Local AI: Agentic Failure Modes & How To Encourage Them
The post argues that traditional marketing metrics (opens, likes) are insufficient for AI‑driven content agents. It highlights Cici’s LinkedIn experiment, where modest engagement generated $1,600 in course sales, and a prior post that earned $8,185 despite poor social metrics. The author proposes a self‑improving "flywheel" framework where outcome data, not code, guides each iteration of an agent. This information‑centric approach is taught in the author’s Data & AI Strategy Certification course.
Building Knowledge Graphs As An Agentic Operating System
The post argues that knowledge graphs should serve as an operating system that aligns AI agents with a company’s strategy, turning technology into a reliable partner rather than a disruptive force. It stresses that AI models alone are too inconsistent...
Building Knowledge Graphs To Support Agentic Workflows
The article argues that knowledge graphs only add value when they inform both decisions and actions, shifting from pure information representation to outcome‑centric engineering. By recounting past projects—one that saved tens of millions annually and another that generated roughly $2 billion...
Agentic Architecture Part 3: The Information Layer
The article emphasizes the information layer as the critical foundation of any agentic architecture, detailing the infrastructure needed to turn raw data into a usable knowledge graph. It argues for an incremental, cost‑effective approach that lets small teams deliver a...
The Fed Chair Just Said What AI Leaders Won't: The Models Don't Work
Fed Chair Jerome Powell publicly expressed his lack of confidence in the economic models used to forecast markets, noting that no system has reliably predicted the economy. He highlighted that while large language models (LLMs) have advanced dramatically, they remain...
Agentic Architecture Part 2: The Agentic & Shared Development Environment
The second installment of the Agentic Architecture series examines the Agentic & Shared Development Environment, where intent is transformed into coordinated actions across a network of specialized agents. This layer handles decomposition, routing, execution, and multi‑technology coordination, making it the...
Local AI: From Local To Enterprise Agentic Architecture
The author outlines a five‑layer agentic architecture that bridges the gap between static knowledge graphs and actionable AI agents. While platforms like ServiceNow provide an Action Layer and Salesforce a Data Cloud Information Layer, the post argues that both must...
Local AI: How & Where To Start Building Something You Can Monetize
The post argues that local AI—running LLM‑based agents on personal hardware—offers a viable path to high‑margin products without costly cloud APIs. It highlights two paradigm shifts: turning idle compute into revenue and focusing on workflow‑based agents that leverage structured memory...
Wall Street Has a Scorecard for Your AI Strategy & Most Companies Are Failing
Wall Street has moved from AI hype to a rigorously quantified scoring system, using structured KPIs to evaluate corporate AI maturity. Consulting firms, private‑equity shops and equity research desks now rank companies on these metrics, directly influencing share prices and...
