Speed you can plan around
Platform-grade scope in a fraction of the usual time, with milestones you accept on deliverables.
Our AI-native approach
This page is the honest version of how that works. No percentages we can't prove. Just the practice.
A week of delivery, sketched
The headline fact
All development at Buzzinga happens through coding agents, mostly Claude Code and Codex. That sentence sounds like hype until you see what it changes in a week of work.
Our engineers spend their day where humans are irreplaceable: understanding the problem, deciding the architecture, reviewing what ships. The mechanical work happens through agents, sometimes running long after the office empties. Verifying quality never moves to the agent. Each engineer stays responsible for what they ship.
Humans own
The problem, the architecture, the review. Responsibility never moves.
Agents carry
The mechanical work, sometimes running long after the office empties.
The practice
Five habits, in the order they happen. None of them are exotic. Together they are why the timelines hold.
Discovery produces written scope, assumptions, and risks. We design systems around real operational workflows, not just screens.
Every repo carries whole-app documentation in markdown: architecture, how-it-works, feature docs, personas. Agents and people both learn the product from these docs before touching the code. Right understanding builds the right thing.
An engineer spends the day on planning and research: architecture decisions, migrations, tricky flows. Then hands implementation to agents with precise instructions.
Human review on everything. Design and architecture decisions never leave human hands.
Fixed price, milestones accepted on deliverables, not dates.
What changed
Our designers build frontends; some products have no Figma at all, the UI is built directly with agents against hard design rules in the codebase. Engineers move across the stack. What holds it together isn't titles, it's the documentation, the design rules, and the review discipline.
Consistency was the hardest problem with agent-built UIs. We solved it the boring way: strict rules that live inside each codebase, where agents can't miss them.
What holds it together
Why it matters to you
Platform-grade scope in a fraction of the usual time, with milestones you accept on deliverables.
The docs-in-the-codebase practice means the product isn't trapped in anyone's head. Any engineer, or agent, can pick it up.
A codebase agents can navigate today is a system agents can help operate tomorrow.
Explore our services ->Proof in the wild
An embedded software security company needed an internal app. There was no Figma at all. A brainstorming session covering scope and architecture went straight into development, and the demo build reached staging in weeks.
The practice above is why that timeline was normal for us, not heroic.
See more work ->Next step
Tell us what you're imagining. We'll reply with an honest take on scope, approach, and whether AI belongs in it at all.
Fixed price, milestone-based. Milestones accepted on deliverables, not dates.