Articles

Writing about developer products.

I write about DevRel, documentation, technical content, and the work behind making developer products easier to understand.

Technical SEO Checklist for Documentation Sites
Technical SEO for developer documentation: crawling, rendering, indexing, canonicals, internal links, Core Web Vitals, structured data, and search visibility.
13 min read documentation-seo technical-writing developer-experience
How to Organize Documentation That Has Drifted
Reorganize documentation that has drifted after product releases, version changes, renamed features, and duplicate pages without losing useful URLs.
15 min read technical-writing information-architecture documentation
Documentation Review Checklist Before You Publish
Review technical documentation for accuracy, task completion, code, structure, accessibility, links, metadata, and release readiness before publishing.
15 min read technical-writing documentation-workflow docs-as-code
Technical Writing Examples: 12 Real Formats and When to Use Them
Twelve technical writing examples from software teams, with the reader need, structure, and quality bar behind each format.
14 min read technical-writing documentation developer-experience
The Agentic Workflow Playbook: From Prompt to Shipped PR
The repeatable five-stage process I run to take a task from vague intent to a pull request I trust, with an AI agent doing the heavy lifting and me stepping in to frame the work and read the diff before it merges.
9 min read ai agents developer-experience
How I Set Up a Coding Agent That Actually Finishes the Task
A coding agent succeeds or fails before it writes a line. Here is the setup I use, the rules file, repository context, tools, permissions, and guardrails, that turns a capable model into an agent I trust with real work.
9 min read ai agents devtools
Wiring Tools into Your Agent with MCP: A Practical Setup
A hands-on guide to connecting an AI agent to your own tools and data with the Model Context Protocol. The client-server shape, a minimal working server, tool design, and the guardrails that keep it safe.
9 min read ai agents developer-experience
Fine-Tuning vs RAG for Agent Memory: When Each Approach Makes Sense
Fine-tuning and RAG solve different parts of the agent memory problem. Here is how to decide which one you actually need.
8 min read ai-agents rag fine-tuning
Shared Memory vs Isolated Memory in Multi-Agent Workflows
How to choose between shared and isolated memory architectures for multi-agent systems, including their coordination and debugging trade-offs.
6 min read ai-agents multi-agent agent-memory
Why Your Coding Agent Keeps Forgetting Everything: Memory Persistence in AI Coding Assistants
The memory persistence patterns that actually work for AI coding assistants, and why most agents lose context between sessions.
9 min read ai-agents coding memory
LLM Inference Optimization: What Actually Works in Production
A practical breakdown of the inference optimization techniques that move the needle — batching, quantization, caching, and attention kernels — with concrete numbers and the tradeoffs between them.
7 min read ai llm infrastructure
Memory Versioning and Audit Trails for Regulated AI Agents
If your agent overwrites its memory, you cannot pass a compliance audit. How to build append-only memory versioning and trace agent reasoning.
8 min read ai agents agent-memory compliance
Contextual Compression for Agent Memory: What Stays and What Goes
How agents decide what to keep in memory when context space is finite, and the three compression strategies that actually work.
8 min read ai-agents agent-memory context-windows
Episodic, Semantic, and Working Memory in AI Agents: A Practical Map
AI agents juggle three distinct memory types. Getting them wrong is the source of most agent memory failures I see in production.
7 min read ai-agents agent-memory llm-architecture
Memory Serialization: How Agents Persist State Across Sessions
Why agents forget everything on restart, and the serialization patterns that actually solve it
7 min read ai-agents agent-memory agent-architecture
Multi-Agent vs Single-Agent Systems: The Real Trade-offs
The decision between one agent and many is not about capability. It is about failure modes, latency, and operational complexity.
6 min read ai agents multi-agent systems agent architecture
The Agent Design Space: A Map of What Engineers Are Actually Building
After surveying production agents across industries, the design space clusters into patterns. Here is what I found.
8 min read ai agents architecture
When to Build an Agent and When to Build a Smarter Assistant
The difference between an AI agent and a smart assistant comes down to one thing: who drives the loop.
6 min read ai agents ai architecture agent design
Lambda Calculus as an AI Reasoning Exercise
Lambda calculus exposes substitution, scope, and composition errors in AI outputs through problems with mechanically checkable answers.
6 min read ai reasoning formal methods evaluation
The Anatomy of an Agent Loop: Perceive, Think, Act, Remember
The agent loop is not one thing. It is four distinct phases that run in sequence, and understanding each one is how you debug what breaks.
8 min read ai agents agent architecture loop design