RAG vs. Fine-Tuning vs. Tool Use: A Practical Decision Framework
A practical framework for choosing between retrieval-augmented generation, fine-tuning, and tool use based on knowledge freshness, behavior, actions, latency, and control.
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AI & Agents
Analysis of AI models, agents, autonomy, safety, and how these systems reshape software, products, and interfaces.
Model Context Protocol (MCP) Explained: What It Solves and What It Does Not
A practical explanation of Model Context Protocol: what MCP standardizes, how tools/resources/prompts fit together, where it differs from function calling and APIs, and what it does not s...
How to Evaluate AI Agents: Reliability, Cost, Latency, and Failure Modes
A practical framework for evaluating AI agents across task success, reliability, cost, latency, tool use, trajectories, and failure modes before production.
AI Agents vs. Workflows: When to Use Each Architecture
A practical framework for choosing between deterministic AI workflows and autonomous agents based on task structure, reliability, cost, latency, and control.
AI Doesn’t Need Malice to Become an Existential Threat
Catastrophic AI risk does not require a conscious machine that hates humanity. It can emerge from accidents, governments, institutions, individuals, or autonomous systems given too much p...
Anthropic Preaches Restraint, Then Ships Its Most Powerful Model
Anthropic argued that advanced AI required stronger controls. Weeks later, it released Claude Opus 5 with broader access and lower costs. The contradiction deserves scrutiny.
Apple, OpenAI, and the Battle for AI Hardware
Apple’s lawsuit against OpenAI is more than a trade-secret dispute. It reveals a deeper fight over who controls the interface that may come after the smartphone.
How AI Is Changing Software Development
The most useful role for AI in software development is not replacing engineers. It is reducing repetitive work so teams can spend more time on product judgment and architecture.