Field notes from the AI search frontier.
We Ran Our Own Page Through an E-E-A-T Auditor and Scored 61
We ran the page we use to sell AI search work, search.agency/ai-search, through StoryMint's E-E-A-T Auditor, and it came back with a 61 out of 100. Fair, not good. E-E-A-T is Google's shorthand for Experience, Expertise, Authoritativeness, and Trust.
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How to Build SEO Into Your Go-to-Market Strategy (Not Bolt It On Later)
Build SEO into your go-to-market plan the way you build in sales or paid: as a demand channel with a job to do, sequenced to your company stage, anchored to a real buyer and a real pain, and now optimized for AI answer engines as well as the ten blue links. The startups that treat search as a launch-day input win compounding pipeline. The ones that treat it as something to switch on later spend year two paying for the months they skipped.
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The Startup Founder's Guide to Realistic SEO ROI in Indonesia
SEO can be one of the highest-return channels an Indonesian startup ever builds, and it can also quietly burn six months of budget before it returns a single qualified lead. Which one you get depends almost entirely on whether you understood the shape of the return before you committed to it.
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How to Run a Persona-First Content Gap Analysis With StoryMint
A persona-first content gap analysis finds the questions your audience is asking that the current search results fail to answer. That is a different exercise from the gap analysis most teams run, which finds the keywords competitors rank for and you do not. Both go by the same name. Only one of them tells you what to actually say.
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Decision Frameworks Are the Content Format AI Search Rewards
A decision framework is a piece of content that walks a reader through choosing between options, scored against weighted criteria so the tradeoffs are explicit instead of implied. It is also one of the most reliably cited formats in AI search, because it answers the exact shape of question generative engines are built to resolve.
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No Two AI Engines Read Your Prompt the Same Way
Type one sentence into an AI engine and it almost never searches for that sentence. It quietly rewrites your prompt into a handful of other queries you never see, runs them, reads what comes back, and hands you a single answer stitched from sources you were never shown choosing. That hidden step is where AI visibility is won or lost, and most GEO advice skips straight past it as if every engine did it the same way.
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What Screaming Frog Can Really Do Once You Connect It to Claude
Most Screaming Frog tutorials stop at broken links and missing meta descriptions. That is the warm-up. The tool earns its license fee on the layer underneath, the canonical logic, the rendering gaps, the international signals, and above all the moment you stop treating the crawl as the answer and start treating it as one input among several. On enterprise sites, the real wins live where crawl data meets Semrush and Search Console.
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Enterprise GEO: How to Roll Out AI Search Optimization Across a Large Site
Enterprise GEO is the practice of operationalizing generative engine optimization across a large site, so that thousands of pages, multiple teams and several markets all produce content that AI engines can cite, consistently and at scale. On a small site, GEO is a checklist you apply by hand. On an enterprise site, the same checklist applied page by page never finishes, so the work shifts from doing GEO to building the system that does GEO for you.
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Governing AI-Assisted SEO Content at Enterprise Scale
A human directs, AI accelerates, a human verifies. Enterprises that wire that loop into roles, guardrails and pipeline checks get the speed of AI with the quality their rankings and brand depend on. Those that skip the bookends get volume that quietly erodes both. If you want help designing and running that governance model, that is part of what [our AI search team in Indonesia](/ai-search-agency-indonesia) does.
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AI SEO Tools for GEO: What an Enterprise Stack Actually Needs
For an enterprise SEO team, the AI tool worth buying is not the one with the slickest demo. It is the one that fits your existing stack, holds up across thousands of pages and several markets, and produces output your governance process can stand behind. Judged that way, the tools that help a GEO program fall into four jobs: finding the right questions, structuring content for extraction, automating schema and technical hygiene, and monitoring whether engines actually cite you. The category that creates the most risk is the fifth: AI writing at volume.
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