Blogs & Articles
Loop engineering, in the open
Notes on outcome-driven agents: pointing AI agents at a real-world metric and getting them to improve on it, run over run. Learn how an AI SEO agent optimizes rankings autonomously.
3 articles
Loop Engineering
Outcome loops, agent feedback, and the difference between an agent that remembers and one that improves.
6 articles
SEO & Organic Search
Measured search work: Search Console diagnostics, blog traffic, and outcome-driven SEO.
All Articles & Guides
SEO KPIs: use organic clicks as the outcome and the rest as diagnostics
A practical SEO KPI framework: organic clicks as a north star, with impressions, CTR, average position, indexation, and engagement used to explain it.
Why Is Organic Traffic Dropping? Diagnosis Guide & Fixes
Diagnose a drop in organic traffic step-by-step. Troubleshoot Google updates, technical indexing issues, ranking drops, and CTR before rewriting content.
Internal Linking Strategy: Donor Selection & SEO Measurement
Learn how to build an internal linking strategy using contextual donor pages, natural anchors, and Search Console metrics to measure organic traffic gains.
Google Search Console Optimization: How to Improve Rankings
Use Search Console metrics (clicks, CTR, position) to diagnose ranking drops, fix snippet conversion, and improve organic search performance.
How to Increase Blog Traffic: A Measured Organic Search Plan
Learn how to increase blog traffic with Search Console data, striking-distance optimization, internal linking, and measurable organic click experiments.
What is an AI SEO agent? A practical guide to measured search work
An AI agent running an SEO outcome loop ships bounded changes, measures Search Console results, and learns what moved organic clicks—not just what generated copy.
Agent reward loops: the missing layer between memory and real-world improvement
AI agents don't improve just because they remember. They improve when each shipped action is tied to measured reward and used in the next run.
Agent memory vs. agent feedback loops: why remembering isn't the same as improving
Most "AI agent memory" just gives an agent recall of the past. It doesn't make the agent better. Here's the difference between memory and a feedback loop.
Evals vs. outcomes: why your AI agent should loop on a real-world goal
Evals tell you if an agent passed a test. Outcomes tell you if it moved the number you actually care about. Here's the difference, and why it changes how you build.