GREG ISENBERG (@gregisenberg) X analytics
@gregisenberg
I drop startup ideas daily. Host @startupideaspod. CEO: @latecheckoutplz we build companies like @ideabrowser, @meetLCA, @boringmarketer etc
@gregisenberg has 750.9K followers, a median of 115.4K views per post and a 1.05% engagement rate.
Based on 30 recent original posts (high confidence). Updated October 24, 2026.
At a glance
Key stats
- Followers
- 750.9K750,887 followers on October 24, 2026+9.6K in 7 days
- Median views per post
- 115.4K
- Average views per post
- 304.9K
- Engagement rate (by views)
- 1.05%
- Original posts per week
- 8.0
- Average engagements per post
- 3,214
Engagement grade
Developing
This is near the lower benchmark range for accounts with 100K-1M followers.
Profile score
85/100
- Profile completeness100
- Audience shape100
- Engagement25
- Consistency100
- Positioning clarity100
Monetization
Estimated X creator earnings
$57–$137 in the last 30 days
From 11.5M views on @gregisenberg's original posts in the last 30 days.
Rewards eligibility: likely
Rough estimate. X publishes no payout rate, so this assumes about $5–12 per 1M original-post impressions from reported creator payouts. Only Premium viewers’ impressions count, so real payouts can be much lower.
Free report
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Growth
Follower growth
+9.6K followers in the last 7 days. Tracked by Xholic since July 28, 2026.
| Date | Followers | Change |
|---|---|---|
| Oct 26, 2026 | 750,887 | 0 |
| Oct 24, 2026 | 750,887 | +2,625 |
| Oct 22, 2026 | 748,262 | +190 |
| Oct 21, 2026 | 748,072 | +338 |
| Oct 20, 2026 | 747,734 | +6,446 |
| Oct 18, 2026 | 741,288 | +1,900 |
| Oct 16, 2026 | 739,388 | +9,706 |
Timing
Best times to post
When @gregisenberg's recent posts performed best (UTC).
- #1 slot
7:12 PM
Monday · UTC
- #2 slot
6:23 PM
Tuesday · UTC
- #3 slot
7:34 PM
Wednesday · UTC
What worked
Top recent posts
- 01
@gregisenberg ·
I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies. My observations: 1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively. 2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now. 3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention. 4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is. 5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now. 6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text. They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it. 7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy. 8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies. Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here. 9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens. 10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity! 11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it. 12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable. 13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think. 14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data. 15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open. 16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down. 17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building? 18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone. 19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good. 20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped. 21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense. Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era. Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways. Happy to be home and locked in. Until next time!
- 934Replies
- 2KReposts
- 21.2KLikes
- 2.5MViews
7.9x average engagementHas an imageLong post (over 200 characters)Posted Wed 16:00 UTC - 02
@gregisenberg ·
Meta Muse will probably create 1000+ millionaires This is the most slept on arbitrage I’ve seen in years and it’s not even close. Here’s how i’d build a 1 person business powered by AI/Muse with with $0 and 0 social following
Watch video- 475Replies
- 750Reposts
- 10.8KLikes
- 1.4MViews
6.3x average engagementHas a videoLong post (over 200 characters)Posted Mon 18:00 UTC - 03
@gregisenberg ·
I literally can't think of a better risk/reward bet right now than building a ChatGPT plugin and getting in front of their 1.2 billion weekly users. As of yesterday, ChatGPT recommends plugins in the middle of conversations. Millions of questions get asked every day with no plugin to recommend. Each one is an empty slot. Facebook apps in 2007. iPhone apps in 2008. TikTok in 2019. Every big platform has a few months where distribution is free, and most people miss it. I saw this firsthand when I lived in SF building venture backed companies. They are sacred times! If I were starting this week: 1. Find a tool or workflow people already Google for or do by hand every week (PDF to Excel, invoice generator, weekly client reports) 2. Build it as a ChatGPT plugin 3. Write the description using the exact phrases people type into ChatGPT 4. Ship 5 of them and see which ones get picked up 5. Double down on the one with the most traction In 12 months these slots will be crowded but right now they're pretty empty. Most people will realize ChatGPT plugins were the biggest free distribution channel of 2026 sometime in 2027.
- 309Replies
- 395Reposts
- 8.2KLikes
- 1.2MViews
3.7x average engagementText onlyLong post (over 200 characters)Posted Thu 00:00 UTCQuote post - 04
@gregisenberg ·
The MOST obvious (but REALLY good) STARTUP ideas right now: 1. Zestimate for company data (what your data is worth to an AI lab) 2. Google Analytics for agents (see which agents visit your site and what they want) 3. Y Combinator for 1 person companies (back solo founders running a team of agents) 4. Okta for agents (who each agent is and what it's allowed to touch) 5. Marie Kondo for your company's data (clean it up so agents can use it) 6. FICO for agents (a trust score before an agent can spend money) 7. Geico for agents (insurance for when an agent makes an expensive mistake) 8. Datadog for agents (see every step your agents took) 9. Twilio for agents (phone numbers and texting for agents) 10. Upwork for agents (hire an agent for a job instead of a freelancer) 11. ESPN for AI (every model launch covered like a big game). 12. Shutterstock for robot training videos (get paid to film yourself doing chores) 13. Credit Karma for what AI knows about you (see it, fix it, delete it) 14. Norton for AI scams (protect your parents from fake voices and emails) 15. PayPal Buyer Protection for agent purchases (fixes it when your agent buys the wrong thing) 16. Geek Squad for AI (set up personal agents for families and small businesses) 17. Dell for private AI (AI in a box for firms that won't use the cloud) 18. Carfax for used GPUs (a health report before you buy secondhand) 19. Airbnb for idle GPUs (rent out computing power you're not using) 20. Rotten Tomatoes for AI models (real reviews instead of benchmarks) 21. G2 for skills (find the best skills for your agent) 22. Dropbox for your AI memory (take what your agent knows about you to any agent) 23. Canva for physical products (design it with AI and get it made) 24. ADT for your personal agent (alerts when your agent does something it shouldn't) 25. Hertz for robots (rent one for a move, a deep clean or an event) 26. Harvard Business School for internet businesses (a real education in building online) 27. Workday for agents (onboard, manage and offboard your digital workers) 28. Getty Images for your face and voice (license your likeness to AI safely) 29. Meta Muse for older adults (and other high LTV niche) 30. Google Ads for agents (pay to be what the agent recommends) 31. Loom for agents (a walkthrough of everything your agent did) 32. Plaid for agents (approved access to banks, airlines and stores) 33. Jiffy Lube for vibe coded apps (quick fixes when your AI built app breaks) 34. Ancestry for datasets (where your training data came from) 35. The organic label for human-made content (proof a person made it) 36. Strava for builders (track what you ship every week) 37. Honey that haggles for you (your agent negotiates the price) 38. SEM Rush for personal agent platforms (like Muse etc) 39. Frequent flyer miles for agents (loyalty programs built for agents)
- 480Replies
- 328Reposts
- 4.8KLikes
- 467.2KViews
2.4x average engagementText onlyLong post (over 200 characters)Posted Fri 19:00 UTC - 05
@gregisenberg ·
HOW TO BECOME A FORWARD DEPLOYED ENGINEER (53 MIN MASTERCLASS) Some forward deployed engineers are getting PAID $1M+/year (kinda crazy, I know) And I REALIZED almost nobody talks about HOW they do it in any detail. It's basically nowhere online. So I asked someone who does it ALL DAY LONG for Fortune 500 companies to walk me through it, step by step. and he shares EXACTLY how he does it https://t.co/uzgFccsgza Here's what I learned: 1. They start by listening, not building. They interview the people doing the work and let agents quietly read the company's data for a few weeks. The real process is almost always 3x longer than the one on paper. 2. They sort every step into four buckets: delete it, automate it with a simple rule, give it to an AI agent, or keep a human on it. A surprising amount ends up in the first bucket. 3. They build inside the tools the company already uses. Nobody has to learn a new app. When a human needs to sign off, it's just a Slack message. 4. They use the cheapest model that gets the job done. Most of this work doesn't need the most expensive AI. 5. They measure everything before and after, then come back 6 months later and prove it worked. This + concrete client examples + way more on today's episode of @startupideaspod (thanks to @vasuman) A full course pretty much on the topic aivalable to you 100% for free. This episode is for ANYONE who wants to be a FDE or who wants to make their company AI-native by deploying agents. Watch
Watch video- 106Replies
- 244Reposts
- 2.5KLikes
- 213.4KViews
1.2x average engagementHas a videoLong post (over 200 characters)Posted Thu 22:00 UTC - 06
@gregisenberg ·
There are only 13 categories of businesses left to build in the agentic era, everything else is in decline (25 minute breakdown) https://t.co/f6YvOjEwuV
Watch video- 95Replies
- 195Reposts
- 1.8KLikes
- 143.5KViews
0.9x average engagementHas a videoMedium length (100-200 characters)Posted Tue 17:00 UTCQuote post
Latest
Recent posts by GREG ISENBERG
The latest 30 original posts from @gregisenberg, newest first, as of October 24, 2026. Replies and reposts aren't included.
@gregisenberg ·
The MOST obvious (but REALLY good) STARTUP ideas right now: 1. Zestimate for company data (what your data is worth to an AI lab) 2. Google Analytics for agents (see which agents visit your site and what they want) 3. Y Combinator for 1 person companies (back solo founders running a team of agents) 4. Okta for agents (who each agent is and what it's allowed to touch) 5. Marie Kondo for your company's data (clean it up so agents can use it) 6. FICO for agents (a trust score before an agent can spend money) 7. Geico for agents (insurance for when an agent makes an expensive mistake) 8. Datadog for agents (see every step your agents took) 9. Twilio for agents (phone numbers and texting for agents) 10. Upwork for agents (hire an agent for a job instead of a freelancer) 11. ESPN for AI (every model launch covered like a big game). 12. Shutterstock for robot training videos (get paid to film yourself doing chores) 13. Credit Karma for what AI knows about you (see it, fix it,…
- 480Replies
- 328Reposts
- 4.8KLikes
- 467.2KViews
@gregisenberg ·
I keep thinking about the PHP/railway hack. Once you get hacked or your data gets leaked, it’s such a bad feeling. You can’t take it back. It feels like a stranger was walking around your house while you were asleep. Some of the most valuable companies on earth will be security companies.
- 157Replies
- 11Reposts
- 362Likes
- 91.2KViews
@gregisenberg ·
Yes, 99.9% of Duo apps look like trash now but what did you expect? Most companies won’t redesign for a new device until it has millions of users, so the first year is always a little messy. So, startup idea for you coming from someone who has sold tens of millions of dollars of agency services: a Duo app agency. Think about who’s buying this thing! Someone paying $2000+ for a phone the week it comes out is about as valuable a customer as you’ll find on the App Store. They pay for apps, they pay for subscriptions, and they leave reviews. Most companies want those people badly, and most don’t have a spare team to redesign their app for a brand new screen. Hence, why the Duo apps look mostly trash now. How to start a duo app agency: Pick the categories where the bigger screen matters, like recipes, reading, trading, design and music. Record a short video of their app looking cramped on the Duo next to an AI mockup of what it could look like. Charge $40k to $75k to ship the…
- 134Replies
- 15Reposts
- 433Likes
- 72.6KViews
@gregisenberg ·
I think we’ll see a lot more of this. The attackers were going after the AI keys stored on Railway, because an API key is basically a credit card for compute now. Every company running agents is sitting on a pile of these keys! here’s the 10 minute fix. rotate every key tonight, set a hard monthly spend limit in each AI dashboard, give every agent its own key, and turn on usage alerts so you know the second something spikes. someone should build the tool that finds every AI key a company has, rotates them every week and pings you when spend looks weird. charge $99 a month. every startup running agents needs it yesterday.
- 207Replies
- 52Reposts
- 761Likes
- 109.4KViews
@gregisenberg ·
I think AI agents are going to go through 9 stages before every business accepts them. Right now we’re at stage 1, where big companies like Amazon, Delta etc are blocking them. Here are the next 8 stages and the startup ideas I’d build.
Watch video- 111Replies
- 25Reposts
- 356Likes
- 47.7KViews
@gregisenberg ·
Does anyone else find it lame when founders pick fights with each other publicly? Do it in the DMs or not at all (ideally)
Watch video- 167Replies
- 6Reposts
- 317Likes
- 51.7KViews
@gregisenberg ·
Meta Muse will probably create 1000+ millionaires This is the most slept on arbitrage I’ve seen in years and it’s not even close. Here’s how i’d build a 1 person business powered by AI/Muse with with $0 and 0 social following
Watch video- 475Replies
- 750Reposts
- 10.8KLikes
- 1.4MViews
@gregisenberg ·
Delta, Chase and Amazon are blocking AI agents. The war on agents has begun, and here’s how it probably plays out: Stage 1: Companies block agents because agents skip the ads and upsells. Stage 2: Agents learn to act like humans, and it becomes an arms race. Stage 3: The market splits. Companies that make money on sales let agents in, companies that make money on data charge for access, and the giants build their own agents. Stage 4: A trusted middle layer for agent identity and payments becomes the standard way in. Stage 5: Companies that welcome agents start winning customers from the ones that block them. Stage 6: The agent blockers come back and let agents in on their own terms. Stage 7: Everyone starts competing for agents with better prices, faster checkout and SEO built for agents. Stage 8: The ads come back, and companies pay to be your agent’s first recommendation. Stage 9: The agent war ends, and selling to agents becomes as normal as having a website.
- 514Replies
- 258Reposts
- 2.7KLikes
- 258.1KViews
@gregisenberg ·
I've never seen an exceptional product that was designed by committee. Too many cooks in the kitchen make products that are complicated and diluted. Every compromise feels small in the meeting, and together they water down the whole thing!
- 161Replies
- 47Reposts
- 610Likes
- 63.4KViews
Show all 30Show fewer
@gregisenberg ·
Postiz hitting $275k MRR so FAST is a great example of what I'm seeing: tools that agents use for things like posting, email, payments, phone numbers and browsing are going vertical. A few other businesses I keep seeing go vertical: - Data brokering. Selling rare/useful AND expert knowledge to labs and to companies training their own agents. - Hosting for agents. Renting always on computers so people can run their agents 24/7. A lot of people want an agent working for them and have no idea how to set one up. - Compute reselling. Buying GPU capacity in bulk and renting it out to smaller teams who need it for a few hours. - Vertical harnesses. Agents built for one industry and one workflow, like insurance claims or construction bids. - Skills. People are selling packaged skills that make an agent good at a specific job. - Done for you agent setup. Local businesses are paying someone to set up agents for them, the same way they used to pay someone to build their website. When you zoom…
- 160Replies
- 63Reposts
- 1.1KLikes
- 112.9KViews
@gregisenberg ·
You have the same 24 hours a day that Elon has You have the same 24 hours a day that Zuck has You have the same 24 hours a day that Jensen has They use the same AI tools you do, same apps, same internet. It's the greatest time ever to be building and it's not even close
- 245Replies
- 194Reposts
- 2.8KLikes
- 104.2KViews
@gregisenberg ·
I’ve been playing with Gemini 4 Argon for 7 days — Google gave me early access and sponsored today’s episode. 10 Insights using Gemini 4 Argon (for people who want to make cool things with AI): 1. It's perhaps the best AI copywriter. Surprisingly. Using it as my default writer as of now. 2. I recreated a 3D version of our website pretty quickly. There's cars driving around, sounds, even a little basketball game you can play. The original took our team 40,000 hours to build. 3. It needs references to make great creative. My first attempt looked like Zuck's metaverse avatar lol. Once I gave it a Mondrian reference, it got beautiful. So you really gotta get your references in there. I like using Sublime or Cosmos for some of my inspo. 4. The best way to get it writing like you is to ask it to study everything you've written and turn it into a skill. It built me a voice guide, my vocabulary and templates in one go. 5. It did really well on my SaaS engineering on the first few…
Watch video- 69Replies
- 30Reposts
- 442Likes
- 49KViews
@gregisenberg ·
More SF observations: 1. Seeing the word "inference" on billboards in SF still blows my mind. 99.9% of america has no idea what inference is and I wonder how many know what an agent is. Will Muse, Instinct, Dots etc will change that over the next 12 months? 2. You know who doesn't get enough credit? Manus. In March 2025 they shipped the blueprint for AI agents: every task gets its own computer in the cloud, you can watch it work, it writes a todo list and checks it off, and you walk away while it finishes. So much of what we use today runs on those ideas! 3. Your product now has to sell itself twice. First the agent has to pick it, then the human has to trust that pick enough to say yes. 4. I was talking to a guy who told me we should just destroy all the data centers. I think that sentiment is more common than people in SF realize. You can already see some of the big AI companies adjusting positioning their AI as something that helps people and gives them more time/cures for…
- 215Replies
- 178Reposts
- 2.1KLikes
- 162.6KViews
@gregisenberg ·
I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies. My observations: 1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively. 2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now. 3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention. 4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system,…
- 934Replies
- 2KReposts
- 21.2KLikes
- 2.5MViews
@gregisenberg ·
people saying apple homeview is “just an ipad on a speaker” and it’s literally the best lesson in business you’ll see this year: you can take one product and sell it to a totally different customer. - homeview: an ipad on a speaker, for grandparents and the kitchen counter - iphone: the computer for everyone - ipad: an iphone with a bigger screen, for kids, artists and couch scrollers - ipad mini: a smaller ipad, for readers and pilots macbook: an ipad with a keyboard, for people who work - apple watch: an iphone for your wrist, for runners and people who want fewer distractions -airpods: the iphone’s speaker, moved into your ears, for commuters - homepod: the iphone’s speaker for your living room - apple tv: the iphone’s apps on your tv, for families - vision pro: the iphone’s screen strapped to your face, for early adopters apple has been doing this for 20 years! same chips, same apps, same ecosystem. a different customer every time. unbundled or bundled. it works and has…
- 179Replies
- 28Reposts
- 533Likes
- 118KViews
@gregisenberg ·
we’ll tell our kids that the first AI we used was basically a giant scrape of the internet frozen in 2021, couldn’t go online to check anything, forgot who we were every time we closed the tab, couldn’t see a photo or hear our voice, couldn’t read more than a few pages at once, couldn’t do a single thing for us besides type back, and was “at capacity” half the time, and they’ll think we were living in the stone age.
- 145Replies
- 49Reposts
- 861Likes
- 57.6KViews
@gregisenberg ·
i don’t think we’ve fully processed how big this AI wave shift we're living in really is. every app, job and business that was built around humans doing the clicking is about to get rethought. for 40 years computers were like cars where we had to do all the driving, and now they’re becoming chauffeurs where we just say where we want to go.
- 259Replies
- 84Reposts
- 1.5KLikes
- 81.3KViews
@gregisenberg ·
There are only 13 categories of businesses left to build in the agentic era, everything else is in decline (25 minute breakdown) https://t.co/f6YvOjEwuV
Watch video- 95Replies
- 195Reposts
- 1.8KLikes
- 143.5KViews
@gregisenberg ·
The limit on software used to be engineering and now it's mostly imagination. I'd spend a lot more time on the version of my idea that makes people say "wait, what is that?" Most software looks the same, so anything that looks different gets noticed, shared and remembered.
- 176Replies
- 295Reposts
- 4.4KLikes
- 327.1KViews
@gregisenberg ·
THE VIBE MANUFACTURING PLAYBOOK 1. Measure everything. Digital calipers for small parts, a phone LiDAR app like Polycam to scan a space or an object. Bad measurements are the #1 reason first builds fail 2. Have a frontier model write the design as code. Describe the part to a model like Claude Opus 5.5 or Astra, and have it write the design in a codebased CAD tool like OpenSCAD or CadQuery. Zoo's Text to CAD does it in one step! 3. Use real CAD files. The text to 3D models on Hugging Face make shapes that look right, but factories need precise files: STEP for machined parts, DXF for lasercut metal, STL for 3D printing 4. Make sure it can be made. Ask the AI to check the design against how factories actually work: how tight metal can bend, how small a hole can be, how much wiggle room parts need etc... 5. Prototype in plastic first. A $300 to $600 home 3D printer like a Bambu Lab lets you test the fit overnight before paying for metal (really fun to play with too!) 6. Pay an…
- 115Replies
- 177Reposts
- 2KLikes
- 155.7KViews
@gregisenberg ·
HOW TO BECOME A FORWARD DEPLOYED ENGINEER (53 MIN MASTERCLASS) Some forward deployed engineers are getting PAID $1M+/year (kinda crazy, I know) And I REALIZED almost nobody talks about HOW they do it in any detail. It's basically nowhere online. So I asked someone who does it ALL DAY LONG for Fortune 500 companies to walk me through it, step by step. and he shares EXACTLY how he does it https://t.co/uzgFccsgza Here's what I learned: 1. They start by listening, not building. They interview the people doing the work and let agents quietly read the company's data for a few weeks. The real process is almost always 3x longer than the one on paper. 2. They sort every step into four buckets: delete it, automate it with a simple rule, give it to an AI agent, or keep a human on it. A surprising amount ends up in the first bucket. 3. They build inside the tools the company already uses. Nobody has to learn a new app. When a human needs to sign off, it's just a Slack message. 4. They…
Watch video- 106Replies
- 244Reposts
- 2.5KLikes
- 213.4KViews
@gregisenberg ·
I'm headed to San Francisco next week. First trip away since my son was born two months ago! My life right now is 3am feedings, a toddler running around, and building in the gaps. Nap time is my new deep work block. So when I say I'm excited to sit at a dinner table and have a full conversation with adults about AI agents and startup ideas without anyone throwing food at me, I mean it. I'll be in town for a few days. If you're building something interesting, I'd love to buy you dinner and hear about it. Who wants to hang out in SF?
- 171Replies
- 6Reposts
- 503Likes
- 60.7KViews
@gregisenberg ·
I literally can't think of a better risk/reward bet right now than building a ChatGPT plugin and getting in front of their 1.2 billion weekly users. As of yesterday, ChatGPT recommends plugins in the middle of conversations. Millions of questions get asked every day with no plugin to recommend. Each one is an empty slot. Facebook apps in 2007. iPhone apps in 2008. TikTok in 2019. Every big platform has a few months where distribution is free, and most people miss it. I saw this firsthand when I lived in SF building venture backed companies. They are sacred times! If I were starting this week: 1. Find a tool or workflow people already Google for or do by hand every week (PDF to Excel, invoice generator, weekly client reports) 2. Build it as a ChatGPT plugin 3. Write the description using the exact phrases people type into ChatGPT 4. Ship 5 of them and see which ones get picked up 5. Double down on the one with the most traction In 12 months these slots will be crowded but right…
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@gregisenberg ·
My first OBSERVATIONS from Sundar's Gemini 4 Argon announcement: 1. Quantum. Google's quantum researchers gave Argon a key piece of quantum software to shrink, and in minutes it found a version that needs 40% fewer qubits and operations than the best published human solution. Quantum computers are useful ONLY once programs fit on the hardware, so this pulls that date closer from the software side, and it also shortens the time banks and governments have to switch to encryption quantum can't break. 2. Data center memory. A team of Argon agents read Google's server data, found waste, and freed over 300 TiB of memory on their own, with up to 1 PiB expected. If agents can do this everywhere, companies will point them at their cloud bills before buying more servers, and some of the huge data center buildout may turn out to need less hardware than planned. 3. Rewriting old code. Argon agents are converting Google's old C and C++ code into Rust, a safer language, including an 800K-…
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@gregisenberg ·
There were 20+ announcements at OpenAI DevDay today, but only 4 REALLY stood out to me. Here’s my take on Dots, agents, and the potential $100B opportunity for founders after watching Sam Altman and team for 60 minutes. https://t.co/IPPvxZkoLk
Watch video- 89Replies
- 59Reposts
- 883Likes
- 75.9KViews
@gregisenberg ·
Muse vs Dots vs Grokbot Zuck vs Altman vs Musk. The battle of personal agents for the masses. Who do you think wins?
- 876Replies
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@gregisenberg ·
It's kind of wild how many new primitives AI has given us in 3 years: - Local models (2023: Llama, Ollama, LM Studio) - Voice cloning (2023: ElevenLabs) - Text to CAD (2023: Zoo) - Text to video (2024: Sora, Veo, Runway) - Real-time voice (2024: Gemini Live, ChatGPT Voice) - Memory (2024: ChatGPT) - Reasoning models (2024: OpenAI o1, DeepSeek R1) - Vibe coding (2024: Bolt, Lovable, v0) - Computer use (2024: Claude, OpenAI Operator) - Connectors (2024: MCP) - Deep research (2024: Gemini, Perplexity, OpenAI Deep Research) - Agents (2025: Claude Code, Codex, Manus) - Image editing (2025: GPT-4o images, Nano Banana) - Agent payments (2025: x402, AP2) - Skills (2025: Claude Skills) - Personal agents (2026: Grokbot, Muse, Instinct)... we are here now. Each one of these is a starting point for hundreds of companies. The most interesting ones I'm seeing combine 2 or 3 of them with a specific niche!
- 125Replies
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- 37%
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Creator style: High-reach broadcaster
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