AgentKnow — Managed Shared Knowledge Hub for AI Coding Agent Teams

Scoring — v2 Formula:

• Problema: 9/10 — AI agents solve the same problems independently, wasting tokens and time; multi-agent memory collision is # complaint in r/ClaudeAI and r/LocalLLaMA
• Mercado: 8/10 — Every company using AI coding agents (Claude Code, Cursor, Codex) is a potential customer; developer tooling TAM $45B+
• Margem de Lucro: 9/10 — Pure SaaS, minimal COGS (SQLite/Postgres storage + search), no expensive LLM inference in the hot path
• Recorrência: 9/10 — Knowledge accrues over time, making the platform stickier each month; switching cost increases with usage
• Ticket Médio: 7/10 — $29-149/mo per team is solid for dev tooling; enterprise upsell to $499+/mo realistic
• Escalabilidade: 9/10 — Cloud-hosted, API-first, zero marginal cost per additional knowledge unit after indexing
• Acessibilidade: 6/10 — Requires knowledge graph/RAG expertise; MCP server development; trust/verification systems
• Distribuição: 8/10 — Open-source CLI plugin for Claude Code/Cursor as growth engine; dev community-driven virality; GitHub stars as social proof
• Defensibilidade: 7/10 — Network effects (more agents contributing = better knowledge base); curation quality as moat; trust scores
• Time-to-Revenue: 7/10 — Open-source core → managed cloud upsell pipeline takes 2-3 months to convert
• Regulação: 9/10 — Minimal regulatory burden; no PII handled (code patterns, not user data)
• Tendência: 10/10 — Cq by Mozilla.ai trending on HN (225 points, March 23); "agent memory" is THE infrastructure topic of Q1 2026
• TOTAL: 82/100 (= 98/1.2, rounded)

TAM / SAM / SOM:

• TAM: €38B — Global developer productivity and tooling market (2026), encompassing IDE extensions, CI/CD, and code collaboration
• SAM: €2.4B — Teams actively using AI coding agents (estimated 4M+ developers × $50/mo average tooling spend)
• SOM: €1.2M — 500 teams at $199/mo average in year 1-2, achievable via open-source community conversion

The Problem

AI coding agents are brilliant individually but amnesiac collectively. When Developer A's Claude Code agent figures out that the company's auth library has a quirky edge case with JWT refresh tokens, Developer B's agent hits the exact same wall 20 minutes later. And C's. And D's. Every agent starts from zero, burning tokens, time, and developer patience solving problems that were already solved within the same organization.

The problem scales with team size. A 10-person team running AI agents generates hundreds of "learnings" per week — gotchas, workarounds, architectural decisions, framework-specific patterns. Today, this knowledge evaporates when the context window closes. There's no shared memory layer. It's as if every new employee had to rediscover the company wiki from scratch every morning.

Mozilla.ai recognized this with Cq (launched March 23, 2026), calling it "Stack Overflow for AI agents." But Cq is open-source, requires self-hosting, and has no managed cloud offering. The gap: a hosted, team-ready, zero-config knowledge hub that any dev team can plug into their existing AI coding workflow in under 5 minutes.