AI technologies
AI technologies used in shipped assistants and applications, including voice, retrieval, prompting, and tool integration.
Models, retrieval, voice, and agent tooling from production work—grouped here with project evidence. AI engineering goes deeper on the work.
Writing about AI
Context Engineering
An agent harness orchestrates memory, tools, skills, and retrieved information so models receive the right context at the right moment.
AI Agents are Infrastructure
Running agents in production means managing tools, state, permissions, and recovery—not just choosing a capable language model.
Agentic Commerce
Google's Universal Commerce Protocol, with A2A, AP2, and x402 around it, moves checkout into AI surfaces and makes shopping a workflow agents can execute.
Evolution of AI UX
AI interfaces are moving from prompts and answers to agents that hold intent, run workflows, and deliver outcomes, which makes visibility and control the core of the UX.
Why I'm Bullish on 2026
Why I expect AI agents, stablecoins, wallet signing, and tokenized markets to converge in products over the coming year.
Intersection of AI and Web3 (Part 2)
How agentic finance, stablecoin payment rails, and decentralized AI infrastructure are starting to connect in real products.
Agentic Finance
How AP2, x402, and agentic commerce protocols could let AI agents authorize payments and settle transactions with stablecoins.
Prompt Injection
How direct, indirect, and tool-response prompt injection hijack LLM behavior, and the layered defenses I use in AI applications that call tools.
AI Model Context Protocol (MCP)
What the Model Context Protocol standardizes about connecting models to tools and data, and how I structure MCP-style tools, composition, and memory in TypeScript.
RAG with TypeScript
How retrieval-augmented generation works, and how to implement it with TypeScript SDKs, embeddings, and vector stores.
The Skillset of a Product Engineer
Why product engineers take ownership of user needs, interfaces, and systems instead of working within one technical layer.
The Intersection of AI and Web3
A July 2024 snapshot of shared infrastructure between AI and Web3: compute, identity, data, and open networks.