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An argument for moving AI outputs from unstructured text to typed data objects to build durable systems. When AI agents produce durable work like decisions or plans, passing that output as text creates fragile workflows.
Explains why adding more parameters isn't enough anymore; we need more compute and better post-training data for reasoning. Tracking parameter counts is getting outdated.
A concrete workflow for using coding agents while keeping humans responsible for quality. Kenn separates design, specification, implementation, verification, and merge ownership instead of treating agent output as production-ready.
Why AI application startups have to build their own model fine-tuning factories to survive in the enterprise. Decagon AI shows that selling agents to large enterprises requires custom workflows that frontier models can't handle alone.
A breakdown of the six components you need to build a reliable agent harness. The harness is the software layer between the model and the actual work.
How Wall Street is turning AI data centers into securitized assets like power plants. Nvidia signed MOUs with Apollo, BlackRock, and Blackstone to raise $500 billion for AI data centers.
As Vice President of Research at OpenAI, Mia Glaese leads teams focused on model alignment, human data, and capability evaluations.
Amanda Kahlow founded 6sense and grew it past $100 million in revenue before taking a five year break. She recently returned to build 1mind, a startup replacing traditional sales funnels with conversational AI agents.