AI native agency for product design and development

An AI-native agency builds products with AI integrated into every step — not bolted on as marketing. At Managed Code, every senior engineer and designer ships with real AI tooling on their workstation, and our internal quality framework verifies AI-generated code before it touches production. The result: a senior team of three delivers what a traditional crew of eight used to, in a fraction of the time.

Three differences matter. First, we staff only seniors — no juniors billed at senior rates, no training overhead on your project. Second, every engineer ships with real AI tooling, not just ChatGPT in a browser tab — which is why a team of three produces what a traditional team of eight would. Third, we sell fixed outcomes against fixed time blocks, not open-ended hours. You always know what's shipping and when.

A Minimum Sellable Product — design, code, and production deployment — takes four to six weeks with our AI Product Team. Sprints with the AI Dev Team ship working code every Friday. Design work runs in two-week blocks. The pace comes from three things: senior-only staffing, AI tooling on every workstation, and one team running design, development, and QA in the same repo. No handoffs, no waiting.

Every engineer and designer has a stack of paid AI tools — coding assistants, design generators, code review agents, and more. AI handles the routine work (boilerplate, variants, test scaffolding, documentation) so senior people focus on architecture, user experience, and the decisions that actually matter. Then our internal quality framework reviews every AI-generated piece against architecture rules and test coverage before it ships. AI doesn't replace senior judgment — it multiplies it.

No. Many of our clients are non-technical founders who came to us after no-code or vibe-coded experiments hit a wall. You describe the what — the product, the users, the outcome — and we own the how: architecture, design, code, testing, deployment. We translate between business goals and technical decisions every day. You don't need to know the difference between .NET and Node to get a great product.

Yes — this is one of our most common starting points. We assess what you have, decide what's worth keeping, and rebuild the rest properly. That usually starts with a short Discovery to map the product, user journeys, and technical risks. Then the AI Product Team takes the validated parts into a production-grade build. You keep the early momentum; we replace the cracked foundation.

Yes. Our team has shipped products under HIPAA, GDPR, and financial compliance requirements. Compliance gets designed in from day one — not bolted on at audit time. The AI Product Team includes a Project Manager and QA Engineer because regulated work needs documentation, test evidence, and architecture decisions that hold up under review.

Both. We can run as the entire product team for founders without engineering, or plug into existing teams as a senior AI-native squad. We're used to shared repos, shared standards, and shared rituals. The one thing we won't do is be the cheap junior crew you offload tickets to — that's not the value we deliver.

Yes. We build custom AI agents that run in production, not just demos: workflow automation, knowledge retrieval (RAG), and decision-support agents. Each one is scoped around your data, business rules, integrations, and escalation paths, then built by senior engineers with tests and review before anything ships. See our AI agent development.