Designing an Agent Reading Test
In which I try to give people tools to understand how agents read web content, and where they fail.
37 Posts
Documentation
Measure Agent Web Traffic Redux
In which I revisit measuring agent web traffic, and dive deeper down the rabbit hole.
Confident-Sounding Gibberish
In which I share research about why LLM-generated output is hard to fact check.
The Verification Gap in AI Content Pipelines
In which verification is the hardest unsolved problem in AI content pipelines, and most organizations don't know it.
How to Evaluate a Platform-Written Spec
In which I find that a platform-published spec's omissions track financial incentives.
Is Your llms.txt Already Stale?
In which I build a freshness check for llms.txt and discover that my tools were the problem.
Vibes are Out, Data is In
In which I explain why a vibes-based approach to AI and docs ain't cutting it.
How to Measure Agent Web Traffic
In which I lurk in server logs and try to make sense of what I see.
Make Your Hugo Site Agent-Friendly
In which I show you how I made multiple Hugo sites agent-friendly.
Case Study - 'upgrade-stripe' Agent Skill
In which I deep dive on a Stripe Skill, and what it means for the industry.
LLMs vs. Agents as Docs Consumers
In which I discuss how model training and agents need different docs access patterns.
Upskilling in the AI Age
In which I answer someone who asked me how to get started with AI.
Agent Web Fetch Spelunking
In which I ask an agent to help me explore Web Fetch with docs pages - and get a surprise.
Agent-Friendly Docs
In which I ask an agent to view hundreds of docs pages - and feel sad.
Agent Skill Analysis
In which I build a validator and analyze popular Agent Skills.
Inside the Code Example Comparison APIs
In which I deep dive into the problem domain to discuss the problems we had to solve.
Code Example Testing Redux - Designing Cross-Language Testing Infrastructure at Scale
In which I design systems to scale code example testing across the org.
Audit - Conclusions
In which we report what we learned through the code example audit.
Audit - Slicing Code Example Data
In which we explore different ways to break down audit data.
Audit - Modeling Code Example Metadata
In which we decide what information to store, and how.
Audit - AI-Assisted Classification
In which we have an LLM help us assign categories to code examples.
Audit - How can we access the data?
In which we explore the best way to get content and work with audit data.
Audit - What should we track?
In which we dive deeper into what we actually want to know.
Audit - What is a Code Example?
In which we decide what to count, and how.
Audit - Overview
In which we try to make sense of our code examples, and track them.
Docs Consolidation Project - Month Two Check-In
In which I explore lessons learned in the second month of a project to consolidate 9 docs sets.
Docs Consolidation Project - One Month Check-In
In which I explore lessons learned in the first month of a project to consolidate 9 docs sets.
What to Test In Docs Code Examples
In which I explore WHAT to test in docs code examples.
How to Test Docs Code Examples
In which I explore HOW to test docs code examples.
Hackathon Part 3 - Charts, Charts, Charts!
In which I make a whole lotta Charts.
Hackathon Part 2 - Modeling Documentation Metadata
In which I decide how I want to structure my documentation metadata.
Hackathon Part 1 - Out of Google Sheets and Into Atlas
In which I free my data from Google Sheets.
Benefits of Docs Writing Code Examples
In which I discuss the benefits of having a documentation team writing the code examples.
Knowing When Docs Need Updates
In which I discuss the strategies for knowing when docs need updates.
Test Docs Code Examples
In which I explore why you really need to test docs code examples.
Docs Readability Scoring
In which I automate readability scoring for documentation.
Docs-as-code workflow: the missing link; a collaboration tool
In which I wax poetic about the value of previewing a docs-as-code site.