules from the very first conversation.
The right ratio isn't more engineers.
It's a small, focused expert team setting direction and protecting quality, working with specialized AI assistants that do most of the building. Every app we ship is designed so it works smoothly for the people who use it, and reliably for the AI tools that increasingly use it too.
Big decisions. Not typing.
McMtn Labs was founded on the idea that what really matters isn't who's at the keyboard. It's who's designing the system and making sure quality holds. Our small expert team sets product direction, designs the rules, and makes the calls that need human judgment.
The result is a firm that builds at the speed of AI without sacrificing the kind of quality you'd expect from a serious software company. Not by writing more code by hand, but by designing a better system for the AI that does.
- Product direction and the big design decisions
- Designing the rules our AI assistants follow
- Approving any work that touches security or could break things
- Reviewing what we learn from each project and turning it into new rules
- Client relationships and what gets built next
Specialists, always working.
Making AI work reliably is harder than it looks.
Getting AI to write some code is easy. Getting AI-built software that's reliable, affordable, and safe enough to put in front of real people is a different problem entirely. We've built our platform for the harder problem: five areas, each carefully tuned to make AI work in the real world.
AI works only as well as what it knows.
AI gets things wrong when it doesn't have the right information at the right time. We treat what AI knows as a careful engineering problem: keeping track of what's happened across work sessions, giving each AI assistant only what it needs for the task at hand, and writing instructions in ways that get accurate, predictable answers instead of confident-sounding guesses.
The instructions we give AI are tracked and reviewed like real code, never made up on the spot. When something changes, the change gets tested before it ever touches your project.
AI gets expensive fast, unless you're careful.
Using AI heavily costs real money. We control cost by trimming what AI needs to read for each task, asking for answers in predictable formats so we don't have to retry, and remembering past answers so we never pay twice for the same question.
But the biggest lever of all is matching the AI to the task. Heavy reasoning AI is expensive: fine for genuinely complex problems, but wildly overkill (and wasteful) for changing a button color. We pick the cheapest, fastest AI that can do the job well, and save the heavy hitters for the problems that actually need them.
The result: faster work, lower cost, no compromise on quality.
Multiple AI assistants, working together.
When several AI assistants work on the same project, things can go sideways fast: they duplicate effort, disagree with each other, or make permanent changes without checking first. Our coordination system gives each assistant a clear role, a clear way to hand work off, and a clear way to escalate decisions to a human when something matters enough.
Speed and oversight aren't in conflict here. The AI moves fast on what we trust it to do; humans stay in the loop on what really matters.
Long AI tasks that don't lose their place.
Long-running AI tasks usually break the moment a computer sleeps, a step fails, or an app closes. Our reliability system makes sure every step happens exactly once, and if anything goes wrong, the work picks back up exactly where it left off.
Work doesn't disappear. Long tasks don't restart from zero. Crash, sleep, or reboot: the AI picks up right where it was.
Always using the best AI available.
The AI world moves fast. We built our system so we can use whichever AI is best for a given job (Claude, ChatGPT, Gemini, or whatever ships next) without rewriting anything. Each task uses the right AI for that task, and we can swap any time we need to.
When a better AI comes along, your software gets it. We stay at the leading edge by design, not by accident.
Every project makes the
next one better.
Every project teaches us something new: new mistakes to prevent, new edge cases to handle, new ideas worth standardizing. We capture each lesson, review it, and add it to the rulebook. Our system gets smarter every time we use it. The advantage grows with every project we ship.
Fast, polished, safe, and for everyone — by design.
Every rule we follow is automatically checked. Every important decision is recorded. Every common mistake has a built-in safety net. Here's what that buys you.
Fast.
Our AI assistants do the heavy lifting; our rulebook keeps everything on the rails. We ship in days what traditional teams ship in weeks: new features, full redesigns, theme variants, even brand-new apps.
Polished.
Beautiful designs from day one. Data checked at every step. Predictable, reliable behavior throughout. AI features tested before every release. The mistakes that haunt other AI-built apps are caught by design, not by hoping someone's careful.
Safe.
No silent data loss. No surprise AI bills. No personal information ending up where it shouldn't. Logins, payments, and anything that could break things must pass through a human before going live. Built in, not bolted on.
For everyone.
Strong accessibility standards as the starting floor, not the finish line. Everything works with a keyboard. Everything works with screen readers. Colors meet contrast requirements. Motion respects user preferences. Built in from the first commit. Never patched on at launch.
Let's talk.
Curious about what we're building? Have a project that needs to be done fast, but done right? Get in touch.
nmcginn@mcmtnlabs.com