Greg Bessoni

POV: Your boy just dropped $420 on UConn in round 1 and now can't afford a bench. His roster: UConn ($420) Norfolk St ($15) Grambling ($12) Howard ($8) BidBracket exposes who actually knows basketball and who's just loud. March Madness 2026 DM for access

@hasantoxr been testing SureThing right now actually. asked it to find SEOs on LinkedIn to talk about my new open source AI SEO skill for @openclaw , @claude_code , and Codex. curious to see what it pulls. if it's as smart as the 300K email story I'm sold.

🚨 BREAKING: An OpenClaw early contributor just publicly switched to SureThing. He contributed code to the project. Then he found something better. 300,000 emails. Tamed in one hour. Claude failed. Codex failed. His words: "OpenClaw is Linux. I want a Mac." Here's what happened next 👇

@tonysimons_ @hasantoxr outch

@hasantoxr FYI. I tried!

this is the whole thing. AI made the doing easy. the knowing what to do was always the hard part and it still is. the gap between operators with 10 years of pattern recognition and someone who just discovered SEO last month with claude code is wider now, not narrower. the tools got better. the judgment didn't get automated.

Unpopular opinion: AI does make SEO easier. It makes scaling tactics trivially simple. What it can’t do is tell you which tactics are worth scaling. That’s still strategy. That’s still the hard part. That’s still where years of reps actually matter.

the people saying AEO/GEO doesn't work aren't doing it. the people doing it aren't talking about it because they don't want competitors catching on. impressions are just the start, wait until the conversion data from AI-referred traffic starts showing up in your analytics. that's when it gets real.

SoOoOoOo the AEO/GEO strategy stuff you keep hearing about *actually* works for increasing impressions in a very big way

@4e80ef57af51425 @Ma_Tex_Mex nice system. if you want to add an AI citation readiness layer on top of your audit chain, I open sourced one that checks crawler access, GEO scoring, and generates full reports. could plug into your workflow. github.com/gbessoni/seo-a…. would be cool to see them work together.

@Ma_Tex_Mex Très propre. Et si tu veux aller plus loin : j'ai construit un système qui chaîne tout ça automatiquement. Le collecteur pull GSC, l'auditeur score, l'implémenteur génère les .htaccess + les tests de vérification. Open source : github.com/jgoullet/seo-g…

Tu as 200 pages sur ton site WordPress et la moitié ne génère ni clic, ni impression depuis 6 mois ? Elles ne t'aident pas. Elles te plombent. Voici comment j'utilise Claude Code + Google Search Console + WordPress pour identifier et supprimer automatiquement toutes les pages inutiles de mes sites ↓

GEO doesn't replace SEO, it sits on top of it. your AI search visibility is built on your organic authority. kill your SEO and your GEO dies with it. been deep in this and open sourced an agent that audits both sides. github.com/gbessoni/seo-a…. free, MIT licensed. curious what you're seeing.

@theroberthu I have a feeling GEO might just become more important than SEO in the near future. What do you think?

Brands spend thousands optimizing for Google. Meanwhile AI is answering “what should I buy” and they’re not even in the conversation. The visibility game shifted. Most haven’t noticed yet.

this is the right framing. 'who AI deems more credible' is the game now. been building an open source SEO agent that audits exactly this, AI citation readiness, crawler access, and the technical gaps most sites don't know they have. would love your take on it. github.com/gbessoni/seo-a…

这篇是我最近在研究 GEO 时的一些系统性整理 在这个过程中意识到了些变化： • 流量入口在逐渐从“搜索引擎”变成“AI回答” • 信息的竞争，从“谁排在前面”，变成了“AI 觉得谁更可信” 所以花了比较多篇幅去拆 AI 的决策逻辑，比如： • 为什么单一来源不够 • 为什么必须做 cross-source 的信息分布 • 以及 RAG 和 pretrain 分别在影响什么 也整理了套比较完整的框架，从适不适合做 GEO，到具体怎么做能改善ROI。 如果你最近也在看 AI 搜索，这篇应该会有一些帮助，也期待和大家一起交流学习！

if you're teaching GEO and AI SEO, check out seo-agi on github. open source agent framework for claude code and openclaw that runs full audits, AI citation readiness checks, and technical SEO workflows. MIT licensed, free, built by an operator not a consultant. github.com/gbessoni/seo-a…. could be a solid resource for your students.

📈 ¿Quieres mejorar tu SEO usando IA? “Posicionamiento con IA: Introducción al AISEO y GEO” 📅 13–17 abril ⏰ 9:30–13:30h (20 h) 📍 @PalmaActiva Para cualquier persona que quiera optimizar su presencia online con las herramientas más innovadoras. ℹ️ icpa.palma.cat/icpafront/curs…

the prompt is the weapon but knowing what your prospect is actually frustrated about before you write the VSL is what makes it convert. been building tools that surface the real conversations people are having across X, Reddit, and HN so your copy hits different because it's based on real signal not guesswork. would love to get your take on some of the stuff we're shipping. DM me if you're curious

🚨 BREAKING: R.I.P. CLICKFUNNELS. Opus 4.6 ONE-SHOTS entire VSL funnels now. I compressed my entire VSL framework into a single 5,280-word prompt. The same framework that's generated $1M+ and 500+ booked calls. HOW IT WORKS: You plug in your offer details. It spits out: → Full VSL script from hook to close → Built on the persuasion structure behind EVERY high-converting agency funnel → Generated $1M+ and 500+ booked calls This thing can INSTANTLY double your booked calls. Use it now or get left behind. 🤘 Like + reply "OPUS" and I'll DM it to you

this is fire for the prospecting side. once you've got the leads the next unlock is knowing what they're actually talking about online before you reach out. been building some open source SEO tools for claude code and openclaw that pair well with this kind of workflow. would love to connect and swap notes. got some stuff cooking on github you might dig

This Google Maps Lead Gen Agent is absolutely insane 🤯 Enter a keyword, city, & state → get back names, phone numbers, emails, websites, & reviews. All inside Google Antigravity + Claude Code. Perfect for agencies and lead gen operators who need prospecting data without paying insane SaaS fees. Here's the problem: You're manually searching Google Maps. Clicking through listings one by one, copy-pasting phone numbers into a spreadsheet. It takes hours to build a decent lead list. This scraper solves it: → Enter your keyword (plumber, dentist, realtor, etc.) → Pick your city and state → Set the number of results you want → Hit search and let Apify do the scraping → Save leads you like to a bookmark list No manual searching, no copy-pasting, no paying $200/month for a lead gen tool. What you get: - Full search results with business info - Bookmark feature to save your best leads - Search history to track past scrapes - Option to host it on Replit so your team can use it Built 100% with Claude Code & Antigravity. I recorded a full walkthrough showing exactly how I built this from scratch, plus all the prompts I used. Want all the prompts I used for Claude Code so you can build it yourself? > Like this post > Comment "LEADS" >Follow @ashiqur_ai And I'll send it over (must be following so I can DM)

solid skills. the missing layer is knowing what your prospects are actually saying right now before you write the email. we built Clawback to pull the real conversations happening across X, Reddit, HN, and YouTube for any person or company. pairs well with everything on this list. clawback.noexcuselabs.com

We spent hundreds of hours building Claude Code skills for our $7M ARR GTM agency (and we're giving them away for free) - ICP research - signal scoring - cold email writing - sales intelligence - campaign intelligence. These run inside every system we build for 70+ B2B clients. Reply "Claude Code" and I'll send you the Github repo with everything.

100K cold emails a month and 1% convert. cool. now imagine if instead of spraying 100K strangers you actually knew what your top 500 prospects were talking about this week. what they're frustrated by. what they posted on reddit last night. that's what we built Clawback for. type a name, get a full brief on the conversations they're having right now across X, Reddit, HN, YouTube. then your first email isn't cold, it's informed. clawback.noexcuselabs.com

how to send 100,000 cold emails per month for about $1000 hypertide io for inboxes connect to instantly for warming source leads from apollo io api and leadmagic and salesql cascade enrichment waterfall 1% turn into customers remarket to them across all channels with a VSL to build deeper trust startup, cash in, sell out, bro down

dashboards tell you what happened. clawback tells you what your customers and investors are saying right now before you even talk to them. know the conversations they're having across X, Reddit, HN, and YouTube. 10x your odds in every sales call and investor meeting. clawback.noexcuselabs.com

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this is cool but if you want the full SEO agent framework built for openclaw and claude code, I open sourced one too. real strategies, not AI slop. covers technical audits, content optimization, and the actual workflows operators use. github.com/gbessoni/seo-a…. MIT licensed. free forever.

Holy shit...AI search is eating Google's traffic and most websites have zero idea why they're invisible to ChatGPT and Perplexity. A developer just built geo-seo-claude to fix that. Point it at any URL. It runs a full GEO audit, scores your AI citation readiness, checks which AI crawlers can even access your site, and generates a client-ready PDF report. AI-referred traffic converts 4.4x higher than organic. Traditional SEO agencies haven't figured this out yet. This repo has. 100% Opensource. MIT License. Link in comments.

@natjin using perplexity's search API to see what actually gets retrieved instead of guessing by prompting LLMs is the difference between reading the scoreboard and asking the ref what he thinks the score might be. real data beats prompt testing every time. good signal.

the smartest aeo/geo companies are using perplexity’s search api like a super-weapon they realize you can actually see what is getting ranked and retrieved by LLMs at mass-scale (200m+ daily perplexity queries) vs prompting llms to try to get answers this is real alpha

months of cron output silently loading into every context window is the kind of bug that makes you question your entire setup before you find it. this is the openclaw equivalent of wondering why your mac is slow and discovering chrome has 847 tabs open in the background. good looking out.

IF YOU'RE ON OPENCLAW DO THIS NOW: I just sped up my OpenClaw by 95% with a single prompt Over the past week my claw has been unbelievably slow. Turns out the output of EVERY cron job gets loaded into context Months of cron outputs sent with every message Do this prompt now: "Check how many session files are in ~/.openclaw/agents/main/sessions/ and how big sessions.json is. If there are thousands of old cron session files bloating it, delete all the old .jsonl files except the main session, then rebuild sessions.json to only reference sessions that still exist on disk." This will delete all the session data around your cron outputs. If you do a ton of cron jobs, this is a tremendous amount of bloat that does not need to be loaded into context and is MAJORLY slowing down your Openclaw If you for some reason want to keep some of this cron session data in memory, then don't have your openclaw delete ALL of them. But for me, I have all the outputs automatically save to a Convex database anyway, so there was no reason to keep it all in context. Instantly sped up my OpenClaw from unusable to lightning quick

'reimagined the entire computer' is a wild claim for what looks like zapier with a chat interface and better marketing. connecting to gmail and slack isn't reimagining computing, it's oauth. the phone app is a nice touch though. most agent platforms forget you might want to check on things when you're not at your desk. curious to see if this actually works or if it's another demo that falls apart the second you try something the promo video didn't cover.

🚨BREAKING: A Stanford CS grad just reimagined the entire computer. Not for humans. For AI agents. It's called adaptive.ai You describe what you want in plain English. It builds the software to do it Automations. Scheduled agents that run while you sleep. Full apps. Databases. UIs. Not a chatbot. Not a no-code tool. A computer that AI operates for you. And it's on your phone. A full iOS app connected to the web platform. Manage your AI agents, check results, approve tasks from anywhere. Not even OpenClaw or Perplexity have this. Here's what makes this different from everything else: It connects to your REAL accounts. Gmail. Google Calendar. Slack. Sheets. Drive. GitHub. Notion. Twitter/X. LinkedIn. Plaid. Not simulated. Not sandboxed. Your actual tools doing actual work. → You say "send a follow-up email to everyone who signed up yesterday." It sends from YOUR Gmail. → You say "track my expenses across 3 bank accounts." It connects via Plaid and builds an automated expense tracker. → You say "monitor my competitors on Twitter and send me a weekly report." It builds the entire pipeline and runs it every Monday. Here's what you can build in minutes: → Customer support system that handles 80% of inquiries automatically → Smart email triage that categorizes, drafts responses, and escalates urgent items to Slack → Meeting prep assistant that researches every participant before your call → YouTube analytics tracker with weekly performance reports → Lead qualification system that auto-routes prospects to your CRM → Content repurposing pipeline that turns YouTube scripts into LinkedIn posts and tweet threads Here's the wildest part: It remembers everything. Your preferences. Your workflow patterns. Your business context. It gets smarter about YOUR specific needs over time. Every project builds on the last. And it doesn't just build one thing at a time. Apps built on Adaptive can talk to each other. Your file hosting app shares files with your expense tracker. Your email triage feeds into your CRM. Everything is interconnected. Backed by Conviction Capital (Sarah Guo), Pebble Bed, Anti-Fund, Ryan Hoover (founder of Product Hunt), and Dave Baszucki (founder of Roblox). No API keys to manage. No backend to configure. No code to write. Your AI computer. In your pocket. On your desktop. Always running. Just describe what you want. Adaptive builds it. This is what computers look like from now on. Link in the next comment.

this is the toothpaste listicle playbook again just wearing a pest control uniform. write a fake comparison guide, put your client at #1, publish it on medium and a press release site, and wait for chatgpt to cite it as a recommendation. it works until it doesn't. and when AI models start filtering for this exact pattern, every business you 'ranked' disappears overnight. also 'comment LOCALRANK' is the real business model here, not the pest control SEO.

I got a local pest control company recommended by ChatGPT by exploiting one simple content gap. No website redesign. No new reviews. No marketing budget. Here's exactly how: Most people think pest control companies get AI recommendations from: - HomeAdvisor profiles - Google Maps visibility - Angi reviews Wrong. AI recommends pest control companies from whoever creates the most helpful, structured comparison content. The strategy: 1. Search ChatGPT for "best pest control in [city]" You'll notice AI either gives generic advice or mentions big national chains. Almost zero local companies show up. That's the gap. 2. Write a "Local Pest Control Comparison Guide" "2026 Phoenix Pest Control Guide: Services, Pricing, and Top Rated Companies for Every Pest Type" 3. Include a comparison table organized by pest type Columns: company name, ants specialist Y/N, termites, rodents, scorpions, initial inspection cost, monthly service rate, eco-friendly options. 4. Publish on Medium, LinkedIn, and distribute via press release Cost: $150-200 total Time: 3-4 hours 5. Create a follow-up "Seasonal Pest Guide" for the city "Spring 2026 Phoenix Pest Prevention Guide" with your client mentioned as the recommended solution. Why this works: Pest control is one of the most underserved niches in AI recommendations. There's almost no structured comparison content. The first company to create it wins every AI query. The takeaway: Industries with zero AI-optimized content are goldmines. Pest control, HVAC, and plumbing are the easiest niches to dominate in AI recommendations right now. Comment "LOCALRANK" if you want my LLM citation framework and I'll DM it to you (Must be following)

context beats prompt all day' is the one line from this entire list that people need tattooed on their forearm. everyone's out here engineering the perfect prompt when the real move is just giving the agent enough context about your business and letting a simple instruction do the work. the prompt engineering era is over. the context loading era is here.

AI AGENTS 101 (58 minute free masterclass) send this to anyone who wants to understand ai agents, claude skills, md files, how to get the most out of AI etc in plain english: 1. chat vs agents - chat models answer questions in a back and forth while agents take a goal, figure out the steps, and deliver a result 2. agents don’t stop after one response. they keep running until the task is actually finishedno babysitting required 3. everything runs on a loop. they gather context, decide what to do, take an action, then repeat until done 4. the loop is the system. they look at files, tools, and the internet. decide the next step. execute and then feed that back into the next step. over and over until completion 5. the model is just one piece. gpt, claude, gemini are the reasoning layer. the key is model + loop + tools + context 6. mcp is how agents use tools. it connects things like browser, code, apis, and your internal software. once connected, the agent decides when to use them to get the job done 7. context beats prompt all day. you don't need to write perfect prompts. load your agent with context about your business, style, and goals and then simple instructions work 8. claude.md or agents.md is the onboarding doc it tells the agent who it is, how to behave, what it knows, and what tools it can use. this gets loaded every time before it starts 9. memory.md is how it improves. agents don’t remember by default. this file stores preferences, corrections, and patterns you tell the agent to update it, and it gets better over time 10. skills + harnesses make it usable. skills are reusable tasks like writing, research, analysis the harness is the environment like claude code or openclaw that runs everything. basiclaly, different interfaces, same system underneath this episode with remy on @startupideaspod was one of the clearest ways of understanding a lot of the core concepts of ai agents could be the best beginners course for ai agents 58 mins. all free. no advertisers. i just want to see you build cool stuff. im rooting for you. send to a friend watch

so the startup idea is: spam reddit and forums with fake recommendations at scale, hope LLMs scrape it, and charge local businesses $3k/mo for astroturfing they don't know is astroturfing. this is the exact playbook that got businesses penalized in google for a decade except now we're doing it to AI models and calling it a service. 'first agency to own this category' bro the category is reputation manipulation. it already exists. it's just never ended well for anyone doing it

Holy fucking shit A new startup idea just dropped: 1. DM local businesses - "hey, you're invisible to AI search. I can fix that." 2. Use CrowdReply to organically embed their name into relevant online conversations at scale 3. AI models scrape that content. Your client becomes the recommended answer. 4. Charge $1,500–3k/mo. Land 5 clients. Done. No need for ads or cold calls. No technical skills needed too. First agency to own this category is gonna print. Bookmark this.