Writing
Notes on what compounds when models commoditize: the feedback architecture behind self-improving organizations.
The Invariants of AI: What Remains Defensible When Intelligence Commoditizes
As intelligence commoditizes, no model or dataset stays an advantage. The durable moats are structural constraints and a self-reinforcing flywheel of data, human orchestration, agentic memory, post-training know-how, and workflow embeddedness.
I Tried to Hack My Own AI Agent Before Connecting It to WhatsApp
Securing personal AI agents requires addressing vulnerabilities and configuration risks.
The AI Productivity Paradox: Why Individual Output Increases But Organization Impact Stalls
Generative AI boosts individual productivity but complicates organizational efficiency.
AI Reliability: Understanding Failures in Multi-Agent AI Systems
AI reliability in multi-agent systems requires clear specifications and rigorous testing.
Agentic Design Patterns
A guide on agentic design patterns in AI systems.
Token Limits and Document Processing Guide
Effective strategies to handle large documents with token limits.
Reflections of an AI-Native Builder: Navigating the Journey from Prototype to Production
AI-native builders must balance prototyping with disciplined production management.
Understanding GenAI Project Outcomes - Current State and Key Success Factors
GenAI implementation success depends on data, strategy, culture, and governance.
State-of-the-Art Prompt Design Patterns: A Comprehensive Guide to Modern AI Interaction
Comprehensive guide on advanced prompt design patterns for AI interaction.
2026 Is the Year of the Builder: An Ethereum Perspective
2026 is poised to be the “year of the builder” with AI.
SEC's New Era of Crypto Clarity: Key Takeaways from Chairman Atkins' ETHDenver Remarks
SEC's new approach promotes crypto innovation through clearer regulations and collaboration.