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Published by Slobodan "Sani" Manić
AI is changing the internet, and nobody asked us if we wanted it changed. So every week I go and look at one thing it did: a website that started charging robots to read it, an assistant that got turned away at the door and answered anyway, a company that promised something a year ago and can't show a receipt. Then I tell you whether it's good, bad, or pointless, and what to do about it, whether you use the web or build it. Around fifteen minutes per episode, usually me on my own, with occasional guests. Hosted by Slobodan Manic, a CXL-certified conversion specialist, WordPress Core Contributor, and the creator of Machine-First Architecture, the framework for building websites for the agentic web.
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On August 5 Shopify switched on a second way into every store on its platform, built for AI agents instead of people. Nothing to install, no merchant asked. I opened three unrelated stores, Allbirds, Brooklinen and Partake Foods, and asked each what it could do for a machine. All three answered with the same roughly 800 words, identical character for character, and no merchant wrote a syllable of it. What those words say, and what it costs a brand when the visitor has no eyes. Chapters 00:40 Thirty years of every shop trying to sound different 02:13 What Shopify switched on, overnight, on every store 03:19 Three stores, one identical answer 05:06 The tools are stage direction for a machine 08:13 Nobody is using any of it yet 13:45 Your voice does not transmit, your data does Key Numbers Three unrelated stores returned the same ~800 words of tool text, identical character for character The adapter file is version 0.1.0 Etsy put AI agent platform traffic under 1% of its total in Q2 earnings Shopify reports AI- referred orders tripled, which is referred traffic, not agents buying Shopify reports over a million merchants on the platform Three Takeaways Shopify wrote what your store says to machines, and every other store says it too. These are instructions, not descriptions. The checkout tool tells the agent to "follow it." Another tells it not to ask the shopper about missing options when it decides they only want to look. Someone chose when the customer gets consulted, and it was not the customer or the merchant. This is the right way to build it, which is separate from whether anyone noticed. The tools read the same database as the storefront people see, so the two cannot drift apart. One good default beats a million bad ones. It is still worth knowing a default was set for you. If the machine is the visitor, your voice does not transmit and your data is what is left. The photography, the badges, the reviews, the copy someone agonised over: none of it survives the call. Back comes a title, a price, a size run, availability. What is left to compete on is whether your prices are right and your stock is accurate. That work pays off whether or not the agents arrive. Mentioned My WebMCP reference guide: https://nohacks.co/blog/what-is-webmcp What I found on day one: https://nohacks.co/blog/shopify-gave-every-store-an-agent-api Shopify's docs for building the buyers: https://shopify.dev/docs/agents Talia Wolf and the Emotional Targeting Framework Episode 229, llms.txt against 137,000 domains Newsletter, one a week: https://nohacks.co/subscribe Say hello: hi@nohacks.co No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
Most of what's sold as AI search optimization has never been tested by the people selling it, and this episode is me checking the biggest one against server logs. Ahrefs looked at 137,000 domains in June: 97% of llms.txt files got zero requests in May, and the biggest readers of the rest were SEO audit tools. I also lay out the line I use to sort every pitch: a hack tries to influence what the machine says about you, architecture changes what a machine can read and do on your website. Chapters 00:00 The AI optimization economy and its zero evidence 02:50 llms.txt checked against 137,000 domains 06:00 The main readers of llms.txt are SEO audit tools 08:53 Why this market keeps producing hacks 10:23 Visibility scores and the prompt problem 12:43 Every generation of hacks dies the same way 15:08 What survives model updates 18:39 The mirror: fix what the internet thinks you are Key Numbers 137,000 domains in Ahrefs' June 2026 server-log study 28% had a valid llms.txt file, and that number is the ceiling, their customers skew technical 97% of those files got zero requests in May, not low traffic, zero Of the 3% that got fetched, around 22% of the readers were SEO audit tools, the tools that flag you for not having the file My own Cloudflare logs at nohacks.co show the same thing, nobody fetches it Three Takeaways The pitch is a screenshot, the truth is in the logs. Before you pay for any AI visibility work, ask for evidence at the level of server logs, and watch what happens. A hack tries to influence what the machine says about you. Architecture changes what a machine can read and do on your website. The first is rented and dies at the next model update, the second is owned. LLMs are a mirror of everything happening online. If ChatGPT doesn't call you the best X for Y, the honest question is whether the internet agrees you are, and that's the problem worth fixing. What to Do Sort anything you bought or got pitched this quarter with one question: does it change what a machine can read and do on the website, or what the machine says about it? Ask any vendor for their evidence before money leaves your account. Logs, tests, a mechanism, the same bar you'd use for anyone touching revenue. Check your own server logs for who actually fetches your llms.txt, it takes five minutes Try this: open free ChatGPT logged out of search, type "what is [your name] known for," and send me the screenshot at hi@nohacks.co. I want to see what you get. Sources Ahrefs llms.txt server-log study (June 2026): https://ahrefs.com/blog/llmstxt-study/ My identity-vs-capability piece: https://nohacks.co/blog/agentic-web-identity-vs-capability Weekly newsletter: https://nohacks.co/subscribe No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
I came back from a month off the grid to find OpenAI had killed Atlas, its most glamorously launched product, nine months after the keynote. It barely matters, though. The automated, non-human visitor Atlas was sending to your website is still coming, through whatever shell comes next. Build for the visitor, not the browser. Timestamps 00:00 - Back from break, and the bad news 01:17 - Atlas: the most hyped browser ever launched 02:27 - Watching it work is a demo, not a workflow 03:29 - Killed with no keynote: the browser was never the product 04:35 - The visitor isn't dead, so build for it 05:24 - The real agentic web: background agents you don't watch 07:52 - Silent failure: a human recovers, an agent doesn't 09:41 - OpenAI's side quests, and the name that gave it away 12:48 - My Cloudflare data: AI traffic is 5-10x human 14:24 - What No Hacks is now Key Numbers AI assistant traffic (ChatGPT and Claude users) is running 5-10x my human traffic on nohacks.co (my own Cloudflare AI analytics) Atlas: launched October 2025, shuts down August 9, 2026, nine months old Eight months in, Atlas never shipped beyond macOS, no Windows, iOS, or Android Key Takeaways The visitor outlives the shell. Browser, app, extension, cloud: the wrapper keeps changing, but the automated visitor arriving at your website is the same one every time. Build for the visitor, not the browser. Watch-it-work AI browsers were always a demo. If you have to sit and watch it, it is not a workflow. The real agentic web runs in the background, which means its failures are silent, and you never see the lost signup or sale. Being cited is not the whole game. The agent does not only mention you, it comes to your website and tries to act. Optimizing to appear in a prompt misses the harder work: a website a machine can actually use. What to Do Simplify the paths a human muscles through but an agent will not: coupon-box bugs, cookie banners, console errors. The agent hits the wall and leaves, silently. Check your own logs and bot analytics for AI-assistant traffic. You are probably getting more than you think. Stop optimizing only to be discovered. Make the website something an agent can finish a task on. More on this every week in the No Hacks newsletter: nohacks.co/subscribe Sources & Links The story OpenAI is shutting down Atlas (TechCrunch) My companion take and data AI Browsers Are Backward Because Agents Never Needed the Visual Layer Cloudflare Radar: bot and AI traffic No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
I sat down with Malte Landwehr, who left VP of SEO at Idealo to become CPO and CMO at Peec AI, the platform that tracks what ChatGPT, Claude, Gemini, and Google AI Overviews actually cite. We open on the strangest finding of the year. GummySearch, a Reddit analytics tool that shut down last November, now sits behind about 0.1% of all ChatGPT citations. From there we get into why clicks are the wrong way to measure AI search, why your local brand keeps losing to US ones, why scaled AI content rockets then crashes, and why Malte says SEO is dead as a default growth channel. Guest Profile Malte Landwehr is CPO and CMO at Peec AI, an AI search visibility platform that runs daily prompts across ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude, and Grok. He spent more than twenty years in search and product, including five years as VP of SEO at Idealo and five years as VP of Product at Searchmetrics. In his first six months at Peec AI, the company grew from roughly $500K to $5M in ARR. Chapters [0:00] Intro [1:15] Leaving one of Europe's best SEO jobs for AI search [5:07] Why clicks are the wrong way to measure ChatGPT [8:22] Which answer engines actually matter [12:34] GummySearch: a dead product winning ChatGPT citations [18:33] Listicles and the English-language fan-out bias [23:48] Advertorials, local results, and Mount AI content [33:50] Digital PR over technical SEO [36:27] ChatGPT Shopping is scraped Google Shopping, and the MCP contest [42:16] SEO is dead as a default channel, and the chunking move Key Takeaways Stop measuring AI search by clicks. In an LLM, clicking is optional, so ChatGPT can look like 1% of your traffic while shaping most of your buying journeys. Measure the influence on the decision, not the visit. What gets written about you offsite now matters more than your own technical SEO. Grounding pulls from Reddit, G2, Wikipedia, YouTube, and news, so digital PR is the bigger lever for how AI describes and recommends you. One citable paragraph beats a chunked article. Put your main claim near the top in two or three declarative, self-contained sentences that name the entities. Do not shred a whole article into one-line bullets. Notable Quotes "In a web search, clicking is part of the intended user journey. In an LLM, clicking is completely optional." Malte Landwehr "They didn't gain visibility as a brand. They now have power over what brands are recommended by LLMs." Malte Landwehr, on GummySearch Resources Peec AI: https://peec.ai Peec AI research blog: https://peec.ai/blog Malte Landwehr's website: https://www.maltelandwehr.de Future of AI Shopping webinar with Malte Landwehr (Peec AI): https://peec.ai/webinars/future-of-ai-shopping Connect Malte Landwehr on LinkedIn: https://www.linkedin.com/in/landwehr/ Peec AI: https://peec.ai No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
This week I welcome Alisa Scharf, Chief AI Officer at Seer Interactive, to the podcast, to ask the question she fires back at every client who walks in wanting to "win at AI visibility." Her answer flips the whole project: fix what the models get wrong about you before you chase the category terms. We got into her research on why lower-authority websites earn more citations, why LLMs recommend a brand only 2.3% of the time, and the gap nobody is tooling for: getting an agent to actually use your website, not find it. About the Guest Alisa Scharf is Chief AI Officer at Seer Interactive, where she runs the AI practice across the agency's client accounts. Her team's research spans hundreds of thousands of pages and tens of thousands of prompts, and she argues that citations are a leading indicator, not a business outcome. Chapters 00:00 - The first question Alisa asks a new client 04:08 - Brand accuracy: what models get wrong about you 06:57 - Defense wins championships 09:54 - The brand accuracy audit 13:12 - Why lower-authority websites get cited more 15:57 - Citations are page two of Google 19:37 - LLMs recommend a brand 2.3% of the time 21:49 - The agentic browsing tooling gap 28:13 - Losing 30-80% of organic traffic 37:31 - How a 15-year-old brand catches up 40:24 - What we will get wrong in 12 months 43:18 - Where to find Alisa Key Takeaways Defense before offense. Pick five factual prompts about your own company, founding, location, what you sell, who you compete with, and run them across ChatGPT, Claude, and Gemini. Fix what the models get wrong before you spend a dollar chasing category terms. Citations are a leading indicator, not a result. They swing by month and by model. Real success shows up in direct traffic, branded search, and brand recognition, none of which sit neatly on a dashboard. Visibility is not readiness. Getting cited and getting an agent to actually buy, book, or provision on a customer's behalf are two different problems. Most providers sell the first and call it the second. Notable Quotes "You can flip an old house and turn it into a really impressive place to live. You can't flip an old house and turn it into a skyscraper." "Everything we just spent the last 10, 15, 20 years learning is now doing you a disservice, because you really have to turn to a fresh page and say, where is my audience?" Resources Seer Interactive: https://www.seerinteractive.com Seer insights and research: https://www.seerinteractive.com/insights No Hacks EP 222, Wil Reynolds, AI visibility is a vanity metric: https://nohacks.co/episode/222-ai-visibility-is-a-vanity-metric-with-wil-reynolds No Hacks EP 225, Matt Biilmann on agent experience: https://nohacks.co/episode/225-every-website-already-has-an-agent-experience-and-most-are-bad-with-netlify-ceo-matt-biilmann SparkToro: https://sparktoro.com Connect with Alisa Scharf LinkedIn: https://www.linkedin.com/in/alisascharf/ X: https://x.com/alisa_scharf Bio: https://www.seerinteractive.com/people/team/alisa-scharf No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
The user-agent string in the HTTP header has been there since the 1990s. The web was built with software navigating it on someone's behalf. For thirty years that someone was a human. That changes now. Matt Biilmann, CEO and co-founder of Netlify, was one of the first to take seriously what it means when the "user" navigating the web is an AI agent. He published the foundational essay on Agent Experience in January 2025, pivoted his entire company around it, and recently shipped netlify.ai as a separate entry point built for agents. We cover the four pillars of Agent Experience, why every product already has an agent experience whether you designed one or not, content negotiation as a way to tell agents to go to a different URL than humans, why SaaS is in real trouble (with a story from inside Netlify about ripping out vendor contracts), how the data-structure assumption that has defined software for fifty years is breaking, and the one thing every website owner should start doing this week. About the Guest Matt Biilmann is the CEO and co-founder of Netlify, the platform that started the Jamstack movement and is leading the shift from developer experience to agent experience. His January 2025 essay on Agent Experience is the foundational text for the discipline. Chapters 00:00 Every product has an agent experience (cold open) 00:35 The architectural question 01:46 Welcome Matt to No Hacks 02:15 When AX became a design constraint, not a concept 06:44 The January 28 2025 essay and who got it first 10:22 Why netlify.ai was built as a separate website 12:44 Content negotiation: telling agents to go to a different URL 13:54 Qualitative data and the Axis eval framework 17:12 Does AX apply to e-commerce and content websites? 20:59 The cumulative media argument (TV did not kill radio) 25:00 User-agent in HTTP and Al Gore-era agent commerce laws 26:33 SaaS business model is dead: build-vs-buy is shifting 30:44 The end of structured content as a hard constraint 40:25 One thing every website owner should do now 43:08 Where to find Matt online Key Takeaways Every website already has an agent experience. Agent Experience is how AI agents currently interact with your product, whether through computer use, fetching, or working around the barriers you put up. It is not a feature you add. The only question is whether the experience is good or bad. The four pillars: Access, Context, Tools, Orchestration. Matt's framework for thinking about AX systematically. Access answers whether agents can reach your product at all. Context is the prompt-engineering equivalent for agents. Tools are the concrete capabilities you expose. Orchestration covers how agents string those tools together inside your product. Build a separate entry point for agents. netlify.ai is purpose-built for agents while netlify.com remains the human entry point. Content negotiation tells agents to go to one URL, humans see the other. The blessed-path approach beats trying to make one URL serve both. SaaS economics are shifting structurally. The build-vs-buy floor is dropping fast as AI lowers the cost of software. Traditional 90%-margin seat-based SaaS is in real trouble. Dev tool companies have upside because companies need more tools. Everyone else is going to be ripping out vendor contracts and building internally. The data-structure paradigm is breaking. Software engineering has operated on the Linus Torvalds principle that data structures matter more than code. LLMs are not built around data structures. Building software around LLMs means rethinking the assumption that drove fifty years of computer science. Notable Quotes "Every product has an agent experience because all of these agents, whether through computer use or through fetching your website or through working around the barriers you put up from them, have some agent experience right now. It is just a question of is it good or bad." "There is a reason it is called a user agent in the header. It was forward-looking." "We have been ripping out SaaS contracts. Sometimes it is heartbreaking. The rep calls to right-size the contract and the customer reacts with 'let me see if I can build it with an agent.' Then they call back and cancel instead." "The context and the flows and your creativity are probably more important than both the data structures and the code." What To Do Next Open your website in Claude Code or ChatGPT and ask the agent to complete a real task. Watch where it stalls. That is your AX baseline. Check your traffic logs for AI assistant visitors (ChatGPT-User, Claude-Web, PerplexityBot, GPTBot). The number is rising whether you measure it or not. Cloudflare reports AI assistants are now 5.5% of all internet traffic, up from 3.9% six months ago. Read Matt's January 28 2025 essay on Agent Experience at biilmann.blog as the starting point. Then read the one-year retrospective for the four pillars framework. If you operate a developer tool or any product with a clear automation surface, start a simple eval scenario: take a fresh agent, give it a task, score whether it succeeds. Axis from Netlify will give a proper framework when it ships open source. Resources Mentioned netlify.ai (the agent-built entry point Matt and team shipped recently) netlify.com (the human entry point) Matt's original Agent Experience essay, January 28 2025: biilmann.blog Matt's "AI in the CLI: The Humanoid Robot of the Web" (August 2025) Claude Code (the agent that flipped broad accessibility for CLI coding agents) Connect with Matt Biilmann Blog: biilmann.blog LinkedIn: linkedin.com/in/mathias-biilmann-christensen-a5a3805 Twitter/X: @biilmann (x.com/biilmann) Bluesky: bsky.app/profile/did:plc:grjr4il5dredrsuj7nosb4pq Mastodon: mastodon.social/@biilmann Netlify: netlify.com and netlify.ai Connect with No Hacks Website: nohacks.co Subscribe to the newsletter: nohacks.co/subscribe Machine-First Architecture: machinefirstarchitecture.com No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
We are significantly closer to movie Her than we were just 6 months ago. Most coverage reads Google's last six months as a string of independent product updates. They aren't. Read together, they're the whole agentic-web stack closing one component at a time. Tuesday's Gemini Intelligence on Android announcement named the keystone - the first OS-level web-agent integration any company has built. Chrome auto-browse lands on Pixel 10 and Galaxy S26 in late June. This episode walks through the six-month assembly (Chrome auto-browse, AppFunctions, AI Mode in Chrome, "Ask Google", web.dev agent-friendly guidance, Gemma 4 + Gemini Nano 4, UCP, A2A, Gemini Intelligence Android, DeepMind AI Pointer), the durability question I can't fully answer yet (five-year moat or six-month head start before Apple closes it), and the audit any website needs to pass once an agent can operate it on a user's phone. Timestamps: 00:00 - 10 Google moves in six months 04:53 - Walking the six-month assembly, January through this week 06:51 - The full stack: action, agent-to-app, transaction, identity, distribution, input 09:01 - Late June: what changes for a salon owner with a booking website 10:32 - The durability question: Apple's six-month gap, not a five-year moat 15:47 - Machine-First Architecture: three visitor classes you have to design for 16:19 - Google's seven rules. nohacks.co passed six. Tailwind 4 broke one. 17:32 - The test you can run today: disable JavaScript, try to complete a booking 20:53 - A few days to fix it. The cost of waiting is unknown. Weekly breakdown of how the agent-web is assembling, every Wednesday: https://nohacks.co/subscribe The Machine-First Architecture framework: https://machinefirstarchitecture.com Sources mentioned in this episode: DeepMind AI Pointer (May 13): https://deepmind.google/blog/ai-pointer/ Gemini Intelligence Android (May 12): https://blog.google/products-and-platforms/platforms/android/gemini-intelligence/ Chrome auto-browse preview (January): https://blog.google/products-and-platforms/products/chrome/gemini-3-auto-browse/ AppFunctions for Android (February): https://developer.android.com/ai/appfunctions Google web.dev - "Build agent-friendly websites" (April): https://web.dev/articles/agent-friendly-websites Universal Commerce Protocol: https://ucp.dev/ Related reading on No Hacks: Selling to AI: The Complete Guide to Agentic Commerce - https://nohacks.co/blog/agentic-commerce Google's Agent-Friendly Checklist Has 7 Rules. Tailwind v4 Breaks One. - https://nohacks.co/blog/google-agent-friendly-checklist Amazon v. Perplexity: The CFAA Case That Decides Whether AI Agents Can Visit Your Website - https://nohacks.co/blog/amazon-perplexity-cfaa-agent-visitor-rights No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
I ran the Cloudflare Agent Readiness scanner on nohacks.co, got 33 out of 100, and felt insulted. One toggle later the score was 67. That gap is where this episode starts. My case: the web is splitting into two economies. A retailer-friendly agentic web where AI-referred traffic now converts 42 percent better than human traffic. And a page-view-driven publisher web losing 20 to 90 percent of its Google traffic in a year. This split is structural, not a rebalancing. Chapters: 00:00 Opening 00:41 The 33, then 67 score on nohacks.co 02:46 The thesis: the web is becoming two webs 03:55 Cloudflare Agents Week: 28 shipments in five days 05:35 The data stack: Adobe 393%, the conversion inversion, publisher declines 10:08 The mobile-first parallel 11:21 Why this split is permanent 13:12 The "publishers will adapt" and licensing-deal rebuttals 17:02 Three sector-specific moves 19:34 Closing: run the scanner, reply with your score Key Numbers Cloudflare shipped 28 agent-infrastructure pieces during Agents Week (April 13 to 17, 2026) AI traffic to US retailers grew 393 percent year over year in Q1 2026 (Adobe) AI-referred traffic converted 42 percent better than non-AI in March 2026, after converting 38 percent worse in March 2025 Google traffic to publishers down 33 percent globally; some local publishers down 25 to 90 percent Automated traffic growing 8× faster than human traffic year over year Three Takeaways The split is structural, not a rebalancing. Retailers fit the agentic web because agents complete the same action the website wants. Page-view publishing does not, because the agent summarizes instead of sending a human to see an ad. The composite score is a trigger, not a target. Ignore the number. Read the per-check list and fix the signals that ship against real agent runtimes today. Watch the infrastructure before the mainstream catches up. The mobile-first rebuild shipped years before the indexing caught up. This is the same gap, different shape. What to Do Run isitagentready.com on your website. Toggle the category, re-run, compare. Transaction-driven revenue: agent readiness is tied to revenue. Fix the checks that ship against real agent runtimes now. Page-view-driven revenue: model your P&L with 30 percent less traffic this quarter. If it breaks the business, start diversifying today. Reply to the newsletter with your score. I read every reply. Sources Cloudflare Agent Readiness Score Adobe Q1 2026 AI Traffic Report via TechCrunch Publisher traffic drop (Press Gazette) What is the Agentic Web (nohacks.co) No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
Wil Reynolds, founder of Seer Interactive, shares how losing 80% of organic traffic actually revealed that his team had been tracking the wrong metrics for years. We get into why AI visibility is a vanity metric, how 44% of LLM users include brand names in their prompts, the real security risks of wrong phone numbers in AI answers, and why trust (not visibility) is the only moat that matters. Chapters 00:00 - 80% traffic drop, pipeline went up 06:43 - The pressure of experimental channels with real budgets 08:28 - AI visibility is a vanity metric 13:49 - People are tracking the wrong prompts 17:15 - AI is getting your phone number wrong (and scammers know it) 22:30 - Trust vs visibility: the real optimization target 30:26 - Trust is a moat, hacks mortgage your brand 32:20 - Be seen, be believed, be chosen 44:15 - What digital marketers should do right now 49:33 - Where to find Wil Key Takeaways Traffic is no longer the leading indicator - Seer lost 80% of their organic traffic over two years. Pipeline went up. Social converts at 5x organic. The correlation between search traffic and revenue has broken for many businesses AI visibility is a vanity metric - When ChatGPT doubles the length of an answer, your "visibility" goes up without any more humans seeing you. If visibility grows but leads don't, you're the sucker. Track visibility against your pipeline, not in isolation 44% of LLM users put brand names in their prompts - Wil's team watched real humans use LLMs and found nearly half include specific brands. Head-to-head brand comparisons are the prompts worth tracking, not generic category queries Trust is the only real moat - Michelin built a restaurant guide in 1900 that still drives foot traffic and pricing power. RAMP launched 52 AI-generated restaurant pages in a day. One is rotisserie chicken made by a chef. The other is a chicken nugget. Both are chicken, but only one builds trust Be seen, be believed, be chosen - Visibility gets you in the room. But if people Google your team and nobody shares their content, if you're not speaking at conferences, if your newsletter has no engaged readers, belief falls apart. Trust transfers from people, not listicles Concepts Discussed Three Types of AI Search | Search-led (web index + AI), answer-led (hybrid with tool use), and fully generative (training data only). Each requires different optimization. Training Data Lag | Gemini 3.1 launched with training data from January 2025, a 16-month gap. Work done since then has zero provable impact on training-data-based answers. Brand-in-Prompt Behavior | 44% of observed LLM users include brand names in their prompts. Changes the optimization target from "show up for generic queries" to "win head-to-head comparisons". Phone Number Hallucination | LLMs serve wrong phone numbers for businesses, creating fraud exposure. Especially dangerous for financial services targeting elderly customers. Recommended Stack Visibility | AI coding tools recommend tech stacks from training data. Being the default recommendation in Claude Code or Codex creates durable, hard-to-displace visibility. Connect with Wil Reynolds LinkedIn: linkedin.com/in/wilreynolds LinkedIn Newsletter: Thinking Out Loud Seer Interactive: seerinteractive.com No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
In 2009, Luke Wroblewski's "mobile first" changed how every website gets built. Start with the harder constraint, and the rest gets better. Now the harder constraint is not a small screen. It's no screen at all. Sani introduces Machine First Architecture, a four-pillar framework covering everything from how you define your business to how machines interact with your website. Identity, structure, content, interaction. In that order. Chapters 00:00 - Introduction: The Mobile First Parallel 01:24 - Why Machine First Follows the Same Pattern 05:09 - Pillar 1: Identity 08:05 - Pillar 2: Structure 12:34 - Pillar 3: Content 15:20 - Pillar 4: Interaction 19:29 - Why This Matters Now 22:30 - One Action Per Pillar 24:30 - Closing Key Stats Brands on 4+ platforms are 2.8x more likely to appear in ChatGPT responses, but only with consistent identity (Digital Bloom) 70%+ of Google's first page results use schema markup Pages with 19+ verifiable data points averaged 5.4 AI citations vs 2.8 for pages with minimal data (SE Ranking, ~130K domains) 96% of AI Overview content comes from sources with verified E-E-A-T signals AI browser traffic to US retail sites increased 4,700% YoY in July 2025 (Adobe Analytics) Key Takeaways Machine first is the new mobile first. What works for a parser works for humans. The reverse is never true. Identity comes before optimization. You need a canonical, structured definition of your business before you touch anything else. Your website is a data model, not a wireframe. The page is a rendering of structured data. Machine-critical info goes at the top. Content must be answer-first and verifiable. Machines evaluate the first few hundred words. Vague marketing copy is invisible. Machines are not just reading your site, they're using it. Agents shop, book, and fill out forms. Visual-only confirmations and modal pop-ups break them silently. Every agent failure is invisible. The agent moves to a competitor. You never see the lost transaction. What to Do (One Action Per Pillar) Identity: Write your canonical definition as fields. Google your business name. Fix every platform that tells a different story. Structure: Disable JavaScript and visit your site. If content disappears, you're invisible to most AI crawlers. Content: Read the first paragraph of your key pages. If it doesn't state what the page is about, rewrite it. Interaction: Complete a core action on your site using only a screen reader. If you can't finish the flow, an agent can't either. Links Machine First Architecture: machinefirstarchitecture.com Subscribe: nohacks.co/subscribe No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
Google was granted patent US 12536233B1 in January 2026, describing a system that scores your landing page and, if it falls below a quality threshold, replaces it with an AI-generated version personalized to each searcher. This episode breaks down how the patent works, how the industry reacted, and what website owners should do to prepare. Chapters 00:00 - Introduction 01:24 - How the Patent Works, Step by Step 04:26 - How the Industry Reacted 06:46 - What This Actually Means 07:57 - Ads First, Everything Else Later 08:58 - Google's Data Advantage 10:13 - Your Website Is Becoming a Warehouse 11:10 - The Measurement Problem 12:28 - Connection to Agentic Browsers and Web MCP 13:38 - What You Can Do About It 15:19 - Closing Key Statistics Patent US 12,536,233 B1 approved January 2026, priority date July 2024 ( USPTO ) Patent filed by six Google engineers: Karen Zhang, IL Grover, Timothy Benjamin Wallen, Lauren Marjorie Bedford, Avi Sadan, and Ethan Milo Landing page score based on conversion rate, bounce rate, click-through rate, and design/content quality assessments AI pages can include product feeds, CTA buttons, chatbot functionality, personalized headlines, filters, and suggested products Key Takeaways The patent is real, and the scope is clear - Google has patented a system to score landing pages and replace underperforming ones with AI-generated versions personalized to each user's search history and context. It starts with ads, but that's the playbook - The patent explicitly references sponsored content items. Google has a history of introducing features in ads first, then expanding (see: Google Shopping's evolution from free to paid). Google has a data advantage no one can match - The system uses full search history, previous queries, click behavior, location, and device data. No advertiser has access to that level of personalization. Your website is shifting from storefront to warehouse - Brands become suppliers of data while Google owns the customer experience. Your product feed and structured data become the front door to your business. The technology is category-agnostic - The patent focuses on shopping today, but scoring a page and replacing it with an AI version is a technique that applies to any content type. The question is when it expands, not whether. Action Items Checklist Treat your product feed like your homepage: accurate, complete, detailed specs, pricing, stock levels, high-quality images Invest in structured data and machine-readable content so AI-generated pages based on your data are correct Build direct audience relationships: email lists, community, direct traffic, brand reputation Monitor your landing page quality scores in Google Ads Read the patent yourself to understand exactly what Google is describing Listen to the Browser Wars episode for context on agentic browsers and Web MCP Listen to the Duane Forrester episode on trust as the most important signal for AI Sources & Links The Patent US Patent 12,536,233 B1 - AI Generated Content Page Tailored to a Specific User Episode URL: https://www.nohackspod.com/episode/220-google-patented-replacing-your-landing-page-with-ai No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
Rand Fishkin, co-founder of SparkToro and one of the most influential voices in digital marketing history, shares research proving that AI brand recommendations are wildly inconsistent. You'd need to ask ChatGPT 1,500 times to get the same brand list in the same order twice. We discuss why AI ranking tools are selling metrics that don't exist, why Google is still 210x bigger than ChatGPT, and why brand building (not digital marketing tricks) is the real lever for AI visibility. About the Guest Rand Fishkin - Co-founder & CEO of SparkToro, co-founder of Moz and Alertmouse, author of "Lost and Founder" Chapters 00:00 - Intro 01:04 - The best thing AI has brought online 02:51 - The AI inconsistency research: 1,500 prompts for the same list 06:17 - Why AI tracking tools give you a false sense of visibility 09:16 - Is AI search actually better than Google? 11:34 - Kung Pao Chicken vs Peanut Butter: prompt variability 16:26 - What AI tracking should actually measure 20:16 - Why the best brands weren't built on digital marketing 22:43 - AI as "Spicy Autocomplete": where the hype exceeds reality 25:17 - Why AI cannot be creative 28:58 - Google is still 200x bigger than ChatGPT 31:28 - Two ways to show up in AI: base models and RAG 34:34 - Brand mentions as the real lever for AI visibility 38:10 - Zero-click marketing and the death of traffic as a metric 41:47 - Why SEO careers are more important than ever 44:39 - What brands should actually do first in March 2026 48:10 - The one thing about AI that should be killed today 52:02 - Where to find Rand Key Takeaways AI rankings don't exist Visibility percentage is the real metric Brand mentions drive AI visibility The best brands weren't built on digital marketing Your homepage is not your homepage anymore SEO is more important than ever, but the metric changed RESOURCES: Rand's AI Inconsistency Research: https://sparktoro.com/blog/new-resear... SparkToro (audience research): https://sparktoro.com Alertmouse (brand mention monitoring, free): https://alertmouse.com Connect with Rand on LinkedIn: https://linkedin.com/in/randfishkin Episode URL: https://www.nohackspod.com/episode/219-your-homepage-is-not-your-homepage-anymore-with-rand-fishkin No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
Five years. 218 episodes. 110 hours of content. To celebrate, five returning guests flip the script and interview Sani about the agentic web, the future of web optimization, and what makes this podcast tick. Kelly Wortham, Iqbal Ali, Talia Wolf, Jon MacDonald, and Shiva Manjunath each bring their own questions, their own perspectives, and a few personal ones too. Chapters 00:00 - Five years of No Hacks 01:33 - Kelly Wortham: Why the shift to the agentic web? 05:17 - Kelly Wortham: The secret to being a great podcast host 08:57 - Iqbal Ali: Why Web MCP is a big deal 12:23 - Iqbal Ali: What excites you about 2026? 13:58 - Talia Wolf: What everyone misses about optimizing for AI agents 15:33 - Talia Wolf: The misleading advice in the industry 18:19 - Jon MacDonald: Why brands need agentic web data now 25:38 - Jon MacDonald: NBA All-Star Weekend hot takes 29:22 - Shiva Manjunath: The skeptic's case against agentic web hype 37:56 - Shiva Manjunath: If you were a meme 38:37 - What's next for No Hacks Key Takeaways AI middleware is coming to every interaction - Chrome has 3 billion browsers, Apple is putting AI into Siri across every device. There will be an AI layer between every user and every website. This is not five years away. It is happening now. Web MCP could make the agentic web actually work - Current AI agents take 3-5 minutes to fill a basic form on well-coded pages. Web MCP provides a standard interface between your front end and AI agents, making interactions reliable regardless of your HTML quality. Optimizing for AI agents is not a separate discipline - A fully functional website built for humans gets you 80-90% there. Accessibility, semantic HTML, schema markup, fast load times. All the basics you felt bad about skipping? They matter now more than ever. Citation tracking in LLMs is misleading - Prompting an LLM 100 times and averaging your position to 4.7 is not useful data. The rankings model does not translate to AI. Bing Webmaster Tools just launched AI tracking in beta, and Google will have to follow. That is when real measurement begins. Getting ready for AI agents means making your website better for humans - There is not a single reason not to do it. Better technical health, better standards compliance, better user experience. The work is the same. This is not about websites going away - Stores did not go away when e-commerce arrived. Websites will not go away when AI agents arrive. But there is a new channel, and if your site is not ready for it, you can disappear from discovery entirely. Guest Hosts Kelly Wortham Founder of the Test and Learn Community (TLC). Asked about the shift to the agentic web and what makes a great podcast interviewer. Iqbal Ali Experimentation and AI consultant, founder of Ressada. Asked about Web MCP and what excites Sani about 2026. Talia Wolf CRO expert, founder of GetUplift, author of "Emotional Targeting." Asked about what people miss when optimizing for AI agents and what common industry advice is wrong. Jon MacDonald Founder of The Good, author of three books on website optimization. Asked about why agentic web data matters for brands and shared NBA All-Star Weekend hot takes. Shiva Manjunath Host of the From A to B podcast. Brought the skeptic's perspective on agentic web hype and asked what meme Sani would be. No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
In the 1990s, Microsoft and Netscape fought for control of the browser, the gateway between humans and the internet. Netscape went from 90% market share to zero in five years. Now, with over 30 agentic browsers launching in under 18 months, the same war is playing out again, only this time the stakes are higher. This episode breaks down the 90s browser wars, compares the tactics to what's happening today, and explains what website owners should do about it. Key takeaways The playbook hasn't changed - Bundling, free products, proprietary lock-in, and distribution deals decided the 90s browser wars. The same tactics are playing out with agentic browsers today. Google is running Microsoft's 1995 playbook - Microsoft embedded IE into Windows to protect its OS monopoly. Google is embedding Gemini into Chrome to protect its search monopoly. The browser is the defensive weapon, not the product. The Chromium trap is deeper than IE bundling ever was - Most agentic browsers (Comet, Atlas, Neon) run on Google's Chromium engine. Even competitors are built on Google's foundation. The prize shifted from attention to transactions - The 90s fight was about what people see. The agentic browser fight is about what AI agents buy, book, and do on your behalf. Your website is the new Netscape - If AI agents mediate every user interaction, your site risks becoming invisible infrastructure rather than a destination. Regulation will be too late - The DOJ took 6 years to settle with Microsoft. Netscape was already dead. The same timeline is playing out with Google's antitrust case. What to do today Don't optimize for one agentic browser. Build for web standards: semantic HTML, ARIA labels, structured data, server-side rendering. Build direct audience relationships (email, communities, subscriptions) so you're not dependent on browser intermediaries. Make your site worth visiting, not just worth scraping. Offer value an AI agent can't replicate. Treat accessibility as an agent strategy. Screen reader compatibility = AI agent compatibility. Test your site with an agentic browser to see what works and what breaks. Read the full agentic browser landscape breakdown: nohackspod.com/blog/agentic-browser-landscape-2026 Chapters 00:00 - Introduction 01:34 - The First Browser War 09:15 - The Agentic Browser Explosion 12:48 - Why Is This Happening Now? 16:15 - Where the 2026 Version Gets Worse 21:27 - What This Means for Your Website 23:14 - What to Do About It 26:49 - Closing Connect Website: https://nohackspod.com LinkedIn: https://www.linkedin.com/in/slobodanmanic/ Newsletter: https://nohackspod.com/subscribe Episode URL: https://www.nohackspod.com/episode/217-the-browser-wars-are-back-this-time-with-ai-agents No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
Duane Forrester, 30-year search veteran who co-launched Schema.org and built Bing Webmaster Tools, explains why AI systems prioritize trust above all else. We discuss machine comfort bias, chunk-level content optimization, why SEO is now a multidisciplinary role, and how to prepare for a world where LLMs decide who gets cited. About the Guest Duane Forrester is the author of "The Machine Layer" and search industry pioneer 30 years in search and digital strategy Senior Product Manager at Microsoft - built Bing Webmaster Tools Co-launched Schema.org structured data standard Leadership roles at Bruce Clay Inc. and Yext Founder of Unbound Answers, creator of CitationIQ Chapters 00:00 - Intro 01:01 - The biggest shift SEO has ever seen 03:30 - Machine Comfort Bias: the 5 layers of trust 09:19 - Chunking: writing for AI and humans 16:01 - Making content citation-ready 18:35 - Schema.org : the trust infrastructure 25:46 - Ironman vs Superman: AI as amplifier, not savior 32:28 - EEAT, Universal Verifiers, and why trust is everything 42:59 - Latent Choice Signals: the invisible metrics 52:35 - The Machine Layer book 57:53 - Emerging roles in AI discoverability 01:01:16 - Where to find Duane Key Takeaways Trust is the new algorithm - LLMs need multiple dimensions of verification before citing you. If you can provide everything they need without them having to guess, they'll lean into that "machine comfort bias" Chunking matters, but not how you think - Don't reformat your entire page into 300-word blocks. Instead, put key facts, figures, and bullet points at the top. LLMs get "lost in the middle" of long-form content Be the canonical source - Your goal isn't rankings, it's being seen as THE source of knowledge on your topic. If you haven't expanded the LLM's training data with net new information, you won't be cited SEO is now multidisciplinary - Technical SEOs must understand branding, conversion, engagement, PR, and UX. Silos are killing companies in the AI discovery layer AI is Ironman, not Superman - These systems amplify your skills but require you to drive them. Hope is not a strategy. Always ask self-referencing questions to verify outputs LLMs want to save money - They won't waste tokens looking elsewhere if you provide everything they need. Consistency and trust reduce their computational costs Resources Mentioned Duane's Work Book: The Machine Layer - Available on Amazon (Kindle & Paperback) Website: duaneforrester.com - Free frameworks from the book available Substack: duaneforresterdecodes.substack.com LinkedIn: linkedin.com/in/dforrester Connect with No Hacks Website: https://nohackspod.com Newsletter: Subscribe for weekly episodes Episode URL: https://www.nohackspod.com/episode/216-the-machine-layer-building-trust-in-the-age-of-ai-search-with-duane-forrester No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
Your website might rank #1 on Google but be completely invisible to ChatGPT, Claude, and Perplexity. In this episode, let's break down why a huge chunk of the web is fundamentally broken for AI systems - not because of bad content, but because of technical decisions that made sense for humans but make sites invisible to the AI systems rapidly becoming the front door to the internet. Chapter Timestamps 00:00:00 - Introduction: The new game your website is losing 00:01:43 - The Scale of the Problem: AI crawler traffic explosion 00:05:19 - The JavaScript Problem: Why AI crawlers can't see your content 00:10:28 - The Bot Protection Paradox: Accidentally blocking AI 00:14:40 - The Speed Requirement: Why 200ms matters 00:17:46 - AI Agents Are Struggling Too: Browser agents and their limitations 00:20:46 - How to Fix It: 6 things you need to do 00:25:33 - Closing: The web is adapting again Key Statistics 569 million GPTBot requests on Vercel's network in a single month 370 million ClaudeBot requests in the same period 305% growth in GPTBot traffic (May 2024 to May 2025) 157,000% increase in PerplexityBot requests year-over-year 33% of organic search activity now comes from AI agents ~40% failure rate for the best AI browser agents on complex tasks The 6 Things to Fix Implement Server-Side Rendering (SSR) - If your site uses a JavaScript framework (React, Vue, Angular) with client-side rendering, switch to SSR or static site generation immediately. Use Next.js, Nuxt, or a pre-rendering service. Add Structured Data with JSON-LD - Expose key information in machine-readable format using schema.org markup. Microsoft confirmed Bing uses this to help Copilot understand content. Optimize for Speed - Target server response time under 200ms. First Contentful Paint under 1 second. Largest Contentful Paint under 2.5 seconds. Check Your Bot Protection Settings - Review Cloudflare, AWS WAF, or your CDN's bot management. Make a deliberate decision about GPTBot, ClaudeBot, and PerplexityBot access. Kill Infinite Scroll and Lazy Loading for Content - Use paginated URLs with standard HTML links. Ensure high-value content is in the initial HTML response. Keep Sitemaps Current - Maintain proper redirects, consistent URL patterns, and fix broken links. Tools Mentioned Glimpse - Free tool to test how AI sees your website: glimpse.webperformancetools.com Show Links Sources Referenced in This Episode AI Crawler Statistics: Vercel Blog - The Rise of the AI Crawler Cloudflare 2025 Year in Review Cloudflare - From Googlebot to GPTBot Search Engine Land - AI Optimization Guide JavaScript Rendering: Prerender.io - Understanding Web Crawlers Search Engine Journal - Enterprise SEO Trends 2026 Episode URL: https://www.nohackspod.com/episode/215-the-agent-broken-web-why-ai-cant-see-your-website No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
Google just made two massive moves in 48 hours, and together, they could reshape how AI interacts with commerce forever. First: the Universal Commerce Protocol (UCP), an open standard that lets AI agents shop on your behalf. Discovery, checkout, payments, post-purchase, the whole journey, with one common language. Backed by Shopify, Walmart, Target, Visa, Mastercard, and 20+ others. Second: a multi-year deal with Apple. Gemini will power the next generation of Apple Intelligence, including Siri. That's Google's AI running on 2 billion Apple devices. In this episode, I break down what UCP actually is, how it works, why the Apple deal matters, and what this means for merchants, developers, and anyone building for the agentic web. CHAPTERS 00:00 – The Anthony Joshua smile meme (and what it has to do with Google) 02:59 – The landscape: AI agents, fragmentation, and the assistant wars 06:36 – What is UCP? Universal Commerce Protocol explained 11:04 – Who's backing UCP and what it enables today 14:21 – The Apple-Gemini deal: what it means 17:55 – Why Apple chose Google (and what happens to OpenAI) 21:00 – Connecting the dots: Google's full strategy 24:00 – What this means for merchants and developers 26:30 – The bigger picture: who controls the agentic web? 29:07 – Closing thoughts LINKS UCP Documentation: https://ucp.dev UCP GitHub: https://github.com/Universal-Commerce-Protocol/ucp Google's UCP Announcement: https://blog.google/products/ads-commerce/agentic-commerce-ai-tools-protocol-retailers-platforms/ Google-Apple Joint Statement: https://blog.google/company-news/inside-google/company-announcements/joint-statement-google-apple/ Shopify's UCP Deep-Dive: https://shopify.engineering/UCP KEYWORDS/TAGS Google, UCP, Universal Commerce Protocol, AI agents, agentic commerce, e-commerce, Apple Intelligence, Gemini, Siri, AI shopping, MCP, Shopify, OpenAI, retail technology No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
For the last 20 years, digital marketing had one goal: drag a human across a "threshold", onto your website, so you could control the message and sell the product. In 2026, the threshold is gone. In this episode, Jono Alderson argues that we have entered the era of "Marketing to Machines." We are no longer optimizing for clicks; we are optimizing for the AI agents that intermediate the web. We discuss why 90% of websites are now "Zombies" (technically online but functionally dead), why AI models treat marketing fluff like an allergen, and why the future of SEO isn't about meta tags, it's about "Upstream Engineering." In this episode, we cover: [00:00] The Death of the Threshold: Why the era of "interrupting humans to get them to your site" is over. [02:24] The Surface-less Web: Why your brand is no longer just your domain, but an aggregation of everything said about you on the web (Reddit, YouTube, 2013 microsites). [06:52] The "Zombie Web" Theory: Why "commodity content" (like generic dentist blogs) is worthless to an LLM that has already memorized the facts. [11:05] The Machine Immune System: Why AI models view persuasive copywriting and sales fluff as "noise" or hallucinations to be filtered out. [16:40] The Incoherence Penalty: How machines spot the gap between your marketing claims ("We love customers") and your reality (bad Reddit reviews). [20:30] The llms.txt Trap: Why creating a separate "agent-friendly" version of your site won't work (and why machines won't trust it). [22:50] MCP (Model Context Protocol): Is this the future of how websites communicate? [28:14] Upstream Engineering: The new SEO. Why you need to optimize your return policy, logistics, and customer service instead of your title tags. [33:05] The Timeline: The best and worst-case scenarios for the web in the next 5 years. [38:39] How to Survive 2026: One final piece of advice for optimizers. Resources: Connect with Jono: jonoalderson.com Follow Jono on LinkedIn No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
If 2025 felt like a constant, high-pitched ringing in your ears, you aren't alone. We call it "Digital Tinnitus", the exhausting result of two years of AI hype, "pivot or die" mandates, and confident mediocrity. In this 2025 finale, let's shut off the noise. We look back at why "Fatigue" was the word of the year, and why the crash of the hype cycle is actually the best news for serious professionals. Sani breaks down why Deep Work is the only antidote to the chaos and reveals the massive strategic shift coming to No Hacks in 2026. The internet is changing. We are moving from an Attention Economy to a Utility Economy. And next year, we focus on one thing only: The Non-Human User. In this episode, we cover: The Hangover: Why 2025 broke us, and why the silence of 2026 is a gift. Deep Work vs. Shallow Hacks: Why "Vibe Coding" is a trap and true craftsmanship is the only moat left. The 82:1 Prediction: Palo Alto Networks predicts 82 AI agents for every 1 human online. What does that mean for your website? The 2026 Mission: Announcing the sole focus for next year: Optimizing the Human Web for Non-Human Users. Links: Connect with Sani on LinkedIn: https://www.linkedin.com/in/slobodanmanic/ Subscribe to the Newsletter: https://nohacks.substack.com/ See you in 2026. No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
The ground beneath the digital marketing industry is shifting. For decades, the mantra was simple: optimize for traffic, measure clicks, and track conversions. But with the rise of Generative AI, Large Language Models (LLMs), and Answer Engines, that rulebook is obsolete. In this powerful episode, I sit down with Joe Doveton to discuss the urgent reality facing every brand that relies on web traffic. We dive into the phenomenon Joe calls the "Crocodile Mouth", the unsettling visual trend where brands maintain high search impressions but see clicks vanish, a direct result of zero-click searches. With the proliferation of platforms like TikTok, Reddit, and various generative engines, we discuss why the Google monopoly on the customer journey is over, and how users can now move from the awareness stage to purchasing a product without ever visiting a Google property. This episode is a wake-up call for marketers still clinging to outdated KPIs. Joe introduces the new alphabet soup of optimization, GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), and LLMO (Large Language Model Optimization) . Crucially, we explore what this means for your analytics. If traffic and conversion rate are "lousy metrics", what should you measure? Joe reveals emerging metrics like Visibility within LLMs and competitive positioning. Most importantly, we agree that this "Wild West" era is finally killing all the outdated SEO hacks, forcing brands back to the core long-term strategy: writing useful content and focusing on the customer experience. About the Guest Joe Doveton is an experienced digital strategist, consultant, and speaker focused on the intersection of AI, search, and customer experience. With a background that includes working in advertising and a deep understanding of Conversion Rate Optimization (CRO), Joe is now pioneering tools and strategies for the Generative Engine Optimization (GEO) space. He is the founder of GEO Jet Pack , a platform designed to extract and visualize entities from content to help brands gain visibility in LLM responses - a critical new metric for the AI era. What You'll Learn The difference between traditional SEO and the new acronyms: GEO, AEO, and LLMO . What the "Crocodile Mouth" is and why it confirms the end of the reliance on clicks. Why the old marketing KPIs, specifically web traffic and conversion rate —are now "lousy metrics" for measuring success. The new metrics emerging for the middle of the funnel, such as Visibility within LLMs and competitive position within prompt responses. Why the entire AI shift proves that long-term SEO success is still about being useful, interesting, and trustworthy (EEAT). Why the current AI era is killing all the old SEO hacks and discouraging tactics like content farming. How and why brands like Google are undermining their own profitable ad business by integrating AI Overviews. The vision of the Semantic Web and why the current structure of websites is inherently ill-suited for machine consumption. Guest Contact: Joe Doveton's website Joe Doveton on LinkedIn No Hacks runs no sponsorships and is funded by advisory and audit work. If your website needs to work for machines as well as people, start with a fixed-scope Machine-First Architecture audit: https://nohacks.co/audit
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