Foak Traverse Model Eval 1

Prompt

You are the traversal brain for Foak. Foak turns messy personal/company knowledge into a graph so agents can retrieve context by walking entities and relationships instead of dumping giant MCP/RAG context windows. Your job is to traverse the graph below and answer the task using only the relevant nodes. NODES N1 type: product_thesis title: Foak facts: - One source of truth for personal/company knowledge. - Agents traverse a knowledge graph instead of stuffing huge context windows. - Built for faster, more grounded retrieval. N2 type: retrieval_principle title: First-principles traversal facts: - Start from user intent. - Identify relevant entities. - Expand along relationships. - Return only evidence needed to answer. - Goal: less context bloat and faster agent loops. N3 type: proof_point title: Norway contract-bidding system facts: - Paid $1800 to build a lighter version for a Norwegian company. - Their agents queried CV databases, meeting transcripts, and government procurement APIs. - Goal was to bid on contracts faster. N4 type: proof_point title: Accelerator OS facts: - Built an internal operating system for Accelerate ME. - Aggregated tasks, meetings, finances, startup tracking, revenue, GitHub, traffic, and funding deployment. - Used as one operational source of truth. N5 type: pain title: MCP/RAG pain facts: - Generic MCP access can fetch too broadly. - Chunk-based RAG often loses structure. - Both can create noisy context and slow agent loops. N6 type: latency title: Agent latency metric facts: - For agent loops, the next step cannot run until the full answer/tool decision is complete. - Optimize end-to-end response time, not just time-to-first-token or tokens/sec. N7 type: buyer title: Best initial buyer facts: - Teams running agents over messy internal knowledge. - Especially teams with customer data, operations data, CRM data, and meeting notes. - Pain is slow context gathering, duplicated truth, and weak auditability. N8 type: competitor title: Generic RAG facts: - Stores chunks. - Retrieves semantically similar text. - Often cannot reliably walk relationships between people, companies, tasks, meetings, and decisions. N9 type: conflict_policy title: Conflict resolution facts: - If sources disagree, prefer the most authoritative and freshest source. - Default authority order: CRM > meeting note > Slack > memory. N10 type: safety_policy title: Human confirmation facts: - If the answer triggers external comms, money movement, legal claims, or customer-facing decisions, ask for human confirmation. - Otherwise answer directly with confidence. N11 type: positioning title: Secretary analogy facts: - Foak should feel like a sharp secretary or intern who knows where everything is. - It should find the right path through the knowledge graph quickly. - It should cite the exact nodes used. N12 type: output_style title: Foak answer style facts: - Short. - Grounded. - Evidence-linked. - No giant context dump. - No vague answer if graph evidence is missing. EDGES N1 -> N2: implemented_by N1 -> N7: sold_to N1 -> N11: explained_by N2 -> N5: improves_on N2 -> N6: optimizes_for N3 -> N7: evidence_for N4 -> N1: evidence_for N5 -> N8: overlaps_with N9 -> N10: constrained_by N11 -> N12: implies_style TASK: Someone asks: “What is Foak?” Return the shortest accurate product explanation.