Eric Siu, founder of Single Grain, describes how his agency built a "Single Company Brain" — an AI-powered intelligence layer that sits between scattered company knowledge (Slack, Gong, CRM, SOPs) and the actual work teams need to do. The key insight is that simply storing more data doesn't help; their early approach of giving agents more memory actually backfired, with persistent memory files consuming 40% of the context window and making the system operationally messier despite being technically smarter.

The solution is a five-layer architecture: Capture (raw data from calls, CRM, SOPs), Retrieval (surfacing only the 6 or so pieces of context relevant to a specific task), Source Truth (establishing which source wins when information conflicts), Permissions (ensuring agents only access what's appropriate for their workflow), and Feedback Loops (converting every human correction into a permanent rule). At Single Grain, this system processes 500K+ tokens of persistent memory, runs 90+ daily crons, and has turned 2,862 Gong call transcripts into operational playbooks — with a single daily ingestion of 15 calls producing 390 insights, 470 facts, and 125 frameworks.

Siu argues the real competitive advantage isn't having the biggest prompt library but having the cleanest intelligence layer. He provides a practical audit framework: pick one recurring workflow, then answer six questions about its sources, trust hierarchy, required context, restricted context, repeated corrections, and how corrections become rules. The result is a system that compounds over time — making the company "harder to forget, faster to teach, and easier to operate."