AI Visibility Explained: Mentions, Citations, and Share of Voice
Sam Oh defines cited, mentioned, and absent AI visibility. This guide adds the mention-citation matrix, measurement caveats, and a practical audit.
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 781 posts across 63 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 (137), AI Agent Architecture (72), AI Business Ideas (41), and Open Source (41). 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.
Sam Oh defines cited, mentioned, and absent AI visibility. This guide adds the mention-citation matrix, measurement caveats, and a practical audit.
Sam Oh compares Google AI Overviews, AI Mode, ChatGPT, and Perplexity. This guide updates the source data and adds a platform-prioritization workflow.
Sam Oh explains training data, retrieval, query fan-out, and probabilistic citations. This guide updates the ranking evidence and adds a practical visibility test.
Andrew Warner and Alex McDonnell demonstrate a Hyperagent sales team inside Slack. Here is the architecture, approval model, shared-memory risk, security history, cost boundary, and safer rollout.
Cody Schneider and Greg Isenberg build a signal-based outbound agent and a transcript-driven content agent. Here is the architecture, cost boundary, platform risk, and safer implementation.
Sam Oh's Ahrefs AEO introduction, rebuilt as a practical guide to SEO overlap, mentions, citations, evidence limits, the full course map, and a 30-day baseline.
When AI search handles more early comparison work, the page that still wins is the one that survives the follow-up question. Here is how service pages should adapt.
Dustin Puryear turns the B2B SaaS demo into a qualification system: a visible CTA, short intake form, evidence-led discovery, three-feature limit, objection library, and same-day follow-up.
Claude Code creator Boris Cherny explains why stronger models need less legacy scaffolding. Here is the eval-led delete-and-restore method, prompt audit, verification contract, and security caveat.
A July 2026 study found AI can often describe brands accurately while still failing to mention them in buyer research answers. Here is what that gap means for small expert brands.
Google launched dedicated generative AI Search Console reports in June 2026, but only for a subset of sites. Here is the interim measurement stack small brands should use instead of waiting.
Futurepedia demonstrates how Claude Design can turn prompts, reference images, design systems, and timestamped transcripts into editable motion graphics. Here is the practical workflow, prompt, QA process, and beta caveats.
Theo traced T3 Code's idle GPU load to infinite status animations interacting with a fixed noise overlay. Here is why Fable and GPT-5.6 guessed wrong, what the final patch changed, and a better AI-assisted debugging workflow.
Running Claude Code on free model tiers via OmniRoute: what is genuinely free, what leaves your laptop, which routes raise terms concerns, and a safer setup.
Andrew Warner and Mike Bradley install ODS on Windows. Here is what the local AI stack includes, what stays private, the real hardware tiers, and a safer setup path.
Bijan Bowen pairs Fable 5 with local Qwen3.6 27B in Traycer. Here is what improved, failed, and the solo baseline revealed about multi-agent orchestration.
Chris Do's live niche coaching turned into a practical decision system: define an ICP, verify demand and budget, distinguish a productive Dip from a dead end, and run a 30-day market test.
Jonathan Courtney's Strategy Signal funnel rebuilt as a transparent case study: 19K opt-ins, 8,423 buyers, $405K front-end revenue, $1.2M backend sales, hidden advantages, and a responsible six-week build plan.
Wes Roth's Qwen3.8 Max roundup rebuilt as an evidence audit: long-horizon agent results, benchmark limits, the confirmed COLDCARD RNG flaw, and the unproven AI-attribution claim.
Malva AI's Vheer tutorial rebuilt as a current guide to the real zero-credit image and video routes, prompt patterns, limits, commercial rights, privacy, and the paid Higgsfield alternative.
Elon Musk's motivational advice rebuilt as a practical operating system for focus, useful risk, first-principles thinking, strong teams, recovery, and meaningful work.
Google AI Mode is increasingly citing Google-hosted business cards for local-intent queries. Here is why your Business Profile has become part of your AI discovery layer, and what to fix first.
Greg Isenberg's framework rebuilt as a practical guide to jobs, arrows, shared state, parallel research, checks, loops, and human approvals.
How Mads Lorentzen turned Claude Code into a job-search agent: fit scoring, tailored applications, independent review, interview prep, and honest tracking.
Every post here is about a system that actually shipped. Book a free call and let's talk about what could ship for you.
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