The Agent Watchtower, Part 1: The Fragmentation Tax
Banks are deploying AI agents across AWS, Azure, GCP, and open-source frameworks. The result: governance blind spots, compliance nightmares, and a ticking regulatory time bomb.
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Insights on AI trust
Practical perspectives on agentic systems, data architecture, and building AI that works in production.
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The Real Reason Your RAG App Hallucinates (It's Not Chunking)
Everyone's optimizing chunk size and embedding models. The problem is upstream. Your data pipeline strips context before it ever reaches the vector store.
Read more →All Posts
What Moltbook Reveals About Multi-Agent Trust at Scale
Moltbook isn't an enterprise product - but the vulnerabilities it exposes matter for any organization deploying multi-agent AI systems.
Read more →The Agent Watchtower, Part 5: Reference Architecture
A complete, implementable design for enterprise agent governance. Concrete specifications, integration patterns, and implementation roadmap.
Read more →The Agent Watchtower, Part 4: Economics of Agent Operations
The financial model for sustainable AI governance. Cost cascading, ROI-driven routing, and why governance pays for itself.
Read more →The Agent Watchtower, Part 3: The Autonomy Spectrum
How to balance business unit freedom with enterprise governance. Federated control, trust-based permissions, and why guardrails beat gates.
Read more →The Agent Watchtower, Part 2: Anatomy of an Agent Control Plane
The technical architecture for unified agent governance. Registry, observability, policy, and control - how to build the infrastructure that makes multi-cloud agent governance possible.
Read more →The Agent Watchtower, Part 1: The Fragmentation Tax
Banks are deploying AI agents across AWS, Azure, GCP, and open-source frameworks. The result: governance blind spots, compliance nightmares, and a ticking regulatory time bomb.
Read more →The Eval Crisis: Why Most Benchmarks Don't Matter
Your model scores 90% on MMLU. It still fails in production. The benchmarks everyone obsesses over measure the wrong things for enterprise AI.
Read more →5 Evals Every Production LLM Needs
Forget MMLU scores. These are the evaluations that actually predict whether your LLM will work in production.
Read more →The Real Reason Your RAG App Hallucinates (It's Not Chunking)
Everyone's optimizing chunk size and embedding models. The problem is upstream. Your data pipeline strips context before it ever reaches the vector store.
Read more →