G8N•AI Podcast

About G8N•AI Podcast

GenerationAI • Focus with Intention and Leverage with AI Building in Public • Custom vibe-coded AI tools www.g8n.ai (https://www.g8n.ai?utm_medium=podcast)

Publisher

Ahad Amdani

Category

education · technology

Language

en

Explicit

Yes

First episode

28 Nov 2025

Latest episode

18 Sept 2026

Latest episodes

20 episodes in the feed.

1. 

   18 Sept 2026

   They Draft. I Speak.

   My agents wrote the first draft of this newsletter. Not one of them is allowed to post a comment underneath it. That sounds like a small distinction. It’s the most load-bearing rule in my whole operation, and it’s the one I get asked about least. Last week a writer I follow, Claudia Faith (https://substack.com/profile/174269834-claudia-faith) , posted a note that got more engagement than anything else she published that week. Forty-two reactions, ten replies. It said, roughly: use AI for your writing, your images, anything you like, but please don’t use it to write comments under other people’s posts. The same week, Wyndo (https://substack.com/profile/556836-wyndo) , who writes carefully about working with AI, credited an AI content system for keeping his publishing consistent. Both of those people are right, and neither of them says where the line is. That’s the part worth writing down, because I’ve had to find it the expensive way. What actually goes wrong when a tool speaks for you? Here’s the specific thing that happened to me, and the numbers are exact because I counted them: a tool of mine posted the same comment on one of my own posts four separate times. That tool posts the first comment on my own LinkedIn posts, five minutes after they go live. The comment is written by me, approved by me, and sits in a file. The tool’s only job is to wait and paste. Once at the right moment, then again a day later, then again, then again. Four identical copies under a post where a real person, Luke Beck, had left two genuinely useful pieces of advice. He was having a conversation with me and my tooling was talking over it. The cause was dull, which is how these things usually go. After posting, the tool checked whether its comment was visible, couldn’t find it within four seconds, and reported failure. The comment had been live since the first attempt. Anything that retried on that failure posted again. Nobody was harmed. But the shape of it’s the thing: a piece of automation with permission to speak, a verification step that couldn’t see the truth, and a public surface where the mistake is already in front of someone by the time you learn about it. Why is drafting safe when speaking isn’t? Because a draft has a gate after it and a comment doesn’t. If an agent writes me a bad post, I read it and delete it, and the total cost of that failure is my attention for nine seconds. Nobody knows it existed. The gate sits between the machine and the world, and everything upstream of the gate is cheap to get wrong. A reply in someone else’s comments is already in front of them by the time I see it. There is no gate after the fact. There’s only an apology, and an apology costs more than the comment was ever worth. That asymmetry is the entire argument. Two jobs that look similar from the inside, because both of them are just producing text, carry completely different risk the moment you ask where the undo button is. So the rule I run is that the machines produce and a human speaks. I call it the Approval gate, and it’s the one piece of my system I’ve never been tempted to loosen. Where does the Approval gate actually sit? It helps to be concrete, because “a human in the loop” is the kind of phrase that means nothing until you say exactly which loop. My agents draft LinkedIn posts, Substack notes, and this newsletter. They file records, take locks so two of them can’t work the same day, refuse malformed input from each other, and run every morning without me in the room. I haven’t opened the thing that makes them in weeks. Not one of them can send a message to a person. The first comment is pre-written by me and approved before the post exists. The direct messages have a hard ceiling that lives in a config file, three connection requests and five messages a day in the first week, and the first ten sends on any platform each need individual approval before the eleventh is allowed to go automatically. Replies to real comments I write myself, by hand, usually slower than I’d like. The gate isn’t a feeling. It’s a list of things that are allowed to reach a person without my eyes on them, and the correct length of that list, for almost everybody, is zero. How do you decide what an agent may do on its own? Most people aren’t deciding this at all, and there’s a number for it. Teleport’s 2026 Infrastructure Identity Survey found that 70% of organizations grant AI systems more privileged access than a human would get in the same role. 51% said slightly more. 19% said significantly more. Nearly one in five is handing software more reach than the person whose job it’s doing. That’s not a trust problem. It’s a nobody-drew-the-line problem. I stopped thinking about this as one permission and started thinking about it as five, in order of how expensive the mistake is: * Reading is free. An agent that reads my calendar, my repository, my own published work or a public feed can be wrong and the cost is a wasted minute. Everything I own reads without asking. * Writing for me is nearly free, because of the gate. Drafts, notes, summaries, a proposed reply I haven’t sent. All of it lands somewhere I look before anyone else does. * Writing to my own systems is where it starts to matter: filing a record, moving a card, closing a task. A mistake is recoverable but not free, because now something downstream believes a thing that’s not true. This is the layer where I’ve spent the most time building checks that refuse bad input from other agents. * Acting on outside systems is the first genuinely sharp edge. Publishing a post, sending a scheduled note. I allow it, narrowly, and only for content that already passed the gate as a draft. The agent isn’t deciding what to say. It’s executing a decision I already made, at a time I already picked. * Speaking to a person is the one I don’t automate. Not comments, not replies, not messages. The useful part of that list isn’t my particular answers. It’s that the question has five answers instead of one, and 70% of organizations are still treating it as a single switch labeled “do you trust AI?” What does this cost? More than I’d like, and I’d rather say so than sell you a version where it’s free. It costs me speed. I answer my own comments, which doesn’t scale and never will. Some days I’m late, and being late to a comment thread on LinkedIn is expensive in a way the platform makes very clear: it costs me reach I could technically have. There are tools that would engage on my behalf all day, and some of them would probably work for a while. What it buys is narrow and, I think, worth it: every conversation anyone has had with me on these platforms was actually with me. When Luke told me to brand my images and to drop a popup that was blocking crawlers, he was talking to a person who could act on it, and both things shipped that week. That exchange doesn’t survive being automated. It’s the whole reason the account is worth anything. Is this just a taste preference? No, and I want to separate the two, because taste is where this argument usually goes to die. Claudia’s objection reads partly as taste. She doesn’t want her comment section filled with generated warmth, and I agree with her. But the reason I hold the line is mechanical rather than aesthetic. It’s about where the undo button is. You can test it without any philosophy. For any automation you own, ask one question: if this produces something wrong at three in the morning, what does the recovery look like? If the answer is “I delete a file,” you can let it run. If the answer is “I apologize to someone,” it doesn’t speak without you. That test doesn’t care how good the model is. A better model lowers how often you need the recovery. It doesn’t change what the recovery is. What I’m not claiming I’m not claiming AI-written comments never work. Plenty of people are doing it and getting engagement. I’m claiming that the engagement isn’t the thing being risked, and that people who measure only the engagement won’t see the cost until it arrives attached to a name they wanted to keep. I’m not claiming my setup is the right one for you. Mine is shaped like my work, which is one person with a lot of automation and a small audience where individual relationships matter more than volume. If you run a support desk, your line sits somewhere completely different, and it should. And I’m not claiming I drew this line on principle. I drew it after four identical comments under a post where someone was trying to talk to me. Do this to one automation today Open whatever tool you’re using that touches other people. A scheduler, an auto-responder, a comment tool, an agent with an integration you set up once and stopped thinking about. Find the exact place where it can reach a person without you looking first. There’s usually one, and it’s usually not where you expected, because it got added later for convenience. Then decide, in writing, whether it stays. Ten minutes. If it stays, write down what happens when it’s wrong, and who apologizes. I’m Ahad Amdani, I write G8N•AI, and the Approval gate is the rule I’d keep if I had to throw the rest of the system away. Get full access to G8N•AI at www.g8n.ai/subscribe (https://www.g8n.ai/subscribe?utm_medium=podcast&utm_campaign=CTA_4)

2. 

   11 Sept 2026

   AI Will Cite You Without Ever Naming You

   Everything I’d learned about writing to be found turned out to be aimed at the wrong reader. For twenty years the reader was a crawler. You wrote for a machine that matched strings, and the craft was getting the right phrase in the right places often enough to be counted. That reader’s gone, and what replaced it does something the crawler never did: it reads your page, takes what it needs, and answers the question itself. I went looking for what actually works now, because I was about to spend real time on it. What I found wasn’t a list of tactics. It was a shape. Getting found by AI is three separate contests, not one. You can win any of them and lose the others, and almost nobody is competing in all three, because most people don’t know the second and third exist. Here’s the shape, then the evidence for it, then what I’d do about each stage. The three contests * Retrieval. Does the engine consider your page at all? * Lift. Once it’s looking, does it take anything from your page? * Attribution. Once it’s used your material, does the reader learn your name? Different things win each one. That’s the whole insight, and it’s why “do good SEO” is now advice about one third of the problem. Does Google rank decide whether AI cites you? I assumed the pages AI cites were roughly the pages Google ranks. They aren’t close. Ahrefs looked at the thousand most-cited pages in ChatGPT, part of about a billion data points they worked through this year. 28.3% of those pages have zero organic visibility in Google. The overlap between ChatGPT’s results and Google’s top ten organic is 6.82%. If you’ve been using your Google rank as a proxy for whether AI will cite you, that proxy is about 7% accurate. The mechanism underneath is stranger and more useful. Among cited pages, 65.3% sit on high-authority domains, while 67.3% of those same pages have almost no page-level authority of their own. Read that twice. The domain matters enormously. The individual page’s backlinks barely matter at all. Which inverts a decade of advice. The old play was to build links to the one page you wanted ranked. The new one is to get the domain trusted, then publish the specific page and stop worrying about whether anyone links to it directly. That’s genuinely good news for a small operator publishing consistently on one domain, and bad news for anyone whose whole strategy was a single heavily-linked cornerstone page. What to do: stop optimizing individual pages for links. Publish consistently on one domain you own and let the domain carry the pages. And know that a page can earn citations while ranking nowhere, which means your analytics will under-report this entirely. Contest two: lift is won by material a model can safely reuse Once you’re in the consideration set, something has to be worth taking. The foundational study here is GEO, for Generative Engine Optimization, out of Princeton and IIT Delhi and presented at KDD in 2024. They tested nine content modifications across roughly ten thousand queries and measured which made a page likelier to show up inside an AI-generated answer. Three things won: citing sources, adding quotations, and adding statistics. Together the best techniques lifted visibility by up to 40%. I’ll be careful with that number, because almost nobody who quotes it is. 40% is the maximum that study found, not the average. It gets passed around like it’s a floor. It’s a ceiling. The loser is the more useful half. Keyword stuffing came in around minus 9%, and roughly 10% worse than baseline on Perplexity. The technique that defined this discipline for a decade doesn’t just stop working. It costs you. That paper’s two years old, which in this field is a long time, so I checked whether it still holds. It does, and the newer work is more specific: structural rewrites on their own, meaning sectioning, fact placement and list use, lifted citation rates by 17.3%. You don’t have to change what you think. You have to change how it’s arranged on the page. There’s a format finding too, and it’s uncomfortable if you write essays. Ahrefs found “best X” listicles are the single most-cited content format in ChatGPT, at 43.8% of cited page types. What to do: put liftable units in your writing. A sourced number, a named authority, a sentence precise enough to quote. Then arrange them so they’re findable: real sections, facts near the top of their section, lists where the content is genuinely a list. And accept that some of your best material will get lifted from a format you find “beneath” you. Why does being cited so rarely turn into being named? This is the part that re-organised how I think about all of it, and it’s the contest nobody is playing. GPO published research in August 2026 with a finding I haven’t stopped thinking about since. When a brand’s own content was cited as a source inside an AI Overview, that brand was still left out of the model’s actual recommendation 69% of the time. Read that again. Your page is good enough to be the source. The answer’s built out of your work. And then the model recommends somebody else. The same research measured how badly old signals transfer: * Brands appeared in Google’s local 3-pack 35.9% of the time. * ChatGPT recommended those same brands 1.2% of the time. * Gemini 11%. * Perplexity 7.4%. For the same brands, that’s roughly a thirty-to-one gap between ranking and being recommended. Semrush and Kevin Indig found the adjacent version in June, looking at 3,981 domain appearances across 115 prompts, fourteen countries and four engines. They called them ghost citations: the answer links your page as a source and never says your name in the text a human actually reads. That was 61.7% of citations. Ghost citations are real. So you can win contests one and two completely, supply the entire answer, and still leave the reader with no idea who you are. What to do: make your name inseparable from your best claim. Not in the title tag, in the sentence. If the liftable line is “the fifth step is the one people skip,” you get cited. If it’s “the fifth step of the 5 Ds is the one people skip,” the thing that travels is yours. Name your frameworks. Put your own name in the prose. A claim with a name welded to it is the only unit that survives summarization intact. The theory, in one paragraph Domain trust gets you considered. Liftable material gets you used. A named claim gets you credited. They’re three different jobs, they’re won by three different things, and the last one is both the least worked on and the one that decides whether any of it turns into a reader who knows your name. If your traffic is flat but your ideas keep showing up in other people’s mouths, you’re winning the first two and losing the third. That’s the most common shape I see, and it’s the one that feels like failure while actually being most of the way there. The audit I run now I ran this on the piece you’re reading and it failed five of six checks on the first pass. * Is there a claim here specific enough for an answer to lift and cite? * Does that claim carry the name or idea I want remembered? * Is my own name in the prose, not just the metadata? * Are the numbers sourced, in the text, where a model can attribute them? * Do the headings ask questions the section beneath actually answers? * Have I named a concept I own? That last one is the item that pays most and the one nobody does. The fifth matters more than it looks: question headings help, but only where the section genuinely answers the question. The research is explicit that a question a section doesn’t answer is the trick that doesn’t work, which is the rule most advice in this area gets backwards. I’m Ahad Amdani, I write G8N•AI, and this audit is now the last thing that happens before anything goes out. What I’m not claiming I’m not claiming this makes you rank. Nobody’s got a formula that guarantees an AI retrieves, cites or recommends you, and anyone selling one is ahead of the evidence. The Ahrefs data is one vendor measuring mostly ChatGPT. The GEO study is two years old. Treat all of it as a working theory that’s better than the one you had, not as physics. I’m also not claiming the old work was wasted. The same ingredients that make a page citable, clear evidence and a claim that survives outside its paragraph, are what make it trustworthy to a person. That’s the part I find genuinely reassuring: what works on the machine is what was always good writing. Do this to one page today Open an article you actually want people to find. Circle every sourced number, every named authority and every sentence that could be lifted whole. Then check whether a single one of them says who you are. If it hasn’t got any, you have a contest-two problem and the fix is material. If it’s got several but none carries your name, you have a contest-three problem, which is the more interesting one and the one 69% of cited brands have right now. If you want the how rather than the what, that’s a conversation. Reply to this and tell me which of the three you’re losing, and I’ll tell you what I’d change first. Get full access to G8N•AI at www.g8n.ai/subscribe (https://www.g8n.ai/subscribe?utm_medium=podcast&utm_campaign=CTA_4)

3. 

   3 Sept 2026

   Your Claude Setup Will Be Gone in Two Years. The Design Underneath It Won’t.

   I could lose every tool I use tomorrow and be back at work by the weekend. Not because I keep backups. Because none of them holds the thing that matters. The chat app, the task board, the AI model, the place my writing goes. I can throw all of it away and the system I built keeps working. I set it up that way on purpose. It’s close to the opposite of the advice everyone’s giving right now. Here’s my system with no product names in it Five helpers: * One remembers everything and decides what happens next. * One writes and sells. * One looks things up. * One argues with the others and checks whether what they said is true, and it’s not allowed to rewrite anything, so its complaints stay complaints. * One keeps track of what’s waiting on me. Work shows up and becomes a card. Every card says who it’s for, what it’s for, and what’s happened to it so far. Every single action gets written down as one line: the card, the action itself, who did it, and when. Nothing goes out to real people without me. On the path that messages strangers, that gate is strict in a specific way: the send tool looks up each message and refuses unless it finds a yes recorded by a person, and a yes written by a tool is thrown out. On the publishing path, it’s a quieter thing: a button only I can reach. Different strengths, same rule. Read that again and notice what’s missing. No brand names. No AI model. No app. Two of those five have been running for months. The other three are new, added in the last few days, and here’s the part that matters: adding them didn’t change the description. It also didn’t change when I swapped what runs underneath. A design that can absorb three new workers, and a change of model, without being rewritten is the thing I’m actually claiming. The question everyone asks stops being true very fast Open almost any newsletter like this one and you’ll find the same article: here are the tools to use, here’s the stack to copy, here’s the fourteen things that will put you ahead. I actually read a really good one this week. It listed the exact tool for fourteen different jobs. It’ll be wrong within a year. The person who wrote it knows that, which is why he writes a new version every few months. Tools change fast. Prices go up. A better one shows up. The one you learned gets bought by a bigger company and slowly gets worse. Enshittification is real. If your business is a list of products, you have signed up to redo the work every time the list changes. The layer underneath the tools barely moves at all. What I could throw away this afternoon This isn’t a thought experiment. These are things I’ve already changed, or could change today. The chat app: work shows up as messages, whether that’s Discord or Teams or an email inbox. Changes one small piece of code. The task board: cards, columns, comments, done. That’s Asana, or Trello, or Linear, or the one I use - Fizzy, by 37Signals. The AI model: today that’s Claude, and I like it. I’m using Anthropic’s Fable and Opus and Sonnet for the right-sized tasks for those models. My helpers are described in plain writing, so what runs them underneath is a setting. If something better arrives next year I change the setting, and every one of them still knows what it’s for. The places I publish: Substack, LinkedIn and X are all driven from a browser I’m already signed into, so none of them has me locked in through a connection I would have to rebuild. When Substack added a scheduler for Notes, switching to it took one morning, because my system already knew what a scheduled piece was. The part I couldn’t throw away is the part nobody sells you: what each helper is for. The rule that one of them may never rewrite another one’s work. The single gate that needs a human. Those took real thinking. They’re also just words in files I own. Your history should belong to you The clearest example is where my writing lives. Every piece I have written, drafted, killed or published is a list of lines in a file in my own folder. Just over a thousand pieces across 222 days. 636 of them went out. Every change is one line with a time and a name on it. The searchable copy sitting on top of that file is throwaway. I delete it and rebuild it from the lines whenever I feel like it, and I have. If that history lived inside somebody’s app instead, I’d be renting my own memory. Most people make that trade without noticing, because the app is genuinely good and there’s an export button right there in the settings. Why almost nobody talks about this part There is nothing to buy. Nobody advertises “spend an afternoon deciding what each part of your business is actually for.” It doesn’t look good in a screenshot. It’s also harder. Comparing tools takes twenty minutes and feels like progress. Writing down exactly what you want, clearly enough that the right tool becomes obvious, takes an afternoon and feels like you didn’t do anything at all. So everyone writes the tool article. It’s quick to write, quick to read, and somebody buys something at the end. I’m not against those articles. I wrote one this week. But it answers a question that expires, and the reason mine keep working is that I answered a slower question first. The one question I ask before adding anything What happens to my system if this exact product disappears in eighteen months? If the answer is that one small piece of code changes, it goes in and I barely think about it. If the answer is that my history lives inside it, or that the way I work would be shaped by its buttons? Then it doesn’t go in. Or it goes in, and I keep my own copy of the record somewhere I own. That question has kept me away from products that were better than the ones I use. It was worth it every time. A slightly worse tool that leaves you holding your own history beats a better one that holds it for you. Try this before you pick anything else Write down how your business works on one page, without naming a single product. Who does what? What decides what? What has to be written down? Where a person is required, and why it has to be a person there? Most people can’t finish that page on the first try. That’s the useful part. Every place you get stuck is a decision you have quietly handed to a product. Then, go and pick your tools. You’ll find the choice is much easier, and much less interesting, which is exactly what you want. PS. If you want a resilient setup for your own business, I can help. Get full access to G8N•AI at www.g8n.ai/subscribe (https://www.g8n.ai/subscribe?utm_medium=podcast&utm_campaign=CTA_4)

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