Sun Tzu on AI: Position, Don't Fight
Sun Tzu wrote about war, but he was really writing about uncertainty. How to win through positioning when you can't predict outcomes. That feels relevant right now as AI reshapes work.
Category: AI/ML (8)
AI agents already want to transact but payment rails block them. The intersection of AI, blockchain, and programmable money, with practical applications over hype.
Machine-to-machine payments, AI agent economies, and coordination systems for autonomous economic actors.
Context Isn't Retrieval: Why RAG Won't Fix Agent Decision-Making
Retrieval gives agents information. Context gives them decision logic, constraints, and workflows. This deep dive explains why RAG cannot solve decision-making and why the context layer becomes essential infrastructure.
Post-AI World: Survivors and Casualties
AI disruption is coming without coordinated solutions. Historical transitions had survivors and casualties. In the absence of a plan, individual agency and context ownership become survival strategies.
Why AI Agents Can't Make Decisions Without Context
AI agents can execute actions, but they can't decide which action is correct. Finance exposes this gap more clearly than any domain. Here's why context, not compute, becomes the bottleneck.
AI, the Punch You Don't See Coming
A practitioner's warning to friends who aren't paying attention to AI. The transformation is already here, and most people won't see the punch until it lands.
AI Everywhere, Rockets on Donkeys
Companies are racing to add AI everywhere. But most are strapping rockets to donkeys and calling it innovation. Real transformation requires rebuilding systems, not just adding layers on top.
AI Agents Already Want to Pay Each Other But They Cannot
AI agents already want to transact with one another, but current financial rails block them. Stablecoins may solve storage, but intelligence layers will unlock real-time, global payments.
Rethinking V2 and Avoiding the Rewrite Trap in the Age of AI
Many teams are tempted to rebuild a clean V2 from scratch, but this often fails because it discards history, tribal knowledge, and unwritten context. A more effective path is gradual migration with strong boundaries rather than extremes like full microservices. With AI reshaping the way we build, the challenge is knowing where it can augment workflows without replacing engineering discipline. The teams that thrive will move deliberately, applying clarity and judgment to every step.