Greg Isenberg

Inside Instinct AI, the $10B invite only personal agent app. Is it worth trying? https://youtube.com/watch?v=mUAsaprJ66s

Are invisible interfaces coming? Google JUST announced Gemini 3.8 Live. It can talk through a task with you, then keep working after the conversation ends. I think 90%+ of vertical SaaS will need a voice front door. By that I mean the way you use the software becomes talking to it, and the typing, clicking, and form filling happens on the other side without you. So a contractor standing on a job site just says what went wrong out loud. And by the time he's back in the truck, the quote is sent, inventory is checked, the CRM is updated, the customer got a text, and anything risky is flagged for him. Kinda the dream, right? The same thing works for nurses, dispatchers, recruiters, brokers, insurance agents etc. The person talks and the agent finishes the admin. Lots of opportunities here to build voice-first businesses (been thinking about this more and more). I think this is how vertical software becomes invisible. Nobody logs in, nobody fills out a form, and nobody learns your interface. You just talk, and the work gets done behind you. This is a glimpse of where SaaS is going. Not fully there yet but it's coming. Invisible interfaces.

WHAT IS AN AI "SOFTWARE FACTORY" AND IS IT HYPE (31 MINUTE BREAKDOWN) I think it's a silly name for a genuinely USEFUL idea! A software factory is 5-6 markdown files that sit next to your code and tell your agents how you like to work, so you can build high quality apps 24/7. It's going viral because AI coding has a trust problem. The model can build the feature, but with no structure around it you end up babysitting the agent, wondering what changed and hoping it didn't break something important. So you build with agents the same way a factory builds physical products! 1. Each feature gets its own station, which in software means its own branch, so multiple agents can work at the same time without stepping on each other. 2. The build station gives the agent rules for how to write the code, because "it works" is very different from "a developer could open this repo next month and understand what happened." 3. The proof station makes the agent show evidence. Screenshots, videos, speed numbers, before-and-after states. It has to prove the thing works instead of saying it works. 4. The review station runs the work through a code review agent, and if it doesn't clear the bar, it goes back through the line. 5. Then you show up at the end to merge. For a 100+ years people have run production this way, and it worked because the structure is good. The full episode on what’s a software factory is NOW live on @startupideaspod with the wonderful @rasmic Watch: https://www.youtube.com/watch?v=_LCeJZFIsd4&t So is it hype?!? I don't think it is, because of what it does to your output! WITHOUT a factory, you build ONE feature at a time and you're the bottleneck at every step, prompting, checking the diff, testing it yourself, hoping nothing else broke (spoiler alert it often does). WITH a factory, EACH feature runs in its own isolated copy of the app, so you can have 10+ of them going at once, and each agent has to prove its own work and pass a code review befo...

AGENT HARNESSES ARE THE NEW GPT WRAPPERS What exactly is an agent harness? A harness does 4 things: 1. Runs the model in a loop so it keeps working step after step instead of answering once and stopping. 2. Gives it hands to read files, call tools, open portals, and run code. 3. Manages its memory so hour three of a job still knows what happened on hour one. 4. Enforces the rules about what it can touch and when it has to stop and ask a human. WHY IT'S INTERESTING - The market is MEGA. I think about it like a wrapper let you sell software ($800B market) but a harness lets you sell the work ($5T+ market)! - It doesn't depend on any one company's model. The knowledge about the job lives in the harness, so you can run GPT today, Claude next month, an open model like Google Gemma, Qwen, Deepseek etc on your own machine after that, and it keeps working. A wrapper was one model doing everything and a harness is a router. - It gets better the more you use it. See, every correction a human makes becomes a rule the harness keeps, so what you have after 500 jobs is a completely different product than what you had after 5. Wrappers only got better when OpenAI got better. - You can charge for finished work! The harness knows when a job is done, so you can price per claim, per filing, per review, per resolved exception, or per closed month. This helps compete with SaaS! - Most jobs are just the same handful of decisions, repeated, using the same few tools. That's true for most of the 800+ occupations out there, which is why almost all of them could have a harness built for them. Lots of space for startups to be building. -The frontier labs won't come for these. OpenAI is not going to learn how a freight claim gets denied in Rotterdam or which prior auth your specific payer rejects. Those markets are too small for them and the knowledge only exists inside the job. They'll keep making the models better, which just makes your harness better which is cool. - OH, AND rea...

The internet is the only place where anyone from anywhere can achieve anything And despite all the AI doom and gloom you might read, that dream is more alive today than ever Prepare for an explosion of entrepreneurship!

There's no such thing as a solo founder anymore. You have Grokbot, Hermes, Claude Code, Codex etc. For $200 a month you rent more brainpower than a 1990s Fortune 500 department. You have a team, it runs on tokens!

The only businesses left to build: 1. AI native service firms 2. Offline businesses 3. Distribution (media, community, audience) 4. Proprietary datasets 5. Domain specific harnesses (the agent that runs one industry's work) 6. Robotics and physical AI 7. Physical products with a fan following 8. Compute and energy 9. Health, longevity, and care 10. Marketplaces and social networks (for people and agents) 11. Real assets (property, equipment, land, infrastructure) 12. Vertical agents 13. Security

This is the AWS moment for agents. OpenAI just shipped the Agents API, and everything that made agents hard to build is now something you rent instead of build. Keeping one running for days, remembering what it's doing, using tools, recovering when a step fails. Now it's an API call. Before AWS, you had to buy and run your own servers, so only well funded teams could build real/scalable products. AWS made the hard part rentable, and all the value moved up to whoever had the best idea for what to build on top. Same thing is happening here. I'll be honest, my first reaction was that this is bad news for a lot of people I know. If your whole company is an agent platform, the thing you spent the last year building is now included for the price of tokens. But the more I sat with it, the more I think it's really good news if you're building for one specific industry. Basically, vertical software type stuff. If the hardest engineering just became a line item, then the only thing left that's actually hard is knowing the job. Like what counts as a done claim, what makes a filing get rejected, where the money leaks. So the wedge now is owning one painful workflow with your own tools, data, approvals, and a clear ROI. Freight exceptions, insurance reviews, security triage, revenue leakage, healthcare admin, compliance ops. I see a lot of doomers on X saying software is over (and sometimes I feel the same way), you'll just use Claude or ChatGPT for everything. BUT, if that were true, OpenAI wouldn't be shipping infrastructure for other people to build agents on. They're telling you exactly what they think: the general model is theirs, the 10,000+ specific jobs it needs to be pointed at are yours. I think software is just evolving. It's becoming an agent internet, and every layer of it, the tools, the workflows, the boring jobs, gets rebuilt for a user that doesn't have eyes or hands. That's a lot of companies waiting to be built.

GPT-6 Astra makes 2 kinds of businesses MUCH easier to start: outsourced work turned into software, and physical product businesses that used to require $2M to in upfront capital to start 2 years ago. The magic is that Astra can move across the messy middle: browser, codebase, docs, Blender, parts lists, suppliers, PRs. On today’s @startupideaspod, @rasmic shows how he took an AI HomePod idea to Raspberry Pi setup, Blender layout, shopping list, supplier path, and code changes in one session. Watch: https://www.youtube.com/watch?v=nglqTHwuZ-8 Everyone on X is posting game demos, that's cool but... I think we'll also see an EXPLOSION of physical product businesses: tiny hardware, niche ecommerce, custom gadgets, home lab projects, and creator merch with utility. Idea → mockup → parts list → supplier → cart → code → prototype. Pretty big deal.

So, they say AGI is here with GPT-6 Astra! Question: what new businesses does Astra make possible? I’d look for work people already pay agencies, consultants to do: - renegotiate bills - audit app security - speed up slow pages and API calls - monitor competitors - run QA checks - write SOPs - turn a service workflow into software - prototype niche hardware That is the wedge. What feels different with Astra: 1. It is especially good at computer use work like opening apps, clicking through workflows, using the browser, and operating tools. 2. It is super strong when code + browser + local tools are all part of the same task. 3. It can use Blender to mock up a physical product, then create a parts list, sourcing path, wiring plan, and code changes. 4. That means a lot traditional (ie: I need to hire someone to do something) work starts to become software-shaped. Full breakdown with @rasmic on today's episode of @startupideaspod Watch: https://www.youtube.com/watch?v=nglqTHwuZ-8 He walks through how he used Astra to take an AI HomePod idea and turn it into a Raspberry Pi setup, Blender layout, shopping list, supplier path, and code changes in one session. I’ve seen tons of “Astra built a video game in one prompt” demos and it's cool. But I think there will an explosion of physical product businesses. Gonna be crazy. Tiny hardware ideas, niche ecommerce products, custom gadgets, weird accessories, home lab projects, creator merch with actual utility. You can go from idea → Blender mockup → parts list → supplier research → Amazon cart → code changes → first prototype. Pretty big deal.

Apple iPhone Duo is cool but I'm waiting for Apple Studio Display Duo

iPhone Duo is here. Here are 9 startup ideas I’d build for it: 1. Mobile sales room: prospect profile on one side, live call notes + objection scripts on the other 2.Pocket CAD for trades: plumber/electrician sketches room measurements with Pencil, app converts to parts list, code notes, quote. Beats Autodesk. 3. Contractor estimating app: blueprint/PDF on one side, materials calculator + margin controls on the other 4. Jewelry trade in app: customer sees instant offer, buyer sees authenticity checks, comps, resale margin. 5. Two sided live translator for businesses: clerk and customer each see their own language on opposite screens. Sell to hotels, clinics, immigration lawyers, luxury retail. 6. Pocket notary / witness app: signer sees the doc, operator sees ID verification, fraud checks, and legally required prompts. Charge per notarization. 7. Field medical consent: patient sees plain-language consent, clinician sees risks, contraindications, charting, signature. 8. Tow truck accident intake: driver captures scene/photos closed, unfolds on hood for customer claim, repair authorization, rental, tow payment. 9. On site insurance adjuster: damage capture outside, policy rules + claim estimate inside. (I'll add more Duo ideas to http://ideabrowser.com and maybe talk more about it on @startupideaspod) Quick framework for finding iPhone Duo startup ideas (how I'd think about it): - A phone is great when the job starts in the real world: a photo, scan, call, message, location, or quick note. - An iPad is great when you sit down to create: draw, write, edit, design, review. - BUT, Duo is interesting in the messy middle: when someone starts with a phone, suddenly needs more space, has another person involved, AND there’s money or approval on the line. I think the best Duo ideas should feel weird on a normal iPhone and unnecessary on an iPad.

My entire X feed is the world is ending because of AI, instinct is the worlds greatest AI product and Zuck is BACK with Muse AI You?

Local AI 101: open models, Hugging Face, and businesses to build (38 min masterclass) I still think cloud AI is the default for most things, and honestly it should be, the frontier models are the strongest and easiest to use. But something shifted in the last 4-5 months. You can now run genuinely good open models directly on your own laptop, or even your phone. And once you actually try it, it changes how you think about what AI is even for. LOCAL AI, CLEARLY EXPLAINED: 1. The model is the brain doing the thinking. Gemma, Llama, Mistral, and Qwen are the main families, and each is better at different things, some at reasoning, some at coding, some small enough to run on a phone. 2. Hugging Face is the warehouse where you find them. You go there to see what each model is good at, check the license, and grab the compressed versions that run on a normal computer. 3. The software is what runs the model on your machine. Start with LM Studio if you're not technical, it feels like a normal app where you search, download, and start chatting. Ollama is the one you reach for when you want to plug a model into your own apps. 4. The workflow is the actual product you build on top of it all. That's what I'm ideating around for some businesses to create. I think local AI just made a specific kind of business way easier to start. Find an industry that: 1. Sits on sensitive data they'd never paste into ChatGPT 2. Does the same review over and over 3. Runs on software from 2003 Then build a local AI tool that does that review on their own machine, so the data never leaves the building! Take home health agencies. Nurses write visit notes all day, and if a note is missing a detail, the billing gets denied or the audit flags it. Here's how I'd start: 1. Find 5 small agencies. Offer to review a batch of their notes for them. 2. Run the notes through Gemma locally (free, private, no cloud). Read every output yourself. 3. Write down the 20 issues that keep showing up: missin...

real talk, if you've ever wanted to build something (the app, the store etc) and make a bigger life than the one you were handed, now's the time it honestly fires me up so much we're living through the cheapest, most open moment in history to make something big from nothing

What breaks your AI agents?

I think building a crowd sourced niche dataset is one of the most UNDERRATED bootstrapped businesses in the AI AGE: (think LevelsFYI, Glassdoor, Zillow etc but for any niche) 1. Your users build it for you by adding their own data (it gets more valuable with every entry) 2. AI agents now need clean, trusted data to make decisions, and they'll pay to query it on repeat 3. Cloudflare (and others!) are building the rails for agents to pay per query, so this becomes real recurring revenue 4. One dataset sells to many buyers at once: consumers, companies, and now agents 5. Charge three ways from the same data: free for contributors, paid for pros, API access for the agents 6. The narrower the niche, the more defensible it gets (you own a corner nobody else has) 7. Frontier models are hungry for data (and are a great customer) 8. The wedge: give a teaser amount of data, then make people add theirs to unlock the rest (ask for data or email) 9. LevelsFYI was brilliant because people will hand over their own salary just to see what everyone else makes (human nature) Big fan of these types of businesses in the AI age. Low risk, high margin, and they get stronger the longer they run!

I've seen 100+ people post GPT-6 Astra demos where it builds 3D games, and those are cool, but that's honestly not the part I can't stop thinking about. Millions of people can turn an idea into a printable object, a CAD file, a Blender model, or a circuit board, without having to become a full time 3D designer first. So how many thousands of $1M+ businesses come out of that? Well, you'd pick a niche that constantly needs small custom parts. A few examples: 1. Gyms with broken equipment pieces 2. Restaurants missing some weird proprietary clip 3. Cyclists who want custom mounts 4. Small manufacturers stuck doing the same hand work every day with a jig they wish existed 5. Dentists and clinics needing custom jigs, guides, or tool holders You put up a simple page where someone uploads a photo, adds measurements, and describes the part. Astra can do the first CAD pass, you sanity check the dimensions and material, and a print farm ships it. Of course, you need the idea/niche/distribution first, but you're in business. You just became a manufacturer, and it's kinda like your factory is a chat window. (I'll add more of these manufacturing ideas to http://ideabrowser.com) TLDR; In 2024, Lovable/Bolt/Replit/v0 etc turned anyone into a vibe coder. The effects of that are still playing out but we're seeing basically anyone create websites/apps. In 2026, OpenAI turned anyone into a vibe manufacturer, this shift just started. Really big deal and underdiscussed.

RT Greg Brockman Astra for helping in your personal and work life

It's honestly too fun to build a company with AI right now. This is the most creatively alive I've felt building ever? I hope you're having fun.

9 cool GPT 6 Astra prompts worth trying: 1. The bill renegotiator. "Go through my internet, phone, and software bills, jump into each provider's chat support, and negotiate them down or cancel what I'm not using." 2. Turn an agency into software. “Pick one service business in [niche] and reverse-engineer the exact workflow they sell to clients. Break it into steps, tools used, inputs, outputs, human judgment points, and places where the work gets slow or expensive. Then design the simplest AI product that could replace the first version of that service and charge $500-$5,000/month.” 3. Garage sale flipper. "Watch Facebook Marketplace and Craigslist in my city for [cameras / furniture / bikes] listed way under market, and text me the second one's mispriced with the link." 4. Create my 1 person company dashboard. “Look at my docs, notes, Stripe exports, analytics, customer calls, and project list, then build a weekly operator dashboard. I want to know what is making money, what is wasting time, what customers are asking for, what I should stop doing, and the three highest-leverage actions for next week. Be blunt and show your work.” 5. Audit my company for agent opportunities. “Look at how this business works and find the tasks we should give to agents before hiring another person. For each task, estimate the current human time, the cost of mistakes, the tools involved, the difficulty of automating it, and the first safe version we could deploy. Prioritize things that save money or create revenue within 30 days.” 6. Be my browser operator. “Use the browser to complete this workflow: [workflow]. As you go, click through the actual sites, collect the data, fill the forms where appropriate, and keep notes on what broke or slowed you down. When you’re done, give me the output, the repeatable SOP, and the automation plan so this can become an agent.” 7. The whole QA team. "Every night, open my app on a real phone, go through signup, checkout, and the main flo...

HOW TO FIX YOUR AI AGENTS (it's called "self-healing agents") If you've run AI agents, you know they BREAK constantly. The FIX is something called a "self healing" agent! A normal agent hits a dead end and just stops, leaving you a half finished mess and that's why output sometimes isn't ideal. BUT, a self-healing one hits the same wall and thinks "okay, that didn't work, let me try another way" HOW TO BUILD SELF-HEALING AGENTS (4 steps): 1. Make it check its own work. After each step, the agent asks "is this what I expected?" instead of assuming it worked and moving ahead. 2. Have it name what broke. Not just "it failed," but which kind: the tool timed out, returned an error, came back empty, or gave a wrong answer. Wrap your tool calls so the error gets passed back to the agent, because it can only fix a failure it can actually see. 3. Match the fix to the failure. Glitch, retry it. Tool down, switch to a backup. Keeps failing, break the task smaller. Anything risky like money or deleting data, stop and ask you. 4. Make it log every fix. It writes down what broke and what worked, so it stops repeating the same mistake in a session, and you get a list of what to fix at the root. That's it. Now, you've got agents that fix themselves.

I think we've reached the point where new AI model releases all kinda blur together. I honestly can't keep the names straight anymore. It's all numbers, decimals, and words like Pro, Ultra, and Max. At this point half of them sound like energy drinks. But I actually think that's a good sign. It means we've moved past the phase where the model itself was the product. I still pay close attention to new models. I've just changed what I'm paying attention to. 2 things I've noticed (maybe you've noticed it too?): 1) I've stopped caring about benchmarks completely. The only question I ask about a new model now is which of my someday ideas just became a today idea. What can I build this week that I couldn't last week? 2) The models are turning into a commodity you'll never think about. In 6-12 months you won't know or care which one you're using, the same way you have no idea which power plant your electricity comes from. Your agent just grabs whichever is best for the task, switches midtask if it needs to, and never tells you. Being an openai person or a claude person is about to sound as silly as being loyal to one electric company. I'll still cover the big releases on @startupideaspod, but only when one actually changes what you can build. Anyway, just kinda venting. Am I the only one feeling this?

AI agent startup idea for you ($100B+ market) Agent Relationship Management (ARM) is the new CRM. I haven't seen anyone really talking about this, so let's get into it. Let's just assume that within the next 36 months, every internet user will have their own personal agent. I think that's where we're heading and not crazy to say that. In that world, there's a huge gap in how companies deal with agents, a whole new set of problems nobody's built for yet. Like: - Can an agent even access your data, or does it hit a wall the second it tries? - Can it buy from you without your checkout breaking halfway through? - Does it trust your proof over the competitor's, or do you look sketchy to a machine? - Are you on the shortlist its agent built, or did you never even show up? None of that is what CRM ($100b+ market) was made for because CRM managed how you deal with people. and this is about how you deal with the agents acting for them, and there's no Salesforce for it yet. So someone needs to build the system of record for it. Where a company goes to see how agents perceive them, where they're winning the shortlist, where they're getting skipped, and what to fix. (this is exactly what we do at @meetLCA. If you're serious about designing for agents, DM me, we're booking 2027 now, I'll respond if it's a fit) And then it cascades: 1. The winners stop competing on the prettiest UI and start competing on the best action layer, the cleanest set of things an agent can actually do. 2. Which means websites split in 2: a nice side for the humans still visiting, and a machine readable side for the agents 3. Which means the stuff companies hid behind, brand, nostalgia, a familiar logo, stops working, because an agent feels none of it and just picks what's actually best. 4. And the whole idea of selling flips. CRM was about nurturing a human, the follow-up, the demo, the relationship. ARM is about how you pitch, prove, and win over a machine that reads everything and ...

NVIDIA just released a repo that scans AI agent skills for security risks BEFORE you run them, which matters more than people realize now that everyone's installing random tools, skills, and MCPs from GitHub. I break down that one AND 4 other GitHub repos trending over the last 30 days in this episode of @startupideaspod: 1. A skill that kills AI slop finally (better writing) 2. A CRM thats built for AI agents (so you can have agents follow up, reach out etc) 3. An agent that edits your videos for you (so you can focus on creative) 4. An opensource CapCut alternative built for agents (because editing is a headache) All free, all open source. Watch my breakdown of the 5 GitHub repos trending over the last 30 days below http://youtu.be/9_SZFIW7tus?si=lhIbLbtR18aeJ0XA The tools people will be talking about in six months are on GitHub today. That's the fun part of digging through GitHub right now.

AI AGENT STARTUP IDEA FOR YOU ($15B market) Yesterday, a friend mailed my newborn a stuffed manatee from Canada, the CUTEST thing, and then I got HIT with $93 in tariffs just to receive it which is more than the manatee cost!! The more I realized this is happening to MILLIONS of people right now, because between the new tariffs and the way cross-border shipping works, everyone's getting surprise fees at the door. A big chunk of those fees are either overcharged, misclassified, or straight up refundable, and nobody has the patience to sit on hold with customs to find out. HOW IT'D BUILD THIS The whole thing starts as an agent that reads your customs and shipping paperwork, the commercial invoice, the HS code they slapped on your package, the duty they charged, and checks it against what you should have actually been charged, because a shocking amount of this stuff gets misclassified by whoever filled out the form in a warehouse. When the agent finds an overcharge, it files the refund claim for you, and you split whatever comes back. Zero risk to the customer, which is the whole reason they'll say yes. HOW I'D GROW THIS I'd make content around the pain they already feel, videos and posts of people reacting to insane import fees on normal stuff, a $93 tariff on a stuffed animal, a $200 fee on a pair of shoes, and every one of those becomes a lead magnet where you drop in "paste your receipt and we'll tell you in 30 seconds if you got overcharged." You can also lean into all the people that hate Trump and his tarriffs, no doubt that’s gonna work. THE WEDGE That free checker is the little wedge product you build. Most people find out they overpaid, you file for them, and now you've got a customer who tells every other person who's ever been burned at the door. HOW TO SCALE Once you've got volume on the consumer side, there’s a huge business in the data. You'll know exactly which shippers, which product categories, and which customs brokers overcharge the mo...

Before I hire anyone now, I run 2 questions in my head: 1. Can an agent do this? (Grokbot, Hermes etc) 2. What do I lose if I do? I think hiring a human has become something you earn your way into and not the default anymore.

The "marketing engineer" is the NEW forward deployed engineer, and I think the BEST ones will make $1M a year! A forward deployed engineer embeds with your team and uses AI to build the workflows The marketing engineer does that BUT for growth, they build AI agents that find your customers, write your outbound, test your ads, and get smarter every week. The most valuable marketer changes with EVERY major tech wave: 1. Traditional marketer: make people care with story (print, radio etc) 2. Digital marketer: the marketer who owned new digital channels (SEO, PPC) 3. Growth hacker: the growth marketer who lived in loops, PLG and retention 4. Marketing engineer: the marketer who builds AI agents that run the whole system. The type of agents a marketing engineer would create: 1. The customer language agent. It pulls your Gong call transcripts, your Intercom tickets, and your G2 reviews every week, extracts the exact words customers use to describe the problem, and drops a memo ranked by how often each phrase shows up. 2. The buying trigger agent. It watches for signals that someone's ready, a company posting a job for the role you sell to, a funding announcement, a competitor getting torched in a review, then enriches the contact through Apollo and drafts the outbound tied to that exact trigger the second it fires. 3. The SEO gap agent. It pulls keyword gaps from Ahrefs, checks who's already ranking on page one, reads the top three results, then writes a better post with the founder's actual take baked in, plus the meta title and internal links, and drops it in for approval. 4. The creative testing agent. It takes one offer, generates 100 ad variations across three different angles with Nano Banana and your copy model, pushes them live through the Meta API, and kills anything under a 1% CTR on its own so only the winners keep spending. AND MANY MORE. If you're a marketer, this is how you stop being replaceable. If you're a founder, this is how you grow your ...

I think we're going to see a lot more creators buy dying public companies (sorry private equity) GoPro is down 98% since IPO. Markiplier (38M subs) is the customer, and knows exactly how to grow it. Creators are the new private equity? Honestly, smart.

Pretty crazy that my company spent $20,987 mostly on AI tokens this month. It's not like someone said hey let's spend $20k a month on AI, it just kinda crept up token by token until one day it was the biggest line on the card. Probably created $200,000+ of value this month.

Everyone is open sourcing everything right now. Why? AI made software a commodity. So you don't sell the software anymore, you sell everything around it: the hosting, the support, the enterprise tier, the trust, and the community. Open source is the default now!

I think cold email is going to die. Every email inbox will have an agent gatekeeper soon, and the only way through will be a warm intro or being interesting enough that the agent decides you're worth its person's time.

https://x.com/i/article/2093776326561873920

The best model today might be closed, and that’s fine, use it when it makes sense. But every serious company that uses AI should have a plan for open models, local models, and model switching, because AI is becoming too important IMO to build on top of a door that someone else can close. Kinda like you shouldn't bet 100% of your business's marketing on one social feed's algorithm.

The best model today might be closed, and that’s fine, use it when it makes sense. But every serious AI company should have a plan for open models, local models, and model switching, because AI is becoming too important IMO to build on top of a door that someone else can close.

It really is the GOLDEN AGE of hardware startups. For basically all of history, hardware was the worst business you could pick. You needed a factory, a supply chain, a hardware engineer, tens of millions of dollars, and 2 years before you could even find out if anyone wanted the thing. That's why almost nobody did it, and the few who tried mostly died on the manufacturing. What's happening now is that every one of those walls is coming down at the same time. 1. The brains got cheap because open source models can run the thing for basically nothing. 2. The design got free because the whole robot is open source, so you're not starting from a blank page, you're forking someone else's working robot and changing what you need. 3. The manufacturing is increasingly something you can contract out in small batches instead of betting the company on a 10 000 unit order. So now you're able to create a $399 that used to cost like $3999 not long ago. The thing I keep coming back to is that this is the same pattern software went through, just 15 years later. When building an app got cheap, we got a million businesses nobody could have predicted. Building a robot just got cheap. I'll add some hardware ideas to http://ideabrowser.com (literally free to sign up to get validated ideas) TLDR; We're about to get the same EXPLOSION, except this time it touches the physical world. I'm not surprised NVDIA agreed to buy HuggingFace for $12.9B. The hardware wave is COMING. What do you think?

RT Vinny Wanna learn more about WebMCP? Now that OpenAI is integrating it into ChatGPT, you should. Greg and I get into it, along with the potential for entrepreneurs to utilize this tech to their advantage:

WebMCP by Microsoft and Google is HERE and I'm surprised more people aren't talking about it. Why does it matter? BILLIONS of dollars are about to move through agents, and the internet isn't built for them yet. 1. SEO was about Google understanding your page. 2. AEO was about AI citing you. 3. WebMCP is about the agent actually finishing the job (buying, researching, requesting quote etc). WebMCP is basically websites with agent buttons. Instead of an agent scanning a page like a human, screenshotting and guessing where to click, the site just tells it "here's how to search, here's how to book, here's how to buy." 2 cash flowing businesses you could start today using WebMCP: 1. A WebMCP conversion agency Make boring business websites agent-ready. Law firms, HVAC, med spas, dentists. Build them the first tools (request a quote, book a consult), sell the setup for $2k, then charge a few hundred a month to monitor and improve it. 2. An agent mystery shopper. Test whether agents can actually complete the important journeys on someone's site, buying the hoodie, booking the consult, filing the claim. Hand them a report on where the agent got stuck, missing tools, bad descriptions, lost conversions. Charge monthly, then turn the repeated fixes into software. Full episode on @startupideaspod with @hot_town below http://youtu.be/EoNH3Tn8wYE?si=vqaNLrrNTfrnlBtB You'll learn what WebMCP really is, see examples of it IN ACTION, and hear more about 2 startup ideas using WebMCP you can start today. WebMCP is pretty cool. Watch.

Someone should build GitHub for normies. Now that anyone can build software with AI, millions of non technical people are making apps, but they have nowhere to store, share, or show off what they built. GitHub was made for engineers and it feels like it. You're starting to see personal software platforms emerge like Wabi, I think this only gets bigger. The version built for regular people, dead simple, visual, no git commands, is going to be huge.

This is the MOST asymmetric window I've ever seen in business. It's honestly hard to comprehend. Never in history have this many categories opened at once, ALL ripe for the taking: 1. Take a boring business doing 20% margins, an accounting firm, an IT shop, a local service company, and swap the human labor for agents until it runs at software margins with customers it already has. This is the Thrive Holdings model. 2. Build the picks and shovels, the clean API or data source that agents call 1000 times a day, and get paid per call instead of per user. I call this being in the building blocks business. 3. Buy a sleepy SaaS with real customers and a tired founder, then rebuild it AI native and 10x what it can do while building a media machine along side it. 4. Run a service business that looks like an agency on the outside but is really you plus a team of agents doing the delivery, priced like consulting, delivered like software. 5. Watch what people are still hiring for on Upwork, the "data entry specialist," the "appointment setter," the "research assistant," and build the productized agent that replaces that exact role, then sell it to every company posting the job. Vertical agents are here! I could keep going forever but you get the point. Contrary to what a lot of people believe (AI is coming for us, you need to raise venture to compete etc), the opportunity right now is endless. You don't need to quit your job. Finally, you can build a real startup on the side. It's starting season. If you've EVER thought about starting a something of your own, this is the moment to stop thinking about it. Seasons like this don't last forever. Start.

I went live to react to some of my fav tweets of yours from the X timeline like a $1m baby iOS app, how to actually make a company AI native, and why iMessage agents are becoming a real category worth watching. Laughed a lot. Full stream below.

Some days I feel like I’m the only one not on peptides Anyone feel the same?

AX is the new UX. Software was built for humans clicking, now it gets rebuilt for agents. Stripe just paid $8B for OpenRouter betting the main user of the internet is an agent. Rebuilding all that software is 1000+ new companies. The most obvious opportunity in a long time!

it really feels like open source is having its moment

RT Elon Musk Cool

RT The Startup Ideas Podcast (SIP) 🧃 http://x.com/i/article/2090900582223814656

Grok Bot might be the first tool that lets one non-technical person run an entire business with a team of AI agents. My friend Billy runs his whole newsletter business on Grok Bot agents, and I think we're about to see 100,000+ businesses like his. BEST PRACTICES: 1. The agents run on a shared cloud computer, so running your newsletter, your X, and your receipts all in one place creates context bloat and burns tokens fast. One mission per setup. 2. Start with a Chief of Staff. Give it access to your existing docs (Notion, Slack, Gmail), have it audit the business, then tell you the top three agents to build first to drive revenue. 3. Perfect a task with the Chief of Staff before spinning up a new agent. Have it do the outbound sales once, review it, and only then say "now build a bot that does exactly that." You earn each new hire by proving the task works first. 4. Constraints are the feature. You get a limited number of agents, one thread per bot, like DMs with a teammate. It forces you to stay mission-oriented instead of spinning up a bot for every random idea. 5. You make the decisions, not the agent. Billy's team spent three weeks unable to pick where content should live. At some point you say "we're doing Notion, no more tinkering" and move on. 6. Run week one with no new agents. Build the team, learn to fly the plane, just execute. Week three is when you find the real gaps and expand, someone to man the inbox, someone for the Shopify shop. 7. Then add routines so it works while you sleep. Ask your Chief of Staff what recurring jobs would move the business forward overnight, and it builds the automations that run without you. Thanks to @billyjhowell for sharing the sauce on @startupideaspod (follow for more). Grokbot is really cool. Watch below: http://youtu.be/qQluNEfSVHk?si=3L2cAB71NQSuqxWU

I miss japan

2008-2025: "There's an app for that" 2026-????: "There's an agent for that"

vibe coding is now just coding

BOOTSTRAPPED VS VENTURE BACKED STARTUPS If you run a bootstrapped business using VC strategies, you will lose. They are different games with different rules. I REALLY felt how different while listening to Travis Kalanick on David Senra. Travis subsidized rides to buy the market, ate massive losses on purpose to spin up the network effects, and went from a $6B to a $17.5B valuation in 2 months to turn money into a weapon. It's a masterclass. And if you're bootstrapped, most of the movse he describes belongs to a different sport. I've built and sold VC-backed startups (one to WeWork, the most VC thing that ever existed lol), and now I'm building a bootstrapped holdco, so I've felt both. Underpricing to zero is genius in VC and suicide bootstrapped. Taking a dividend is smart bootstrapped and crazy in VC. Every strategy only makes sense inside the game you're actually playing. Same words, growth, win, competition, mean opposite things depending on which game you're in. And there is no right game or wrong game. It's a really personal thing. Some people watch Travis talk about turning money into a weapon and going to war for a market, and they get fired up, that's their game, and they should go raise and swing for the $10B outcome. Some people watch the same clip and think that sounds like a nightmare, they'd rather own the whole thing, get paid every month, and answer to nobody. I think both are great. You just have to know which one you are. They're just different lives.

Send this to ANYONE on your team using AI agents with Claude/Codex skills: If I were you, I'd put your BEST AI skills in a GitHub repo, turn that repo into a PLUGIN, and have your team INSTALL it in Claude/Codex with auto update on. Why? 1. Everyone gets the same AI SOPs instead of 10 versions floating around Slack 2. When one person improves a skill, the whole team gets the better version. 3. New hires can start with your best workflows instead of a blank AI setup (this is a BIG deal). 4. If someone breaks a skill, you can roll it back with version control. 5. Personal skills can stay personal, while team skills become shared company infrastructure (and an asset!). 6. Your best AI processes stay with the company when someone leaves. 7. You can chain skills together for bigger workflows, like titles -> thumbnails -> descriptions -> YouTube publish. 8. You can track which skills are actually being used and delete the ones collecting dust. 9. You get less slop because the agent has real instructions, examples, taste, and process. 10. Your team moves from single-player AI to multiplayer AI. (thanks to @aiwithremy for coming onto @startupideaspod) Watch full breakdown here (clearly explained): https://youtu.be/xHsftiyT9pQ?si=pcwqatvS7u3cf3Ne I don't know why I didn't do this before. The more I think about it, the more obvious it feels: your AI workflows should be version controlled company assets. It kinda feels like the difference between “we use AI” and “we actually operate with AI". Enjoy.

I don't think we're ready for how much the internet is about to change within the next 36 months because of super intelligence and AI agents

The biggest lie 12 months ago was the narrative that GPT wrappers were useless/you were dumb building a business on top of the LLMs, and now we're seeing dozens of them worth billions and hundreds of these companies worth $10M + There's a lesson there?

9 things that took my Claude Code from okay to unreal: 1. Workspace: a repo that explains itself 2. Memory: the files that tell it how you work 3. Brief: plan mode before it touches anything 4. Ticket: one clear task with a finish line 5. Eyes: it opens the app and clicks through like a customer 6. Review: it checks its own work against your standards 7. Schedule: routines that run while you sleep 8. Permissions: what it can do freely vs what stays with you 9. Skills: reusable actions, plus connectors and hooks Note: thanks to @AnthropicAI for sponsoring today's ep. I go through all 9 with the exact prompts/best practices and a 7 day plan to set it up in the full episode. Once these are in place, Claude Code just hits different Watch http://youtube.com/watch?v=SkY-tR9kf-k&t

Running list of AI agent ideas to make you more productive and more money: 1. The onboarding rescue agent. Watch PostHog for any new signup who stalls on the same step for more than 10 minutes, then have an agent send them a Loom style personal message or a CustomerIO email that answers the exact thing they're stuck on before they give up. 2. The pricing page bounce agent. Fire a PostHog webhook when someone hits your pricing page twice and leaves, have the agent enrich them with Apollo, and send a short email with the objection handler for their specific company size when it matters. 3. The second product in support agent. Point an agent at your Intercom/Plain inbox etc and have it tag every request that isn't actually about your product, the adjacent thing people assume you also do. It ranks them by frequency. 3. The you already answered this agent. Have an agent read your sent folder, your Intercom replies, and your sales emails, and pull the clearest explanations you've ever written about your product. It drops them into a swipe file your landing page and cold emails pull from. 4. The internal tool to product agent. Point an agent at your team's GitHub scripts, Retool apps, and Google Sheets, and have it flag the ones 10 other companies in your niche would pay for. 5. The review mining agent. Apify scrape every review of your top 3 competitors on G2 and Capterra, cluster the 1-star complaints with Claude, and get a ranked list of the features to build and the exact words to use in ads to poach those unhappy customers. 6. The sell what you give away agent. Once a week, feed your Granola/Gmeet call notes and Intercom threads into an agent that hunts for every task your team did for free that took more than 30 minutes. It clusters them, counts how often each came up, and ranks by demand. The top 3 become paid add ons. 7. The win pattern cloner. Pull your last 50 closed-won deals from HubSpot or whatever CRM you use, have an agent find the firmographic tr...

The question I get most right now is "what should I turn into an AI agent?" Here is the 5 part test I use (works for Claude/Codex/Grokbot etc): 1. It has a repeated trigger, so the same kind of task keeps happening over and over. 2. The inputs are stable, so the information comes in a predictable shape every time. 3. The tools are clear, so there is a defined set of things it can actually go do. 4. There is a measurable finish line, so you can tell when it is done and whether it worked. 5. There is judgment in the middle, so each run is a little different and needs a real decision made in the moment. The first 4 are really just asking "can this be automated at all?" The 5th is the one that matters, because judgment in the middle is what makes it an agent instead of a simple automation. Once you see it this way, you start spotting agent work pretty much everywhere.

Stop asking "can this be an AI agent??" Start asking: is there a repeated trigger, are the inputs stable, are the tools clear, and is there a measurable finish line? Four yeses and you've probably found agent work.

One of the biggest consumer AI opportunities is helping people close the tiny loops they keep avoiding. Think about the 47 little things sitting on your list that you keep not doing. Emailing back the person you owe a reply, disputing the wrong charge, rescheduling the appointment, things like that. Each one is small, but each one requires digging up context, making a decision, and sending a slightly uncomfortable message. So they just kinda sit there lol. The opportunity is an agent that does the hard 90% of each loop, finds the context, makes the call, drafts the message, so all you do is hit send. The wedge is going after one loop first and nailing it. Examples: 1. Warranty and rebate claims. People throw away hundreds because filing feels like homework. The agent watches your purchases, knows what's claimable, fills the forms, and hands you the check. 2. The "I should switch" loops. You're overpaying for insurance, your phone plan, your electricity, and you know it, but comparing is a slog. The agent monitors and drafts the switch when it's clearly worth it. 3. The kid-logistics loop. The permission slip, the form the school needs signed, the birthday party you never RSVP'd to, the summer camp that's about to fill up. For any parent, it's a hundred tiny deadlines a month, and the agent catches each one and drafts the response. Things like that. Just giving some ideas to get the creative juices flowing. Tons of apps like this will be created over the next 12 months. It just makes sense.

i agree

The BEST prompt for AI agents I've heard over the last 12 months is ONLY 3 words, and it comes from someone who managed multi-billion dollar P&Ls in AI, led a 100 person org at AWS, and now runs a brilliant AI workforce of 34 agents: 1. Her best prompt is just "do smart things" She gives the agents all her context first, her calendar, email, Stripe, goals, and transcripts, then lets them decide what's worth doing. She realized every task still started as a thought in her own head, which meant the company could only ever be as good as what she remembered to ask for. 2. Her human team talks to her agents in Slack. She has a channel where a teammate can ask "did that financial services client reply to Ali's email," and the agents answer directly, so people stop waiting hours for her to get back to them. 3. Since an AI agent costs almost nothing, she hired the person she'd never put on payroll. One does nothing but ask how to make everything ten times better. Another just watches the other agents work and flags where they get stuck. 4. She avoids old job titles, because the second you call one your CMO, you've rebuilt a 2015 company with robots. Most of her sub-agents run on cheaper, smaller models and do the job fine. 5. Run an AI watchdog instead of a dashboard. Point one at your Slack to catch two people doing the same work, at your calendar to flag conflicts, at your analytics to tell you what to post tomorrow. Almost nobody does this yet. 6. She keeps a daily "brain dump" that feeds the agents. At the end of each day she dictates what's in her head that isn't written down anywhere, the stuff that only lived in a meeting or a Slack thread, and it goes into a wiki the agents read. That's how they get the context that email and calendar miss. 7. She uses a "last 30 days" research skill to spin up on anything fast. Before running a workshop for 200 execs in an industry she doesn't know, she fans out agents to scan and synthesize the last month of news, then...

Cloudflare just made it possible to charge AI agents to access your site. Sounds small, but it's not. It's the start of an internet where agents are the customers and websites are the resources they pay to use. Watch: http://youtube.com/watch?v=MNNfat_QP0E&t

23 ways I'd use AI agents to grow my startup to $1M ARR or PMF (my running list): 1. An agent read your Stripe refunds/cancellation reasons, then trigger a different CustomerIO sequence for each, so the person who left over price gets a discount and the person who left over a bug gets a "we fixed it" email. 2. Wire an agent to your PostHog feature flags and have it race two onboarding flows on live signups, auto killing whichever activates fewer people each week. An A/B test that prunes itself!! 3. Watch your competitor's status page, and the hour they go down, spin up Google Ads targeting "[competitor] alternative" while their users are actively searching. (kind of ruthless, kind of brilliant) 4. Feed an agent your closed-lost deals, have it draft a personalized reopen email for each, and drop them in your outbox for 1 click send. 5. Turn your best customer's onboarding into a playbook.md, then run every new signup down that exact path so your best outcome becomes the default. 6. Point an agent at your inbox for positive-sentiment messages and auto-send a Senja review request while the customer is still glowing. And then your G2 page fills itself. 7. Watch for the moment you solve someone's support problem and fire the referral ask right then, while they're relieved and grateful. Timing is everything on referrals. 8. An agent watch your Stripe data for annual customers who never log in, and reach out to re-onboard them, because realistically silent renewers are one bad quarter from canceling so get ahead of it. 9. Catch pricing page bouncers via a PostHog webhook, enrich them with Apollo, and send the objection-handler for their specific industry before they forget you exist. 10. Build an agent that continuously scans for new "best X" and "X vs Y" articles ranking in your category, and auto-drafts a personalized pitch to each writer asking to be added as an option. 11. Use Apify to scrape everyone who liked your competitor's launch post, waterfall th...

The new org chart probably looks something like this: A small layer of humans on top doing strategy, creative, and judgment, with a wide layer of agents underneath running support, sales, research, marketing, ops etc Managing people became managing agents, and managing agents is really just managing context (which is a whole thing millions of people need to learn right now) That shared brain is the actual company now, and the humans and agents just plug into it. Both humans/agents come and go, the context is the thing that compounds and can't be copied. I keep thinking about that.

Dashboards are dead, agents are alive

A lot of agent startups should probably start as a daily text message (not a SaaS product!) Kinda like your smart co-worker. “Here are the 3 customers you should call today and why” etc Truth is, if the message is valuable enough, the interface can come later

A simple way to think about startup ideas: 2024: build a copilot for xyz. 2025: build Cursor for xyz. 2026: build an agent for xyz. 2027: build /loop for xyz.

Marketing agents are the new coding agents and every marketing channel is RED ocean now because AI slop FLOODED all of them How to actually build marketing agents that work (2 real examples, all tools shared, 43 minute masterclass) watch: http://youtube.com/watch?v=mD7JpNHLT70

"Graph engineering" clearly explained (and how it can get you more out of claude code/codex) Watch: http://youtu.be/JWhICz1QR8M?si=Lyb3jO03voQZU7oG

Every startup should have a daily markdown file called "what_the_market_is_telling_us.md" It updates every morning from the places where customer truth already lives: 1. Stripe for who pays, upgrades, downgrades, and churns 2. PostHog for what people actually do in the product 3. Intercom or Plain for support tickets/complaints 4. Granola or Gmeet transcriptions for sales calls/ customer interviews 5. HubSpot or Salesforce for CRM notes/lost deal reasons 6. Linear, Jira, or GitHub Issues for bugs and feature requests etc 7. Ideabrowser MCP for outside market signal: startup ideas, trend reports, social/search demand, AI research reports, and builder prompts that show what people are starting to want before it shows up in your own customer data. Basically, the file should notice what changed in the business this week and not just be this summary of here’s what happened (which I think a lot of people have their agents do). Why this is valuable: 1. Maybe new buyers are using different words than they were a month ago. 2. Maybe trial users are getting stuck in the same place. 3. Maybe upgraded customers all touched one feature right before they paid. 4. Maybe churned customers keep mentioning setup confusion. 5. Maybe sales calls are suddenly losing to a competitor you used to beat. 6. Maybe support tickets are revealing a workflow your product accidentally became responsible for. You get the point. The fastest way to PMF is understanding customers better than anyone else, and the highest signal customer insight is usually a change in behavior. So I’d have the agent update the file every morning with the pattern it found, the receipts behind it, and the product or GTM decision it might affect. For example: “3 customers who churned this week all mentioned setup confusion, and 2 of them never invited a teammate. This looks more like an activation problem than a pricing problem, so I’d look at team invite and onboarding before building another analyt...

The biggest opportunities right now: 1. build for solving loneliness (the more AI floods everything, the more people crave real human connection, IRL and small social) 2. build for agents that need to spend money (they're getting virtual cards and budgets, someone builds the spend controls, fraud protection, receipts) 3. build for people drowning in AI output (everyone generates infinite drafts now, the bottleneck moved to reviewing and choosing, build the judgment layer) 4. build for the burnout economy (everyone is expected to always be on and always optimizing, and the backlash toward rest, slowness, and enough is building) 5. build for verifying humans (deepfakes broke trust, every dating app, marketplace, and video call needs proof-of-human within 2 years) 6. build for the physical world (the trades, hardware, robots that AI is finally reaching) 7. build for the agent that answers the phone (every local business misses calls after 5pm, a voice agent that books the job is worth thousands a month) 8. build for the aging (70M+ boomers who want to stay healthy, sharp, and connected) 9. build for the LLM-search land grab (being the cited answer is the new SEO) 10. build for the newly automated (the paralegal, the analyst, the marketer whose job just changed and needs to reskill fast) 11. build for the seat-pricing collapse (software repricing from $50/seat to per-outcome, whoever nails outcome billing wins a category) 12. build for AI enablement (95% of businesses use nothing beyond ChatGPT, someone has to onboard the other 95%) 13. build for the agency everyone resents (businesses pay $1k/mo to agencies they hate, an agent that does 80% of it undercuts the model) 14. build for verticals on 2011 software (dentists, HOAs, contractors, all overdue for an AI-native rebuild) 15. build for reviving dead software (thousands of abandoned apps with real users, agents can maintain what a team couldn't, buy and revive) 16. build for markets too small to matter...

forget virtual reality, the next big thing is actual reality

we are going to witness a golden age of hardware startups because the cost of intelligence is collapsing open source models commodity robotics global manufacturing ai design tools hardware is becoming software

Software is dead? No way. Let's discuss. See you there. https://x.com/i/broadcasts/1yGBeenOQBLKN

Every year it's the same. Something is dead, the window closed, it's too late And every year, the people who ignore it and just build put themselves in a position to get "lucky" Maniacally focus on driving a huge amount of value for customers with real problems and keep going!

Call me crazy but I don't think software is dead There's a wave of doomerism right now about no opportunities left, and honestly I just don't see it I'm going live today on X/YT at ~2:30PM EST to break down why. Come through, bring your questions Have a creative day, friends.

RT jack thanks greg!

EVERYTHING you NEED to know about Jack Dorsey's AI agent "Slack killer" Buzz (set up, use-cases etc in 38 mins) What we get into: 1. What Buzz actually is and should founders switch from Slack? 2. How to swap the model under any agent and keep all your context? 3. How to talk to your agents live with audio huddles? 4. How to get agents to build and deploy real apps for you, like a full CRM from one ask? 5. How to set up the context loop that feeds your live app data back to your agents? 6. How to share compute so a few people split one machine running a local model? 7. Who it's actually for right now, and what's still rough? Full breakdown on the pod @startupideaspod. Thanks to @hot_town for jumping on and clearly explaining @jack and team's latest product. My TLDR take is Buzz is a glimpse into the future of work. Some of you will roll your eyes at that, and I get it, it's alpha software and it's slow in places. But the core idea, that your context is the foundation and agents build out from there, is right, and that's worth seeing early. Watch http://youtube.com/watch?v=_jGSgzBkzrY Curious what you think

People are often surprised to hear that my podcast (2M+ listens/month) is literally just me and one producer + freelance editors. You don't need a lot of people to make videos, you need a system, curiosity, desire, and reps. I've done 790 videos since 2021, so at this point it's second nature. The real trick is I'm not doing this full time. I'm running companies all day, and that's actually where the content comes from. I'm taking notes on what I'm learning as I go, and when something's interesting I tell myself to come back and make something out of it. Or I'm in a meeting with someone sharp and I go "you should come on the podcast." It's not a second job I bolt on, I just made it part of how I already live and work.

Marketing agents are the NEW coding agents. It's code in the cloud that makes decisions off your live business data on a loop. It researches, acts, reads the results, improves, and goes again. Picture an agent that runs your entire Facebook ad account by itself. It researches your customer's pain points, generates on-brand creative, publishes it, kills the losers, scales the winners, and makes more of whatever's working. We show you the EXACT stack. Perplexity to scrape Reddit for real pain points, Nano Banana for on-brand static creative, a vision model to check it against brand guidelines, HeyGen for AI UGC video, all wired into a loop that reads Facebook's data and reacts. Now point it at a business. What are some startup ideas you can point marketing agents to? WordPress runs 43% of the internet. Take the plugins people already pay for, like Yoast, WooCommerce, and WP Forms, and build the AI-first version of each. Examples: Yoast (~$15M ARR) shows you red and green dots and tells you to fix your SEO yourself. The AI version just does it. Proven demand, no AI-native competition, and thousands of site owner pay agenices $1,000 a month and many wish they'd pay less and got more. Coding agents changed who gets to build software. Marketing agents change who gets to grow a company. Full breakdown on @startupideaspod. Thanks to @codyschneider for the sauce. Will break down more marketing agents if people are interested? Just LMK. Watch. http://youtube.com/watch?v=U2hogriGmEw I'm rooting for you and happy growing. I think we've heard a lot about coding agents recently. And we're about to hear a lot more about marketing agents.

M&A is going nuts right now for AI startups. It's Monday at 10:58am and 2 people have already emailed me trying to buy my company, unsolicited. The X timeline is saying the "death of software" and RIP good times, I think there are TONS of buyers to scoop up AI native startups (with EBITDA). Some data: 1. Startups buying other startups jumped 18% in the first half of last year, driven almost entirely by a 30%+ surge in early-stage deals. 2. Private equity is sitting on over $2 trillion in dry powder and competing so hard they're paying about 3 turns of EBITDA more than strategic buyers just to win deals. 3. The market flipped to rewarding profit over growth: in 2021 growth mattered 2.5x more than profitability, and in 2026 a profitable business growing 25% beats one growing 50% while burning cash. This is one of the best times to build there has ever been. Cheap tools, hungry buyers, and insane opportunity to build the AI-native version of things. Anecdotally, based on a lot of people I know, there's a ton of M&A for startups that aren't reliant on Google SEO and built something truly AI-native in hardware, mobile apps, or vertical AI agents. Tune out the doom. Build something worth buying. Keep going.

There's panic right now that AI is eating indie software. I see it differently. For 10+ years you could spin up a few hundred auto-generated pages, rank them, and let Google send you signups for free. Now the answer people used to click your site for sits right inside ChatGPT and Google's AI overviews. If your whole business ran on that one faucet, the water's turning off, and it feels like the end of the world. And I've built a few of these projects, so I feel that darkness too. But let's look at the data. Has it really gotten dark/worse for software founders and indie devs?? Let's look a Stripe Data... New companies on Stripe Atlas are up 130% year over year. Companies are hitting $10M ARR within three months of launch at double last year's rate. One in five charges its first customer inside the first month, up from 8% in 2020. Fastest business formation anyone's ever recorded!! And the solopreneurs, the exact people saying they're getting crushed, are winning the most. 63% of new companies on Atlas are solo founded, and AI native solo startups pull 2.3x the revenue by month 24. This category was basically non existent at the scale we're seeing rn like 5 years ago. TLDR; So my thinking it's a channel shift wearing a collapse costume. The people hurting share one setup: they sell inexpensive tools to other indie hackers, and/or their traffic comes from SEO. That's the most exposed spot in the whole market, because your customers can rebuild your $20 SaaS in a weekend, and your traffic source is the exact thing the models replaced. Kinda feels like 2 cannons pointed at one little boat. Call me an optimist, but here's my take.... Building software is a bigger game than it's ever been. More companies, forming faster, making money sooner, run by fewer people, than any point in history.

RT jack the team did a great job at bringing this all together. and moving fast!

I think the most interesting thing about Jack Dorsey's "Slack killer" is the idea around shared compute. I haven't seen people talk about it so here are my thoughts FWIW: Open models got good, close enough to the paid frontier stuff to run for real. But the strongest ones need expensive hardware most people probably won't buy alone, and it's kinda a pain to set up if you aren't technical. Shared compute solves exactly that. In Buzz, one person runs the machine, loads up an open model like Google Gemma, and everyone in the community plugs into that same model. Basically, a whole group has real AI they own and control together, running on their own hardware, learning from their own data. Once you see it, a bunch of things click into place. 1. A community can now run a top open model together, on a machine they own, instead of renting from a lab. 2. It learns from the group's private data and gets sharper over time, and all of that stays inside the community. 3. A narrow, private model can quietly get better than ChatGPT for the one world your group lives in. 4. It's impossible to copy, because the edge is the private data on your machine, not the model itself. 5. The moat stops being how smart your AI is and becomes whose data it learned from. 6. Compute becomes something you share like a building shares a gym. 10 people split one machine instead of 10 people each renting forever. 7. Idle compute becomes income!!! Your machine sits dead half the day, so it earns money renting that time to someone who needs it. 8. Communities become the unit of intelligence instead of companies. The group with the smartest shared brain wins, and being a member means owning a piece of it. 9. A shared brain becomes an asset you build equity in. You put in money and data, it appreciates, and your slice is worth something the day you leave. 10. The whole thing runs on open protocols, so the group keeps full control and nobody outside can throttle it or shut it off. You know...

Are you an Opus 5 person or a Fable 5 person?

If your whole workflow is one Claude Code instance on your MacBook, you're leaving 10x on the table. Here's why. On your laptop, running 2 agents at once means two copies of your code, and you're constantly fighting over which worktree you're on and whether everything's synced. It caps out fast. Cloud agents in VMs let you run as many as you want without worrying about any of that. Each one gets its own machine, so the work never collides. Spin up 10, let them all run, and nothing steps on anything else. Watch full ep below on @startupideaspod. Thanks to @ryancarson for sharing the sauce. http://youtube.com/watch?v=vJEy3nP2_C8 Cloud agents are probably the future. So is doing half your work from your phone, which sounds insane until you try it once. Then you don't go back.

My favorite detail from the Opus 5 launch: they gave it a drawing of a machine part but blocked it from viewing the image. So it wrote its own computer vision code to read the raw pixels, then built the 3D model anyway. Nice to meet you Opus 5. Almost as smart as Fable, half the price.

OpenAI launched voice control for Codex on desktop yesterday and it still isn't the thing I actually want. I wish I could FaceTime with my Claude Code or Codex or Grok or Gemini. Right now I send a prompt, wait 5 minutes, and then I look at what it built and realize that's not quite what I wanted. Half the time I didn't know what I wanted until I saw it. That's how the best work happens with people, you're in it together, reacting in real time and jamming. The models can already see, hear, and act on my machine. Somebody just has to put all three in one window. Truly collaborative in the same way that Figma changed design. Before Figma, you'd mock something up, export it, send it over, wait for notes, and make changes. Then multiplayer showed up and suddenly you were in the file together, cursors moving around, fixing things while someone talked. Nobody went back. That's the moment building with AI is waiting for. At least I am. And I don't think it's just me. I'd call this feature "jamming". Whoever does this (frontier lab or startup) will make billions.

16 things that will be normal in 3 years and sound insane today 1. Somebody's entire job is making sure your agents don't do dumb things. 2. Kids grow up assuming any adult who types is old, the way we assume anyone who prints emails is old. 3. You get an itemized bill for what your agents bought last month and it reads like an expense report from a small company. 4. Someone you've never met sells you a business that runs itself, and you never learn what the code does. 5. Your doctor's first opinion comes from a model, and the human's job is deciding whether to trust it. 6. Job posts will say "must be able to manage agents" the same way they used to say "proficient in Excel." 7. The best-paid person at a company will be whoever's best at explaining the business to machines. 8. Your company has more agents than employees, and HR manages both. 9. Companies start hiding how few employees they have, because a lean team reads as fragile to enterprise buyers. 10. Your calendar fills with meetings you didn't schedule, because your agent and their agent worked it out. 11. The CV dies and gets replaced by a body of work an agent can verify in 4 seconds. 12. You interview an agent before you hire it. Give it a fake task, watch how it handles the weird cases, then decide. 13. Losing your job means losing your agents too, and it's kinda scary losing your best agents. 14. "Made by a person" becomes a label on products, and there's a certification body for it. 15. You'll have a folder of agents the way you have a folder of apps 16. Getting a human on the phone becomes a paid tier, and people gladly pay it.

I'm livestreaming, ask me anything. Literally anything. AI agents, life, startups, feedback on anything. I'll also be sharing the most interesting takes on X. Say hello below! https://x.com/i/broadcasts/1yGBeeoDNgMKN

Reply with anything you want feedback on, business or personal, and I'll answer as many as I can live tomorrow July 22nd around 9:45a EST. It could be feedback on your startup, a tough decision, an AI question, you tell me. Last time 5000 people tuned in. What's on your mind?

So let me get this straight.... 1. Agents are about to outnumber humans on the internet, so most of the traffic, transactions, and conversations online will soon be machines talking to other machines while we sleep. 2. Superintelligence exists now, and for $20/mo you pretty much get it all. 3. Cloud agents allow you to run a business 24/7 and from literally a phone while you're waiting to order a latte. 4. Voice AI is wide open. This industry has barely changed since the 90s. Infinite opportunities. Voice AI is finally getting good enough. 5. Mobile apps are interesting again for the first time in 10 years, because an AI-first app that thinks and acts on its own is a different species than the passive ones in the store today. There are kids doing $100k/MRR. 6. It's the golden age of open source. The models you download off Hugging Face for free and own forever are landing within months of the ones behind paywalls, so the smartest thing on earth can't be throttled, priced up, or shut off by a company having a bad quarter. 7. The keyboard is on its way out. We spent 40 years learning to type fast, and it's about to feel like handwriting, because soon you just talk and the computer goes and does it. 8. Every company is about to hire agents with their own logins, their own inboxes, their own track records, and a shadow economy is forming where agents pay, hire, and vouch for other agents. 9. Software stopped being something you buy and became something you rent by the hour. The whole industry is repricing from $50 a seat to thousands per outcome. Tons of opportunity. 10. Robots are about to have the moment software agents just had. The intelligence got solved. Now it's dropping into machines with arms and legs, and the people who can wire AI into hardware are about to be the most fought-over hires on earth. 11. The 10-person startup can now out-ship the 500-person company, and everyone can feel it happening. 12. Every white-collar task is getting a "do it fo...

RT vas Broke down AI Forward Deployed Engineering and why the biggest unlock for enterprises in the AI age. Give it a listen and let me know what you think. Will make more content like it if people find it helpful. Thank you Greg for having me on!

How to become a $1M forward-deployed engineer (FDE) in 30 days (and what FDE clearly means): - What an FDE is and why the role EXPLODED - The 3 stages of the job (business reality, judgment, building) - The exact 30 day roadmap to become one - What the top roles actually pay

If you know how to use Hermes, you know more about AI than 99.9% of people on this planet

Once you get used to using voice-to-text AI to get your computer to do things, typing on a keyboard feels kinda painful.

The thing I'm learning about business nowadays: to survive, you need to constantly reorient. You used to build a business, hit product-market fit, and then kind of coast. Now you hit PMF and the ground shifts 3 months later. New AI models, new algorithms, new tools that change what's possible. So you reorient, and reorient again, it's pretty constant. I'm noticing even companies doing $100M to $1B in revenue are sweating these days. They feel it too. But the cool part is if you reorient right, you get rewarded massively. That's kinda the trade. The stability is gone, but so is the ceiling. I've been reorienting my own companies more this year than in the last five combined. And weirdly, it's the most alive I've felt building. It's a good time to be a founder if you can move on a dime. For the experimenters out there, the people who actually like the constant change... I think this has gotta be the greatest time to be building there's ever been.

Every AI right now is a "yes man", and I'm soooo tired of it. Maybe you are too. I don't want an LLM that claps for everything I do. I want the one that tells me my writing is weak, my logic falls apart halfway through, and I've been lying to myself about the thing I keep dodging. You can engineer an AI with a spine. Here's the exact setup I use: 1. Write a "critic" skill. A markdown file whose only job is to attack the work. It hunts for the weakest claim, the dodged question, the thing you're avoiding. Every agent that loads it gets a spine by default. 2. Run two agents against each other. One builds, one tears it apart. The builder has to defend or fix. You get the truth from the friction instead of from a single agent trying to please you. 3. Score against evals. Give it a rubric with real criteria and have it rate the work 1-10 on each. A number tied to a standard forces honesty that "what do you think?" will always dance around. 4. Make it cite evidence for every criticism. Set a rule: no critique without a concrete example from the work and a reason it matters. It has to show its work, so it can flatter you or hand wave. 5. Give it a kill criterion. Tell it the exact condition where it has to recommend you stop entirely. "If X isn't true, tell me to shut this down." Most agents will optimize a doomed idea forever because you gave them permission to call it dead. I've learned that the default AI claps for you. That's cool for a bit but it gets old quick. If you actually want to build exceptional products, create top 1% work, and grow as a person, you need an AI that pushes you harder than it flatters you. We're in the age of agency. The people who win are the ones who go build the version that tells them the truth. Best time to build there's ever been. Go get 'em.

I'm still astonished that 12 months ago most engineers wrote code by hand, and now most code is AI-generated. Makes you wonder what's normal today that's gone by next year.

We are LIVE Chatting AI agents and answering your questions from yesterday's post. Also breaking down the 8 best AI/startup tweets on the timeline right now. https://x.com/i/broadcasts/1aKbddzgEeRJX