Muse AI Connectors COULD be the App Store moment for AI, and I think BILLIONS of dollars are up for grabs. When Apple opened the App Store in 2008, it gave developers access to millions of iPhone users, and less than two years later Apple had paid them $1 billion. Muse could create a similar opening, except instead of building apps people have to find and open, founders can build services a personal agent calls while completing a task. In today's episode of @startupideaspod, I explain how Muse Connectors work, how to build one with Codex or Claude Code, how people could discover them and 4 startup ideas I’d investigate right now. Who knows whether Muse reaches 10 million, 100 million or one billion users, but whether Muse wins or not, personal agents are becoming a new place where demand gets routed and money changes hands. So, needless to say, it's a really good time to be experimenting with Muse AI connectors. Nobody knew which iPhone apps would win in 2008, but the developers who started experimenting early learned what the rest of the market wouldn’t understand for years. This feels like another one of those moments.

I find it fascinating how many people think this is a bad time to start a company. Grok 4.7, GPT-6 Sol/Luna, Opus 5.5, Astra, Gemini 3.8 Live, Muse, Instinct, Jev, Agent APIs etc. That's the last 3 weeks (crazy progress on personal agents/voice AI). Because arbitrage means the same thing trades at 2 prices in 2 markets (and it's your wedge). And usually you have to hunt for those gaps, because they're rare and they close the moment anyone notices. What's different now is that they're opening faster than anyone can build into them! I think this has got to be the greatest time for arbitrage in history.

Email, phone numbers, and marketplaces are about to get destroyed When everyone has Muse, Instinct etc doing their errands, every inbox, phone line, marketplaces etc gets hit by millions of agents at once The channels built for humans are going to break/be reinvented.

10 Jev native products I’d build, ranked by how much fast, cheap decisions change the product: 1. Agent spend firewall Before every purchase, Jev returns approve/review/deny plus a confidence score based on price, vendor, user rules and purchase history. 2. Self-healing tool calls After an API error, Jev chooses retry, wait, change parameters, switch providers or escalate. So now you have agents that recover from failure in milliseconds instead of restarting the entire workflow. 3. Irreversible action detector Jev scores every step by reversibility before the agent sends an email, deletes a file, moves money or changes permissions. You get aggressive automation for safe actions and human approval for consequential ones. 4. Dynamic permission engine Instead of giving an agent permanent access, Jev decides which tool, data and spending limit it receives for each task. So now all of a sudden, you get temporary, task-level permissions for enterprise agents. 5. Agent branch pruning An agent generates 20 possible next steps. Jev scores them in parallel and kills weak branches before expensive reasoning begins. Deeper agent planning at a fraction of the cost! 6. Production incident controller Jev reads logs, deploy history, affected customers and service health, then chooses ignore, rollback, restart, page or investigate. Someone like pager duty should build this because it's automated incident response that reacts before an engineer opens Slack. 7. Live negotiation policy During a sales, procurement or collections conversation, Jev decides whether to discount, counter, hold firm, offer terms or escalate. Reminds me of Clulely. 8. Autonomous refund desk Jev evaluates order history, customer value, fraud signals, item cost and policy, then returns approve, reject or review. Finally, instant refunds for good customers and focused review for risky cases. Note: I'll be adding more Jev related ideas to and our agency builds the biggest agentic products 9. Realtime marketplace dispatch For every request, Jev chooses the provider using location, price, quality, availability, cancellation risk and customer preferences. Big problem is that marketplaces need to rematch supply continuously as conditions change. 10. Confidence based human queues Jev scores every agent decision and sends only uncertain, expensive or irreversible cases to a person. One person can now supervise thousands of autonomous workflows. LLMs generate possibilities. Jev chooses what happens next. The next generation of software will need both.

Jev is HERE and this is the CLEAREST explanation of what it is and what NEW businesses it unlocks. (and at the end I'll tell you how to get Jev even if you're on the waitlist) WHAT IT IS You know how you open your inbox and have to decide what's junk, what needs a reply, and what can wait? Jev does that part. It looks at each thing and says "this is junk, I'm 94% sure." It doesn't write anything back to you. It just sorts. 1,700 emails for 18 cents, instantly. That sounds kinda trivial but the important part WHAT IT UNLOCKS My explanation of Jev sounds small until you realize HOW MANY jobs are exactly this. Someone reading a stack of applications. Someone deciding which support ticket goes to which team. Someone looking at inbound and deciding who's worth calling back. A few ideas on what it unlocks: 1/ Instant quotes that are actually instant. Every quote form on the internet says "we'll email you by end of day." Build the version that answers in under a second, for roofers, movers, insurance, legal intake. 2/ Lead scoring as a product. Every agency and service business has a contact form full of junk. Score every submission and send the real ones straight to the owner's phone. 3/ Support triage for companies with no support team. The ticket gets classified and routed before anyone opens it. 4/ Clipping tools. Pass in a transcript, get the best moments scored in three seconds. Every clipping product just got a cheaper engine. 5/ Application piles. Grants, permits, insurance claims, job apps, loan docs. Someone reads that stack one item at a time today. 6/ Marketplace matching. Someone types what they need and gets matched to the right local business instantly instead of waiting for callbacks. 7/ Browser agents that actually move FAST. That makes bulk browser work practical: pulling quotes from five carriers, filing the same form for 200 clients, checking supplier inventory in real time etc. TLDR; find an expensive queue and put Jev at the front of it. HOW TO GET IT I didn't realize you can skip the waitlist because Jev is live on the Vercel AI Gateway right now, so you can start calling it today. In this episode, we share how. Episode now live on @startupideaspod (thanks to @ryanvogel for coming on and spilling the sauce today) Watch: Jev is a big deal because this is a whole new way to do AI Really cool Happy Jev day.

I think we'll see 5x the number of people become hardware and robotics founders over the next 18 months Why? Because you can rent every step, from design to manufacturing: DESIGN - Astra to drive Blender, FreeCAD, and KiCad the way a person would, so you get editable geometry instead of a dead render. Zoo dot dev's text to CAD API if you want it programmatic. - Or have Claude write build123d code, which is Python parametric CAD, and there's a Claude Code plugin that runs it and exports the STL for you. PROTOTYPE - Bambu A1 mini is $299, P1S around $399 on sale. Or skip owning one, JLC3DP prints and mails it for about $20. PCBWay does resin, SLS, and CNC if plastic won't cut it. ELECTRONICS - KiCad for the board, Astra can drive it. JLCPCB fabricates and assembles, often under $100 for a small run. ESP32 for wifi, Raspberry Pi if it needs a brain. ANYTHING THAT MOVES - Unitree sells a Go2 with a full SDK for about $2,500. - Hugging Face put out a $399 open-source biped. - LeRobot gives you the whole train in sim, deploy to real pipeline, and Physical Intelligence open-sourced π0 so you're fine-tuning instead of starting from zero. - Prototype the policy in MuJoCo or Isaac Lab first. MANUFACTURING - Alibaba RFQ for the first 100 units. Check 1688 to see what the factory actually charges domestically, then negotiate. Pietra or Sourcify if you want someone to handle it. FULFILLMENT AND SELLING - ShipBob or Amazon FBA. Shopify for the store, TikTok Shop for distribution, Kickstarter if you want the money before you build it. How to think about starting your own robotics or hardware company: 1. Pick a niche that's already buying weird gear. Cyclists, tabletop gamers, beekeepers, home baristas, dog people with mobility issues. These groups spend money on specific objects and complain in public about what doesn't exist. Or grab ideas off 2. Go read the complaints. Reddit, IG etc Search "I wish someone made," "does anyone make," and "modified my." That last one is the best signal, because someone already hacked the product together and you're just manufacturing what they built by hand. Also check Etsy!! If 3 sellers are doing a janky 3D printed version with 400 reviews each, the market is validated. 3. Make one. Describe it to Astra or Claude, get the CAD, print it in ugly gray PLA, use it, fix it. 4. Only go to Alibaba or similar once you've sold a few. Message 10 suppliers through RFQ, take the third cheapest, always pay the $50 for a sample before the real order. 5. Film everything from day 1. The first ugly print, the failed version, the box of 100 arriving. That's your entire marketing budget, and hardware is one of the few categories where people actually want to watch the thing get made. 6. Raise the price. Almost everyone here anchors on what the plastic cost. Your customer is comparing you to nothing, because the alternative is the product doesn't exist. Start at 5x COGS and go up. THIS GOAL OF THIS POST IS JUST HERE TO GET YOUR CREATIVE JUICES FLOWING. Of course, you can build robotics/hardware in a bunch of different ways. One thing I've learned is data couldn't be more important when you're building a hardware/robotics startups. These models learn from first person video of a human doing the task, and that footage doesn't exist for almost any job. So basically you pick one repetitive job people quit over, film someone doing it for 2 weeks, fine-tune π0 on that footage, use organic to sell the first few units and figure out scaling, 5 years ago you needed a factory, a supply chain, and a $1M just to find out if anyone wanted the thing. Now, anyone can become a hardware/robitics founder. And I suspect a lot of people will become one! Vibe manufacturers.

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: 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 before it ever reaches you. Instead of supervising the work, you're APPROVING finished work that already has evidence attached. REALLY interesting to see how work with agents is evolving to be….well, similar to working with people!

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 really important, you can ACTUALLY build one now. OpenAI's Agents API, Claude's managed agents, Vercel's eve, LangChain harness framework etc. They all make it way easier to build agent harnesses. Agent harnesses truly are the new GPT wrappers. This is just the beginning.

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.