Ship AI products with studio ownership
Slides do not launch products. Design, engineering, and launch need to sit with the same team on the same schedule.
Projects run on milestones rather than an open-ended discovery phase. Every phase ends with something you can click, test, or release.
If that sounds like your situation, Arcode is set up for founders searching for an AI product studio. Arcode is an AI product studio covering agents, MCP, RAG, and full-stack delivery for teams that need working software.
What you get
- AI-native product builds
- MCP and agent systems
- Web and mobile surfaces
- Launch-ready architecture
- One studio accountable for the result
- Design and engineering on the same schedule
- Support available after launch
How engagement works
As your AI product studio, we run a shared backlog, design reviews, and engineering sprints, and you keep one point of contact throughout.
- 01
Discover
Goals, constraints, data sources, and success metrics, all settled before we touch architecture or prompts. On AI product development projects we favour practical architecture over trendy defaults.
- 02
Design
System design, AI/tool boundaries, interface direction, and interaction prototypes. The work for teams in San Francisco stays tied to the outcome you asked for.
- 03
Build
Modern stack, clean architecture, evaluated AI behavior, and iterative demos you can react to. You see progress on the critical path every week.
- 04
Launch
Ship, monitor, harden, and keep improving models, tools, and product after go-live. Nothing here waits on a handover between separate teams.
How we build it, and why
The stack is chosen per project, not applied from a template. For AI product studio work these are the defaults, and the reason each one is on the list.
- OpenAI
- a second model provider, so a single vendor's outage or price change is not your problem
- Claude
- long-context reasoning and reliable tool calling for agent work
- MCP
- the Model Context Protocol, so your tools plug into Claude, Cursor, and other agent clients without a custom adapter for each
- Next.js
- server rendering and static generation in one framework, so marketing pages stay fast and app routes stay dynamic
- NestJS
- structure and dependency injection on the backend, which keeps a growing API from turning into a pile of route handlers
- React Native
- one codebase for iOS and Android, which halves the surface area you maintain after launch
What the first weeks look like
- Week 1
Scope and architecture
Users, data, integrations, and constraints, ending in a written plan for the AI product development that you approve before anyone opens an editor.
- Weeks 2-3
Design the critical path
The screens that carry the product, prototyped and clickable. Design and engineering review together, so nothing gets drawn that cannot ship.
- Weeks 4-8
Build in weekly slices
Every week ends with something on a real URL. ai-native product builds lands early, because the rest of the plan depends on it working.
- Launch
Ship, measure, hand over
Release, monitoring, analytics, and a documented handover, so your team can carry it without calling us.
Weighing up your options
There are three realistic ways to get this built. Each is the right answer for someone.
A solo freelancer
Cheapest per hour and fine for a contained task. The risk on AI product development is breadth — one person covering design, backend, infrastructure, and launch usually means one of them is weak, and there is no cover when they are unavailable.
A local agency in San Francisco
Same timezone and a face to meet, which genuinely matters for some teams. You are also paying SF Bay Area expecting modern stacks and AI fluency. rates for the whole team including the layers that never touch your AI product development, and a local shortlist is a small shortlist.
Arcode
A small senior team. The people who scope the AI product development write the code, you get weekly demos instead of status decks, and the engagement ends when the thing is live and handed over.
Work we have shipped
Better Health Solutions
Frontend · CMS
Clinic website for Dr. Khayami with patient resources, scheduling UX, and educational video.
Responsive chiropractic practice site built at Code Band with Next.js, Redux Toolkit, Video.js, and Strapi content management.
- · Responsive clinic experience
- · Appointment-oriented UX
- · Patient education video
- · CMS-managed content
Next.js · Tailwind · Redux Toolkit · Strapi · Video.js
Happy Kids Dental
Frontend · CMS
Pediatric dental site with services, patient resources, and appointment-focused UX.
Code Band clinic product using Next.js, Tailwind, Redux Toolkit, Video.js, and Strapi for content and scheduling flows.
- · Pediatric service pages
- · Patient resource content
- · Appointment scheduling UX
- · Strapi-managed content
Next.js · Tailwind · Redux Toolkit · Strapi · Video.js
Vigorant
Frontend · Accessibility
Accessible web app with reusable components, Redux Toolkit state, and Strapi integration.
Code Band product built with React, Next.js, Tailwind, and Redux Toolkit, focused on accessibility and maintainable UI patterns.
- · Accessibility-first UI
- · Reusable component system
- · Efficient Redux Toolkit logic
- · Strapi-backed content
Next.js · React · Tailwind · Redux Toolkit · Strapi
Working with teams in San Francisco
SF Bay Area expecting modern stacks and AI fluency. We work with clients in San Francisco remotely and keep overlapping hours in PST/PDT. We usually collaborate in English.
How we work with San Francisco teams
San Francisco is on PT, which is the widest gap we work across. We hold one fixed call in your morning and run everything else in writing, so the time difference costs you a day at most on decisions.
What San Francisco clients usually need
Bay Area briefs are the most AI-heavy we see: agents with real tool access, RAG over internal knowledge, MCP servers connecting models to existing systems, and evaluation harnesses to prove any of it works.
Contracts, data, and compliance
Teams here expect modern defaults, so we work in TypeScript, ship through CI, and keep infrastructure reproducible. Expect direct technical conversation with whoever is writing the code.
