Author
Mayank Mudgal
Writes on the company brain, MCP integration, and what enterprise AI agents actually need from a shared semantic context layer.
Mayank works at Colrows on how enterprise AI agents get the context they need to be reliable. He writes about the structural difference between a wiki, a vector store, and a real company brain - and about why Model Context Protocol works only when something on the other end can actually answer typed questions about meaning.
Posts follow the Colrows editorial policy: technical claims are reviewed against the architecture, and citations point to primary sources (Anthropic on MCP, Y Combinator on the company brain, and so on).
Areas of focus
Company brain
Model Context Protocol
Agent context engineering
Institutional memory
Enterprise AI
Posts
- The 9 Best AI Analytics Tools in 2026, Scored on Accuracy and Governance12 Jun 2026
- ThoughtSpot Pricing Explained: List Prices, Real Contracts, and the Cost Nobody Quotes12 Jun 2026
- Auditable SQL for Regulated Industries: Conversational Analytics in BFSI12 Jun 2026
- Semantic Layer vs Text-to-SQL: Why Deterministic Compilation Wins12 Jun 2026
- 8 Looker Alternatives Without the LookML Lock-In (2026)12 Jun 2026
- Power BI Copilot vs Tableau Pulse: Two Takes on AI BI, Same Ceiling12 Jun 2026
- Snowflake Cortex Analyst vs Databricks Genie: Where Warehouse-Native AI Stops12 Jun 2026
- 8 ThoughtSpot Alternatives for Governed, Auditable AI Analytics (2026)12 Jun 2026
- Deterministic vs Probabilistic Text-to-SQL: A Buyer's Framework11 Jun 2026
- The Semantic Layer Buyer's Guide for 20262 Jun 2026
- The Company Brain: Why Enterprise AI Agents Need a Shared Semantic Memory10 May 2026
- MCP Meets the Semantic Layer: How AI Agents Compile Through One Source of Meaning10 May 2026