-
The Agent That Did the Right Thing Ten Thousand Times
In grid operations the dangerous agent is not the one that gets it wrong. It is the one that gets it right at a scale nobody bounded.
-
Delegation Multiplies Authority Unless Something Stops It
Every agent in a multi-agent pipeline is inside its own limit. Nobody is tracking what the tree can spend, and the tree is what has your money.
-
Your Agent Does Not Need a Bigger Context Window
Every document an agent retrieves is an instruction it was never told to distrust. The fix is not more context. It is knowing which parts of it someone else wrote.
-
Structured Output Isn't Reliable Output
JSON mode, function calling and constrained decoding give you schema compliance, not semantic reliability. Valid JSON can be completely wrong.
-
The Insurance Industry's AI Blind Spot: Claims Automation Without Trust Infrastructure
Insurance companies are racing to automate claims with AI. Nobody has built for the regulator, the litigant, or the appeals board. That is the blind spot.
-
The Agent Watchtower, Part 5: Reference Architecture
A complete, implementable design for enterprise agent governance. Concrete specifications, integration patterns, and implementation roadmap.
-
The Agent Watchtower, Part 2: Anatomy of an Agent Control Plane
The technical architecture for unified agent governance: registry, observability, policy and control, and how they make multi-cloud governance possible.
-
Your AI Architecture is Bleeding Money
Cost-per-token is the wrong metric. The real savings come from architectural decisions most teams get wrong.
-
The AI Production Readiness Checklist
The comprehensive checklist for launching LLM-powered features. Evaluation, monitoring, fallbacks, cost controls, and incident response.
-
Prompt Injection is an Unsolved Problem (Here's How to Mitigate Anyway)
There's no complete solution to prompt injection. Here's the defense-in-depth playbook for production AI systems.
-
When to Use Agents vs Deterministic Workflows: A Decision Framework
A concrete decision tree for when to reach for AI agents vs traditional orchestration. Cost, latency, reliability, and compliance dimensions.
-
AI Observability is Expensive Voyeurism
The observability market is selling you dashboards to watch your AI fail in high resolution. What you need is controllability.
-
Your Data Team is Building an AI Graveyard
Every transformation in your data pipeline destroys information AI needs. Traditional data engineering is a lossy compression algorithm.
-
Multi-Agent is This Decade's Microservices Mistake
The multi-agent hype will collapse. We learned this lesson with microservices. Distributed systems are hard.
-
Foundation Models Are a Commodity. Act Accordingly.
Everyone's agonizing over Claude vs GPT vs Gemini. It doesn't matter. The differentiation is moving up the stack.
Platform
Solutions
- European Union
- United States
- Singapore
- Australia
- India
- All regions
- EU AI Act
- GDPR
- SR 11-7
- NIST AI RMF
- Regulatory mapping
- DORA
- ISO/IEC 42001
- Canada AIDA
- MAS FEAT
- UK framework
- All instruments
- Financial services
- Capital markets
- Insurance
- Healthcare
- Life sciences
- Energy and utilities
- Telecommunications
- Government
- Software and AI-native