Project “Clean Room” · Built by Anthony Key
Swarm Lite creates AI persona swarms that review your business proposals, debate your features, and forecast market temperature — before the LinkedIn post, before the reactive sprint, before you commit resources.
The Story
Why product teams keep reacting — and a better way forward.
5
AI personas per swarm
0
Manual research steps
100%
HITL approval on actions
∞
Projects · markets · branches
The Problem
Product teams are reactive by default. A competitor ships a feature. Someone screenshots it into Slack. A meeting gets scheduled. A week later, a half-formed response lands in the backlog — with no user research, no strategic context, no assessment of whether responding is even the right move.
Monday
A new feature appears on a competitor changelog. No one on your team knows yet.
Wednesday
Someone posts about it. Your PM sees it and starts a Slack thread. Knee-jerk reactions begin.
Friday
A feature request lands in your backlog. No user research, no strategic analysis, no signal — just reaction.
Swarm Lite gives you the brief before the screenshot.
Market intelligence treated as a stateful system process — not a research exercise. Test your response before you build it.
Create AI personas representing target users and stakeholders. Run huddle sessions where they debate, critique, and stress-test your proposals.
Branch from any session to test variations — different personas, adjusted queries, follow-up questions. Preserve the original while exploring alternatives.
Define competitive landscapes with competitors, watch items, and scan intervals. The system monitors and surfaces relevant signals.
Every session produces a structured brief — overall sentiment, per-persona breakdown, key themes, and prioritised recommended actions.
Resource-intensive decisions require explicit human approval. Every action logged with cost, status, and context. HITL by design.
Share projects, markets, and personas with specific team members or make them globally available across your organisation.
Thinking Behind the Build
Surveys take weeks and suffer from response bias. AI personas give instant, structured feedback from validated archetypes — and you can branch and re-test in minutes, not months.
Enterprise credibility requires enterprise design. Carbon provides the component system, spacing tokens, and accessibility compliance that make the app look like it belongs in a procurement conversation.
Real strategy is not linear. When a persona raises a security concern, you need to follow that thread with just the enterprise personas — without losing the original five-persona context.
AI proposes, humans decide. Every resource-intensive action surfaces with cost and context. The approval gate is not a limitation — it is the feature that makes this deployable in an enterprise.
Anywhere you need structured feedback from representative user archetypes before committing resources — this architecture applies.
Product Strategy
Constraint: Feature prioritisation
Test proposed features against user personas before sprint planning
Marketing
Constraint: Campaign positioning
Validate messaging with target archetypes before launch
Healthcare
Constraint: Patient experience
Test service changes against patient persona panels
Financial Services
Constraint: Product suitability
Validate investment product positioning with client archetypes
Education
Constraint: Curriculum design
Test learning experiences against student and educator personas
Government
Constraint: Policy impact
Model citizen reactions to proposed policy changes
Next.js 16 + React 19
Frontend
IBM Carbon
Design System
IBM Carbon
Design System
Python FastAPI
Backend
LangGraph
Agent Graph
Anthropic Claude
LLM
SQLite
Persistence
Carbon + Lucide
Icons
IBM Pictograms
Pictograms
Part of a trilogy
Execution layer
Agentic supply chain intelligence. Solver fails — AI diagnoses — Action Card renders — human approves — solver reruns.
Intelligence layer
Competitive intelligence before the screenshot. Monitors your landscape and delivers structured briefs.
Testing layer
AI persona swarms that test your ideas against synthetic market intelligence before you commit.
Anthony Key is a Lead UX Designer and Product Architect with a track record of translating complex operational problems into products people can actually use.
Swarm Lite is a proof of concept and a provocation: what if businesses could test their strategic decisions against a synthetic panel of representative users — instantly, repeatably, and with full transparency into how each persona reasoned?
Every architectural decision in this project is documented and defensible. This is not a side project. It is a portfolio artefact demonstrating AI product architecture, agentic systems design, and the kind of senior product thinking that connects technical choices to strategic outcomes.