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        AI
        HomeAIPage 2

        Category: AI

        Vibe coding scales until it doesnt
        DevelopmentAI
        May 5, 2026By Doug Saltzman

        Vibe Coding Scales… Until It Doesn’t

        The speed is real.

        I want to say that upfront because this isn’t a post about why AI-assisted development is dangerous or overhyped. We use it and it’s changed how fast we can move and for certain things that’s been genuinely valuable.

        I’m writing this because we’ve had a version of the same conversation three or four times in the last year with founders who built something fast, launched it, grew it, and then hit a wall that cost them significantly more to fix than it would have cost to avoid.

        The pattern is always roughly the same.

        It starts with the demo working.

        Week one is great. The thing runs and it does what it’s supposed to do. The AI helped you move fast and the fast movement felt like the right call because you needed to validate the idea before investing heavily in the infrastructure.

        That part is fine.

        That part is actually correct.

        Then you add one more feature.

        And another. And a third-party integration because the native solution was going to take two weeks and the bolt-on took two hours. And a workaround that one developer understood completely but never wrote down because there wasn’t time.

        None of these decisions are wrong in isolation. Each one made sense given the deadline, the budget, the priorities that week. The problem is that they compound. Every shortcut that worked in the demo becomes an assumption baked into the system. Every undocumented decision becomes a puzzle for whoever touches the code next. Every patch that fixed the immediate problem without addressing the underlying one sits there quietly until something forces the reckoning.

        The reckoning usually arrives when you hire someone or when traffic spikes or when a client asks for something that should be simple and suddenly nothing is simple.

        By that point the person who understood how everything fit together has mentally moved on. The system works until it doesn’t and when it stops working nobody knows where to start. What you have isn’t a product anymore. It’s a patchwork that requires institutional memory to operate.

        That’s when you call someone like us and we look at it and have to tell you that the fix costs more than the original build.

        Engineering discipline doesn’t mean slow.

        It doesn’t mean months of planning before you write a line of code. It means someone on your team is thinking one level above the immediate problem.

        What does this decision mean three months from now?

        What would a new developer need to know to understand why this works the way it does?

        What are we cutting corners on intentionally versus accidentally?

        Those questions don’t take long and skipping them consistently is what gets expensive.

        Build fast. Use the tools. Ship the damn thing. Just make sure what you’re building can carry the weight of what you keep adding to it.

        We build and maintain web and platform systems for growing businesses. If your stack is starting to feel held together with good intentions, let’s talk.

        Read More
        Person digging through citations
        AISEO
        April 28, 2026By Doug Saltzman

        What Actually Gets Cited by ChatGPT (We Studied the Patterns)

        Everyone is writing “What is GEO” guides right now.

        Almost nobody is actually studying what ChatGPT cites, or why.

        So we did. Across dozens of commercial queries in our clients’ industries, we pulled the sources ChatGPT returned, compared them against traditional Google rankings, and looked for the patterns. Here’s what showed up in almost every answer.

        The #1 Predictor Isn’t What You Think

        If you had to guess, you’d probably say domain authority, or backlinks, or some algorithmic edge case only Neil Patel understands.

        It’s not.

        The single strongest predictor of whether a page gets cited by ChatGPT is structural clarity. Simple explanation is whether the page is built in a way an LLM can actually extract from. A Princeton, Georgia Tech, and Allen Institute for AI study found that 32.5% of AI citations come from comparison articles, not because comparison articles are better written, but because they’re structurally easier for a model to chunk.

        Domain authority helps, but a clean Reddit thread will get cited over a DR 85 marketing blog if the Reddit thread answers the question in 60 words and the marketing blog buries it in paragraph nine.

        Five Patterns We Saw Repeatedly

        01: The answer lives above the fold.
        Every cited page we studied had a direct, definitional answer in the first 100 words. Not an intro or a hook. A straight-up declarative sentence that a model could lift verbatim. If your content opens with “In today’s rapidly evolving landscape…” you are already out of the running.

        02: The entities are specific and named.
        Cited pages named the tools, the people, the studies, the companies, the frameworks. Vague pages lost every time. “Enterprise marketing platforms” gets beaten by “HubSpot, Marketo, and Salesforce Marketing Cloud.” The model cites the one that lets it build a knowledge graph.

        03: The structure is chunkable.
        H2s that ask the question a user would ask. Short paragraphs (3–5 sentences). Bulleted lists where bullets actually stand alone. If you have to read 400 words to extract a 50-word answer, the model won’t bother. It’ll cite the page that already did the extraction for it.

        04: Recency matters more than depth on fast-moving topics.
        For anything time-sensitive (prices, policies, product releases, 2026 trends), ChatGPT and Perplexity heavily favor content updated in the last 90 days. A thin but fresh article will beat a deep but stale one. This isn’t fair, but it’s how the systems behave.

        05: The page exists as a node, not an island.
        Cited pages link out to authoritative sources (studies, official docs, named experts) and link internally to related content. They behave like nodes in a knowledge graph, which is exactly what models are modeling. Orphan pages get ignored no matter how good they are.

        What This Means for Your Content

        Stop writing for humans who might skim.

        Start writing for models that will extract.

        This doesn’t mean robotic content, it means content with enough structural integrity that both a reader and an LLM can find the answer they came for in under 10 seconds. The best cited pages we saw were genuinely useful to humans and easy to chunk. Those aren’t competing goals anymore.

        The practical shift:

        • Lead every section with a standalone answer:
          A 40-60 word block that works if pulled out of context.
        • Name specific entities:
          No “leading CRM platforms.” Say HubSpot, Salesforce, Pipedrive.
        • Update aggressively on fast-moving topics:
          If your post says “2024 trends” in April 2026, it’s not getting cited.
        • Build clusters, not islands:
          Pillar + spoke structure. The system rewards topical density.
        • Treat structured data as a required input, not an optional nice-to-have:
          Schema gives the model the map.

        The Bigger Shift

        The agencies that figure this out in the next 18 months will build the category.

        The ones that don’t will keep sending ranking reports to clients whose traffic is getting quietly rerouted into AI answers they don’t show up in.

        We track both for our clients. If you want to see what your brand looks like inside ChatGPT, Perplexity, and Google AI Overviews, before your competitors do, that’s what we do.

        You’re not ranking anymore. You’re being cited… or you’re not.

        Read More
        You’re Not Ranking. You’re Being Indexed.
        SEOAI
        April 21, 2026By Doug Saltzman

        You’re Not Ranking. You’re Being Indexed.

        If your SEO strategy still involves a spreadsheet of keywords and a density percentage, you are optimizing for a version of the internet that no longer exists.

        In 2026, the gap between keyword-centric and entity-centric optimization has become a divide. Search engines don’t match strings anymore, they comprehend concepts. They don’t count how many times you say a word, they measure the salience of your entities.

        What is Entity Salience?

        Salience is a technical score (usually between 0 and 1) that an algorithm assigns to a specific person, place, or concept within your content. It’s a measure of how central that thing is to the meaning of your page.

        Google and the LLMs (Perplexity, Gemini, etc.) aren’t just scanning for the phrase “GTM strategy.” They are looking for the surrounding entities that prove you actually know what a GTM strategy is. Here’s what they’re actually looking for.

        • The Connective Tissue:
          Are you mentioning Customer Acquisition Cost, LTV, and Sales Velocity in the same breath?
        • The Hierarchy:
          Is your primary entity in the H1, or is it buried in the 3rd paragraph?
        • The Semantic Net:
          Are you providing enough attributes (founding dates, specific frameworks, proprietary data) for the machine to verify you aren’t just hallucinating?

        The Logic of the Knowledge Graph

        This is where the And Zeros philosophy hits the metal. Think of the internet as one giant knowledge graph… a web of nodes and relationships.

        When you publish a page, the goal isn’t to rank. The goal is to be indexed as a definitive node.

        If your content is vague or uses AI-slop adjectives, your salience score drops. The machine can’t figure out if you’re an authority or just a noise generator (but email me if you want to nerd out on noise generators.) If you use Structured Data to explicitly declare your entities, you are handing the machine a map. You’re telling it, “This node is the Founder, this node is the Framework, and they are connected by this Relationship.”

        Engineering for Extraction

        In the era of GEO (Generative Engine Optimization), you have to write for extraction. AI models don’t read your whole article; they chunk it.

        • The Answer-First Block:
          Start every section with a 50-word direct answer to the heading. This increases the salience of the entity in that section and makes you 10x more likely to be cited in an AI Overview.
        • Topical Integrity:
          Stop writing scattered posts my friend! If you want to own a topic, you have to build a cluster. 1 pillar page (the hub) and 10 supporting pages (the spokes). This tells the system that your domain isn’t just a site, it’s a topical authority.
        • Entity Resolution:
          Use consistent naming. If you’re “Samantha Smith” on your blog but “S. Smith” on LinkedIn, you’re making the machine work too hard. Consistency is a trust signal.

        Stop Counting, Start Connecting

        The Keyword Era (RIP) was about volume. The Entity Era is about Density and Relationship.

        If you provide the cleanest, most interconnected data, the gatekeepers will have no choice but to use you as their source. You aren’t just playing the game anymore, you’re providing the board.

        In case you haven’t figured it out yet, SEO isn’t dead—it’s the future. And that future is built on entities, not strings.

        Read More
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