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15 categories: design, engineering, game-development, marketing, paid-media, product, project-management, sales, spatial-computing, specialized, strategy, support, testing, examples, integrations. Each agent has frontmatter (name, description, color, emoji, vibe) and a detailed system prompt. Source: msitarzewski/agency-agents (MIT). These feed into our content pipeline: agent personas drive strategy and content generation through MixPost Enterprise, Bio.Host, and the wider Host UK toolkit via MCP. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
48 lines
2.3 KiB
Markdown
48 lines
2.3 KiB
Markdown
# Examples
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This directory contains example outputs demonstrating how the agency's agents can be orchestrated together to tackle real-world tasks.
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## Why This Exists
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The agency-agents repo defines dozens of specialized agents across engineering, design, marketing, product, support, spatial computing, and project management. But agent definitions alone don't show what happens when you **deploy them all at once** on a single mission.
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These examples answer the question: *"What does it actually look like when the full agency collaborates?"*
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## Contents
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### [nexus-spatial-discovery.md](./nexus-spatial-discovery.md)
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**What:** A complete product discovery exercise where 8 agents worked in parallel to evaluate a software opportunity and produce a unified plan.
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**The scenario:** Web research identified an opportunity at the intersection of AI agent orchestration and spatial computing. The entire agency was then deployed simultaneously to produce:
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- Market validation and competitive analysis
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- Technical architecture (8-service system design with full SQL schema)
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- Brand strategy and visual identity
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- Go-to-market and growth plan
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- Customer support operations blueprint
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- UX research plan with personas and journey maps
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- 35-week project execution plan with 65 sprint tickets
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- Spatial interface architecture specification
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**Agents used:**
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| Agent | Role |
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|-------|------|
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| Product Trend Researcher | Market validation, competitive landscape |
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| Backend Architect | System architecture, data model, API design |
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| Brand Guardian | Positioning, visual identity, naming |
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| Growth Hacker | GTM strategy, pricing, launch plan |
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| Support Responder | Support tiers, onboarding, community |
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| UX Researcher | Personas, journey maps, design principles |
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| Project Shepherd | Phase plan, sprints, risk register |
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| XR Interface Architect | Spatial UI specification |
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**Key takeaway:** All 8 agents ran in parallel and produced coherent, cross-referencing plans without coordination overhead. The output demonstrates the agency's ability to go from "find an opportunity" to "here's the full blueprint" in a single session.
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## Adding New Examples
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If you run an interesting multi-agent exercise, consider adding it here. Good examples show:
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- Multiple agents collaborating on a shared objective
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- The breadth of the agency's capabilities
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- Real-world applicability of the agent definitions
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