How Wunda runs your team.
We get asked variations of "are you actually faster, or is the AI thing marketing?" enough that we wrote this down. What follows is how we structure the team, what each phase looks like, the tradeoffs we make to deliver agency-grade work without agency overhead, and where the model breaks.
It's opinionated. Some of these choices will sound wrong to a traditional agency or a traditional engineering manager. They're the choices that made this model economically viable.
The labor math just changed.
Building a software business as a non-technical founder used to require five vendors (strategist, designer, full-stack dev, DevOps, growth operator), three contract negotiations, and ~40% of the founder's time spent coordinating between them. Most ideas died in the coordination overhead before they ever reached users.
Two things changed that. AI compressed the labor inside each role — a full-stack engineer with Cursor + Claude + v0 + the Anthropic SDK ships in 10 hours what used to take 40. The bigger and less-discussed shift: the coordination overhead between roles also compressed when one team runs the full arc inside a shared task system, instead of five vendors emailing each other.
Both compressions multiply. That's how a small async team can deliver agency-grade work at a fraction of the cost, billed purely by the hour. It doesn't come from skipping work — it comes from the work being differently shaped.
Chat with us. We do the rest.
Wunda's workflow is designed to feel as low-friction as prompting an AI, but with the reliability of a human team.
Tell us what you need.
Fill out the intake form with a rough idea of what you want to build. We're currently in beta, so we review every request manually and get back to you within 24 hours.
We build your team.
An AI onboarding specialist will discuss your goals with you and assign the exact experts you need (engineers, designers, marketers) to a dedicated Slack workspace for your project.
Direct collaboration.
You chat with your team members just like consultants. Explain what you want to do, ask about ideas, and get expert opinions. Once you agree on a piece of work, they provide an estimate.
Review and keep going.
When the work is done, the results are shared in Slack. You review the output, we iterate based on your feedback, and we move on to the next piece of work.
What we give up to ship efficiently.
Delivering agency-grade work at a fraction of agency cost isn't free. It comes from explicit choices that some teams will see as compromises. Naming them:
- We don't build pixel-perfect at MVP.The MVP looks polished but it won't win design awards. We optimize for "users can complete the core workflow" before we optimize for "users feel emotionally moved by the gradient."
- We pick technology choices, you don't.We use a stack we know ships fast: Next.js, Supabase, Stripe, Resend, Vercel, Anthropic. If you've specifically chosen a different stack, we might not be the right fit. Picking technology together adds weeks of discussion that compound badly.
- We pre-bundle the boring stuff.Domain, email, incorporation, compliance, brand pack, hosting. We orchestrate the partners (Stripe Atlas, Pilot, Termly, etc.) and absorb the coordination cost. You don't see most of it — you just get one Slack channel and one invoice.
- We ship async by default. Real-time meetings cost more than people realize. Most updates happen in a shared Slack channel + weekly written demos. We chat with you in Slack the same way you'd prompt an AI.
- The team adapts to the work. We pull in designers, engineers, or GTM specialists only when the work requires them. You talk directly to the experts doing the work. You only pay for the hours your project actually requires.
The model doesn't fit everyone. Here's where it cracks.
- Hardware-coupled products.If the software depends on physical hardware we can't simulate (an IoT product, a medical device with FDA implications), the velocity story breaks — hardware iteration cycles aren't AI-accelerated.
- Regulated industries.Healthcare with HIPAA, finance with SOX, anything with explicit compliance audits — these add weeks of certification work that doesn't compress. We can still build, but we'd quote you a longer arc up front.
- Multi-stakeholder enterprise sales.If your product's buyers are not the founder — if there are five enterprise stakeholders, an RFP process, a long procurement cycle — the launch is bottlenecked on sales, not product. We build the product; you'll still wait on procurement.
- You've already started building.The compression depends on us picking the stack and the patterns. If you've got 5,000 lines of code in a stack we don't default to, we can still work with it, but the velocity math doesn't hold.
Direct access to specialists.
You talk directly to the people doing the work. You share what you need with an AI onboarding specialist, we assemble the right team, and then experts rotate in and out as the work requires.
| Role | Typically active in | What they do |
|---|---|---|
| AI Onboarding Specialist | At intake | Discusses your proposal and assigns the right team members |
| Product Manager | As needed | Market research, feature prioritization, user interviews, and product strategy |
| Full-stack Engineer | As needed | Builds the product. AI-augmented; reviews own code with a senior pass |
| Product Designer | As needed | UI systems, interaction, prototypes, and landing pages |
| AI Engineer | As needed | LLM integration, agent workflows, RAG, and custom AI features |
| Go-to-Market Engineer | As needed | Paid ads, SEO, conversion rate optimization, and launch campaigns |
| Ops & Accounting | As needed | Coordinates the partner stack for incorporation, accounting, compliance |
Then we should probably talk.
Drop your project on the intake form and we'll write you back within 24 hours with whether we think it fits this model. We'll tell you if we don't. That's the whole offer.