Every case study, system breakdown, and field note, newest first and filterable by topic. No theory, no demos. Only systems that run in production and what it took to get them there.
This is the complete archive: all 513 posts across 54 topics, newest first, filterable by category. It holds the case studies, the model and tool comparisons, and the field notes from systems I built and run. For the curated view, where the writing sits alongside the free Claude Code skills, start at the Library instead.
The archive leans in four directions: AI Search Visibility (98), AI Agent Architecture (61), AI Tools (38), and AI Coding Agents (27). Those four account for most of what I publish, because they are where most of the client questions land.
Three places to start. The AI search visibility guide is the hub for the largest cluster and links out to every spoke in it. Grok Imagine vs Midjourney is the image model comparison, rebuilt against live leaderboard data rather than left to go stale. OutreachIQ is the longest running system breakdown here, from first prototype through to a public repo.
Google and Bing now expose first-party AI visibility data, but they do not measure the same thing. Here is how to read the conflict without over-trusting either platform.
The useful question is no longer whether AI bots exist. It is which ones create discovery value, which ones help users act, and which ones mostly extract value from your site.
If AI Mode queries are longer and more multimodal, service pages need a clearer opening answer, stronger proof, and better internal support without collapsing into generic SEO mush.
AI visibility is getting more measurable, but snapshots still mislead. Here is a better metric for small brands: a citation volatility map that tracks where citations persist, disappear, and move closer to revenue.
AI-mediated discovery is creating more blind spots between visibility and visits. Here is why traffic can look weaker even while your brand is being surfaced, compared, and remembered.
Google's own AI-search guidance is much less mystical than most SEO chatter. Here is what the docs actually point toward, and what they do not support.
If AI agents increasingly compare, shortlist, and even act on behalf of users, service sites need stronger trust, clarity, and proof layers. Here is what that changes.
Bing's June 2026 AI visibility upgrades made citation tracking much more concrete. Here is why Citation Share matters even if Bing is not your main lead channel.
A clean homepage is not enough for AI-mediated discovery. Here is how to think in proof packs: linked sets of service, system, founder, and third-party evidence that help AI systems trust your brand claims.
If AI citations move more often than most brands expect, your service pages need a maintenance rhythm rather than one big optimization sprint. Here is how I would structure it.
AI search visibility is becoming measurable, but the useful business question is still ROI. Here is how I would separate vanity visibility from the signals that actually move revenue.
Google Search Console and Bing Webmaster Tools now offer first-party AI visibility reporting. Here is what each one can tell you, what they still miss, and what a small brand should actually measure.
An integrity graph is the layer that connects your brand facts, services, proof, and entity relationships into something AI systems can understand without guessing. Here is why that now matters for AI search visibility.
AI search often expands one query into many sub-queries before it decides what to cite. Here is how to plan a service page around query fan-out instead of only one keyword.
Google's Preferred Sources and Highly Cited signals push in the same direction: the brands that win will be the ones worth citing first, not the ones publishing the most generic content.
ChatGPT and Google AI Overviews do not seem to use the same third-party sources in the same way. Here is why your proof strategy should reflect that difference.
As AI agents merge public pages with private documents and connected tools, your website is no longer competing only against other websites. It is also competing with the user’s own context.
Reviews are no longer only a reputation asset. As AI systems summarize and recommend businesses, review freshness, detail, and consistency are becoming part of the visibility layer too.
If brand is the new backlink for AI search, the real work is not vague awareness. It is clearer identity, stronger proof, better entity consistency, and more distinctive pages.
Your website now has a second audience: AI agents acting on behalf of buyers. Here is how to make a site easier for agents to interpret without flattening the brand for humans.
Once AI visibility becomes reportable, the strategic question changes. Not “are we visible?†but “which pages deserve that visibility first?â€
The current branding backlash is not anti-AI. It is anti-defaults. Here is why AI-assisted brand refreshes need stronger constraints if they want to stay distinctive.
Fresh June 2026 data suggests the answer is yes, but unevenly. The better question is which users click, and what kind of page they expect when they do.
Google has now said the quiet part out loud: most AI-search “optimization†tricks are still just SEO myths with new names. Here is what actually matters.
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