Nelson Pérez

@AlexAhundred @aatanacio Me pasa igual con mi cuenta Max llega al límite sin motivo

@aatanacio Lo que pasa es que ahorita hay un bug que consume muy rápido los tokens. Desde ayer ando necesitando terminar un runtime pero me rehuso a pagar más

Después de 74 cambios y como 15 veces que Claude me dijo que POR FAVOR me fuera a dormir 🤭 creo que ha quedado funcionando muy bien el bot de Polymarket. (Inserten aquí todos los disclaimers de Not Financial Advice, etc) En el tuit de abajo les dejo como se ven los trades

@dashboardlim AUTOMATE

I've created a full guide on how to automate 14 sales tasks Covered from lead capture and follow-ups to proposals, CRM updates, sales training, forecasting, and more All these will save you so many hrs/mo Like + Comment "AUTOMATE" and I'll DM you the guide

@aatanacio Si es súper interesante estoy leyendo the main street millionaire the Cody Sánchez, buen libro. El tema es no pensar que « boring business «  = income

He estado trabajando en un proyecto para ayudar a comprar boring businesses a gente en latam. Como empezamos: - Un landing page - Lista de Espera - Secuencia de 10 emails - Bot que crea contenido para SEO - Bot que crea contenido para Tiktok En tiktok estoy contando más!

stop spending money on Claude Code. Chipotle's support bot is free:

@RedPillSayian Monitor here war-room.live

Marine Corps veteran arrested inside the senate armed service committee and then attacked for protesting israel 😳 “America does not want to fight this war for Israel!”

@gregisenberg Just vibe-coded war-room.live War Room to monitor the landscape in real time. The era of personal apps is amazing

im excited for you because this is the most asymmetric moment in history for motivated people who want to ship ios apps, mac apps, and web apps you find a niche and then a sub-niche you build the first version in days you use ai to research the space you ask it for content ideas you learn which content people actually want you post you watch what resonates you refine the product you keep shipping the comments become feature requests the dms become customer interviews the saves tell you what the market cares about you turn that signal into product updates you turn those updates into more content distribution compounds the product gets better the audience grows one niche turns into two one app turns into a small suite one workflow turns into a platform and suddenly the thing you started in a tiny sub-niche becomes the default tool for that corner of the internet i knew you could do it

@TechWith_Nova Skill

Your AI conversations aren't privileged. Yesterday, Judge Jed Rakoff ruled that 31 documents a defendant generated using an AI tool and later shared with his defense attorneys are not protected by attorney-client privilege or work product doctrine. The logic is simple: an AI tool is not an attorney. It has no law license, owes no duty of loyalty, and its terms of service explicitly disclaim any attorney-client relationship. Sharing case details with an AI platform is legally no different from talking through your legal situation with a friend (which is not privileged). You can't fix it after the fact, either. Sending unprivileged documents to your lawyer doesn't retroactively make them privileged. That's been settled law for years. It just hadn't been tested with AI until now. And here's what really hurt the defendant: the AI provider's privacy policy (Claude), in effect when he used the tool, expressly permits disclosure of user prompts and outputs to governmental authorities. There was no reasonable expectation of confidentiality. The core problem is the gap between how people experience AI and what's actually happening. The conversational interface feels private. It feels like talking to an advisor. But unless you negotiate for an enterprise agreement that says otherwise, you're inputting information into a third-party commercial platform that retains your data and reserves broad rights to disclose it. Judge Rakoff also flagged an interesting wrinkle: the defendant reportedly fed information from his attorneys into the AI tool. If prosecutors try to use these documents at trial, defense counsel could become a fact witness, potentially forcing a mistrial. Winning on privilege doesn't make the evidentiary picture simple. For anyone advising clients or managing legal risk, this is a wake-up call. AI tools are not a safe space for clients to process their counsel's advice and to regurgitate their legal strategy. Every prompt is a potential disclosure. Every output is a potentially discoverable document. So what do we do about it? First, attorneys need to be proactive. Advise clients explicitly that anything they put into an AI tool may be discoverable and is almost certainly not privileged. Put it in your engagement letters. Make it part of onboarding. Don't assume clients understand this, because most don't. Second, if clients want to use AI to help process legal issues (and they clearly will, increasingly), then let's give them a way to do it inside the privilege. Collaborative AI workspaces shared between attorney and client, where the AI interaction happens under counsel's direction and within the attorney-client relationship, can change the analysis entirely. I'm excited to be planning this kind of approach, and I think it's where the industry needs to head. storage.courtlistener.com/recap/gov.usco…

@gregisenberg Yes !!

What if I hosted an ALL DAY livestream on Clawdbot/Openclaw for 100,000+ humans and AI agents? We all learn how use-cases for marketing, productivity, engineering etc to GET SMART about it Sponsors give away Mac minis so MORE people can build REPLY if this sounds interesting

@mattyp @Replit 😀

Replit Rewind is live! Who sent more messages than me this year? replit.com/rewind2025

@FedotOff90 Gemini

Gemini 3 just dropped yesterday… and if you run ecom, you better lock the f*ck in. I’ve spent the last 5 months testing every major AI model for ecom Claude Sonnet 4.5 GPT-5 DeepSeek R1 Higgsfield All killers. All useful. But Gemini 3? It’s a complete shift in how ecom brands will operate. Here’s what I saw in the first 48 hours: → It identifies winning ad angles in seconds (shit that used to take agencies weeks) → It breaks down competitor funnels with scary accuracy → It rewrites hooks in your brand voice without losing tension → It builds offer variations that actually convert, not generic template trash → It generates new creative concepts faster than you can test them This isn’t “AI that helps.” This is “AI that replaces 3 people on your team without blinking.” I ran it through 150+ creative tests, 12 funnels, and 40+ product angles. The results were insane: 5 new creative concepts that hit above 1.7 ROAS on cold CPC dropped 22% on two of my testing campaigns It found competitor patterns inside Gethookd that I didn’t even see It generated STATIC ads that looked handcrafted — not AI-goo It gave me 20 hooks from one single winning angle (no more blank page syndrome) And here’s the part nobody is ready for: Your competitors who adopt Gemini 3 early will scale faster than you can react. Not because they're smarter… But because their creative volume just multiplied overnight. Ecom is a speed game. If you’re still: launching 3 creatives a week guessing angles manually analyzing competitors spending days writing scripts relying on outdated product research methods …you’re gonna get buried by brands using Gemini to pump out: 50 creatives a week 6–8 new angles every Monday daily funnel audits real-time offer iteration instant competitor teardown This is the “GEM” moment for ecom — the same way Meta’s GEM update punished slow advertisers, Gemini 3 is about to punish slow operators. If you want to stay relevant in 2025 ecom: Start using AI as your creative engine Build systems around it Scale faster than your competitors can blink And if you want the exact Gemini prompts I’m using to generate high-performing angles, hooks, scripts, and PDP upgrades: Connect with me Comment “GEMINI" and I'll send it over.

@mikefutia Nano

Google Nano Banana Pro 🍌 is crazy good at static ads... But it only generates one image at a time. This n8n AI Agent generates 100s of ad variations in minutes, fully automated. All inside n8n + Nano Banana Pro. Perfect for DTC brands & agencies who need massive creative volume to test and beat ad fatigue. Let's be honest: Manual ad creation takes forever. You're generating one image at a time, tweaking prompts, downloading files, trying different angles. And by the time you have enough variations to test, you've wasted hours. This n8n automation solves it: → Upload ONE product reference image via n8n form → OpenAI Vision analyzes your product automatically → AI generates custom image prompts (you choose quantity: 50, 100, 1000+) → Nano Banana Pro creates all variations in parallel → 4K studio-quality output with perfect text rendering → Images auto-stored in Box for instant access No manual prompting. No one-by-one generation. No wasted hours. What you get: → Hundreds of ad variations from one upload → Different angles, backgrounds, compositions automatically → 4K resolution with perfect text adherence → Production-ready static ads for testing at scale Built 100% in n8n. Want the complete n8n template? > Comment "NANO" > Like this post And I'll send it over (must be following so I can DM)

@JulianGoldieSEO Yes

HOLY SH*T… This AI Agent does everything 🤯 Plugged into n8n and it runs the entire content machine: 📥 Scrapes viral videos in your niche 🧠 Rewrites scripts with GPT-5 style prompts 🎭 Auto-creates talking-head avatars 🎬 Edits + captions + hooks pre-baked 🚀 Publishes across TikTok, IG, YT, X, FB, Shorts & Reels 📊 Tracks views + optimizes what to post next …while you sleep. Want the full workflow? 👇 🔁 Like + RT ✅ Reply “YES” 🤝 Follow & I’ll send it to you FREE

@matt_gray_ IG

Instagram becomes a growth machine when you stop posting randomly and start using a system. Here’s what actually moves the needle: • One idea becomes 20 plus posts • Your visuals become instantly recognizable • Comments turn into email subscribers automatically I built a free Instagram Flywheel that breaks down the 3 systems I used to scale to 950,000 followers and $2.3M in revenue. Comment “IG” and I’ll DM it to you (follow me first or I can’t DM you)

One of my favorite lessons I’ve learnt from working with smart people: Action produces information. If you’re unsure of what to do, just do anything, even if it’s the wrong thing. This will give you information about what you should actually be doing. Sounds simple on the surface - the hard part is making it part of your every day working process.

Shopify teams are using AI to announce their internal tools is one of the most delightful side effects of the AI age. This one is too fun not to share

@gregisenberg *self healing testing

@gregisenberg self healing is a major problem not attended

30 ways to find your next $10K+ MRR idea for 2026: 1. Read GitHub issues and look for recurring pain points developers ignore. 2. Set Reddit alerts for “I wish someone would build…” and validate demand. 3. Build an agent around a single recurring vertical Upwork task that pays well. 4. Monitor API changelogs and build integrations the day they launch. 5. Summarize 1-star Chrome Store reviews with ChatGPT and fix the top three complaints. 6. Audit browser DevTools to see what power users still do manually. 7. Reverse-engineer topProduct Hunt hits, then apply AI to improve them. 8. Read YouTube tutorial comments to see what viewers still can’t figure out. 9. Watch Twitch streamers and note what workflows interrupt their flow. 10. Scan job listings for repeated “must-know” tools; build easier versions. 11. Dig through graveyard from companies like Google and ship the best abandoned projects. 12. Implement new AI research papers as usable web apps. 13. Explore niche subreddits and find problems that appear every week. 14. Review SaaS feature requests and build what the big players delay. 15. Connect open-source tools that don’t yet talk to each other. 16. Track “Chrome extension for X” search volume to spot new demand. 17. Feed GPT the top extension descriptions and ask for adjacent product ideas. 18. Use Perplexity Deep research etc to mine podcast transcripts on people's daily frustrations they’re telling you what to build. 19. Follow changelogs and tech-stack migrations of popular startups; build the missing glue. 20. Look at Zapier’s most-used zaps and each one could be an autonomous agent. 21. Track “AI for X” or “agent for X” search queries with SerpAPI. 22. Analyze public Notion templates and build vertical agents around them. 23. Browse LinkedIn for people describing manual data tasks and productize one. 24. Watch how startups use ChatGPT for customer support and make a vertical agent from it. 25. Rebuild niche directories (lawyers, therapists, realtors) as AI concierge services. 26. Create agents that plug into boring SaaS categories: procurement, compliance, HR ops. 27. Read changelogs from AI model providers; build tooling the day new capabilities appear. 28. Find spreadsheets that companies rely on and replace them with AI dashboards. 29. Identify agencies that charge per project and productize their work into recurring SaaS with agents. 30. I built a tool that automates a lot of this, ideabrowser.com and we give away 1 free startup idea per day with paid plans for AI agents to help you. Maybe it'll get your creative juices flowing. I'm rooting for you. TLDR; – The next big idea is probably hidden in a comment thread. – Every complaint online is a free focus group. – Chase friction. every pain point is a map. find one, solve it, then look for the next one it connects to. keep solving until the solutions form a workflow people can’t live without. by owning the whole chain of pain you build defensibility. – Every repetitive task is a business model waiting for an agent. – The internet keeps leaving clues, just gotta listen

@AymericRoucher Loving Gitingest! Built a version inspired by original great @romdot2 & @cyclotruc github.com/coderamp-labs/… – with ZIP upload. No URL swaps needed! Try it: gitingestzip.com 🚀 #AI #DevTools #LLM

For those who haven't come across it yet, here's a handy trick to discuss an entire GitHub repo with an LLM: => Just replace "github" with "gitingest" in the url, and you get the whole repo as a single string that you can then paste in your LLMs

World-class bot detection for every Shopify store. Most traffic on the internet is not initiated by biological lifeforms. More so, commerce attracts 🤖 specimens that you don't find in other environments, purpose built to interact with carts, checkout, etc. Some of these are good, some neutral, some cause harm. Identifying them is a legitimately hard problem that requires specialized commerce knowledge and scale. We like solving hard problems for merchants. We made a huge investment this year to rebuild bot detection from the ground up, and the new analytics filter is just the tip of that iceberg. Long story short: if you're a Shopify merchant, you have world-class bot detection working for you, and a dedicated team that's continuously improving it. 💪🏻