Engineering notes.
Practical, no-fluff writing on AI agents, RAG, LLMs, and blockchain — from the senior engineers who build them in production.
How much does it cost to build an AI agent in 2026?
Real cost ranges for building an AI agent in 2026 — what drives the price, the hidden ongoing costs, and how to spend less without cutting corners.
AI for fintech: 6 use cases that actually ship
Beyond the hype — the AI use cases that deliver real ROI in fintech, what each one takes to build, and the accuracy and compliance bar fintech demands.
AI agent vs chatbot: what's the difference?
Chatbots answer questions; AI agents take actions. A clear, practical breakdown of the difference, when you actually need an agent, and why agents cost more to build.
The AI model race: what it actually means for people building products
OpenAI, Google, and Anthropic are racing for the frontier. Here's what the 2026 AI model race actually changes for teams building AI products — and what to do about it.
AI trading agents: what actually works (and what's hype)
Multi-agent LLM trading frameworks are everywhere in 2026. An honest look at what AI trading agents can really do, why backtests lie, and the engineering that separates real from hype.
How to evaluate an AI agent (and why most teams skip it)
The eval harness is what separates an AI demo from a production agent. A practical guide to evaluating AI agents — what to measure, how to score it, and the mistakes to avoid.
AI in defense and the global AI race: what it signals for everyone building AI
Governments are pouring billions into AI and autonomy in 2026. A measured look at what the national AI race signals for the rest of the tech industry — and the engineering lessons that carry over.
RAG vs fine-tuning: which does your product need?
RAG and fine-tuning solve different problems. A practical, no-hype guide to choosing the right one for your AI product — with a decision framework and real cost trade-offs.
The latest AI models in 2026 — what to actually build with them
A builder's guide to the 2026 AI model landscape — capability tiers, 1M-token context, test-time 'thinking', and how to pick the right model for your product instead of the biggest one.
Smart contract audit checklist before mainnet
The security gates a smart contract should clear before mainnet — test coverage, static analysis, the vulnerabilities to hunt, external audit, and safe deployment.