jack gamrot

AskMaisie is live Less than a week ago it was an idea, now it's live and I'm taking on a small number of weddings: askmaisie.com

@mayukh_panja So what you’re saying is: AI makes intelligence abundant. The scarce thing becomes physical execution. Which sounds a lot like “buy robots.”

For those babbling about the permanent underclass, it is important to remember the stuff AI can NOT do today and definitely not in the NEAR future: 1. extract resources and energy from nature 2. build infrastructure and move raw materials and goods 3. build anything in the physical world (it might be able to 3D print stuff though) 4. build trust and forge relationships- a significant number of business and financial decisions are made based on this If we look at value stack of society, software and analytics (intelligence, if you will) are only one part of it. Business does not run only on optimal decisions. It runs on reputation, relationships, liability, repeated interaction, social proof, and credibility under uncertainty. AI can help prepare decisions, but many people will still want a human or institution to stand behind them. Civilization is not made of intelligence alone. It is made of energy, matter, land, logistics, institutions, trust, physical execution, maintenance, and coordination. AI can optimize many of these, but it cannot directly replace them. These are breathless times indeed. But the doomsayers need to calm the fuck down.

Here's how I feel about the situation... You either have to... 1) stop what you're doing and start using AI to bring all the ideas you've ever had to life via code ASAP (before the token/usage costs skyrocket as VC's stop funding them.. like they did in the Uber/Lyft days) or 2) own as much public equity as you can reasonably allocate tied to AI software and hardware (as AI eats human knowledge labor at an accelerating pace). The alternative is... I think... from what I can tell after being in the thick of AI as a heavy user now for 12+ months... permanent underclass I suppose a corollary to this would be to... be in the IRL experience business or the high-quality premium goods business.

7 days, 88 commits, 1 live product. The agents made the building fast. The bad decisions were all mine, they just showed up quicker. It's live at askmaisie.com/x. Now the actual hard part - finding couples who want it.

Day 7: One commit - finally killed the swipe gestures from day 4. Then shipped it.

I built AskMaisie in less than a week Fast. Messy. Real. The whole week, day by day 🧵

@claudeai  Me pretending my evening isn’t ruined by Fable 5 right now

Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use. Its capabilities exceed those of any model we’ve ever made generally available.

gotcha! we’re talking about distribution & marketing Depends on the product - if you’ve got an audience, use it. If you don’t, go find the people with the problem and put the idea in front of them. If the proposition is strong enough, some will sign up. Loads of ways to try paid & free

@jgamrot @alex_lrz_nmv I dont mean what do you build, landing page is easy enough. How do you get the users to the landing page and to sign up to the waitlist?

Founders, would you rather - launch with 0 users and a finished product - launch with 500 users waiting and an unfinished product

@kbanta11 @alex_lrz_nmv Probably a landing page, mockups, or a demo. I’ve not exactly got a strategy for this yet. In concept you’re not trying to prove you’ve built it. You’re trying to find out if anyone cares. Easier said than done - I know

@jgamrot @alex_lrz_nmv Whays your strategy for getting people onto the waitlist? To care enough without something to show them?

@alex_lrz_nmv Honestly no, but I think I should. look at what @jurree is doing with Gotcha! Such a brilliant idea, I’m on the waitlist

@jgamrot Yeh exactly I agree with that! Do you build waitlist usually for your products?

Why does every washing tablet smell like jasmine, lavender, or some wild flower? I don’t want to smell like a flower. I want my clothes to smell like a brand new t-shirt straight off the shelf in Abercrombie

It's not sexy to say, but most of AI transformation has nothing to do with AI. There are 10 steps in the sequence of making an internal process or external product AI-native. Only 1 step is AI, and ironically, the other 9 steps are the far harder part. Step 1: Identify the problem - find the manual process worth automating. turn your brain off autopilot & turn on your "suck meter". - funny enough, your company becomes more efficient just by mapping out your processes even if you don't introduce AI. Step 2: Understand the workflow - Map how people actually work today. grab an 8.5x11 piece of paper or @excalidraw and create a flow chart of the workflow from beginning to end. - Least sexy part, but generally where the people driving transformation (FDE, GTM engineer, etc) should spend the majority of their time. - Before you reimagine a process you have to become an expert in that process. Which means you either need to have the business context yourself or absorb it through osmosis (See what @DBredvick did at @vercel) Step 3: Collect the data - Gather sample inputs, documents, edge cases - Example: for my content machine ai workflow, I gathered past slack messages/notion transcripts to test automated ideation & I pulled past X/linkedin posts to build .md files of my content voice Step 4: Build the prototype [The AI Part] - Whether its engineer-led or SME-led the goal is to test your hypothesis that there's a better way of doing things for yourself as customer zero. Don't worry about code cleanliness, don't worry about scalability, just worry about proving there's a there there. Step 5: Test & iterate - Validate with real users and edge cases - Before you take the process from single player (only you using it) to multiplayer (many users), you want to beat it up with as many rounds of work & feedback + edge cases as possible. Turning every process into a self-improving loop before scaling is key. Step 6: Integrate with systems - Point-in-time data is good for testing the workflow, but live data is necessary before going into production. - Example: for my content machine, i'm hooked up to notion/gmail/slack for content ideation & i'm hooked up to X & Linkedin to post content once it's ready to go. Step 7: Roll out & train - Whether the new process lives on a live link, on GitHub or an internal library, next step is hand-holding your peers/users through the onboarding process of your new workflow/product. Step 8: Drive adoption - It's actually pretty simple (just not easy). Introduce a new workflow that saves someone a lot of time and integrates with their already existing behavior so they don't have to deal with re-education. - Embed the workflow in your culture where adoption is tracked, ideas & feedback are celebrated, and new/creative use cases become social currency in your business. Step 9: Empower contribution - Treat your new process like an opensource project. Allow users to become contributors. Whether they are literally pushing code or are simply empowered to add ideas/feedback to a kanban board that gets serviced by engineers, make everyone feel like a builder. Step 10: Measure & capture value - Everyone is ROI obsessed atm. If you're in the experimental phase of AI adoption in your company, fuck ROI. The goal is to empower people to throw a lot of shit at the wall & see what's worth focusing on. You don't need to be scientific during this process. Intuition is more than enough in gauging what's working vs. not working. - If you're in the scale-up phase of AI in your business, and you need to realize hard ROI, you need to reskill employees attached to this process, undershoot your approved hiring roadmap, or measurably increase ACV/conversion rate/sales cycle speed.

@alexanderrX_ I tried this but heavy sessions left me dead the rest of the day. Frying my nervous system at 6/7am. No amount of white monster would get me through the work day.

switched from working out after my 9-5 to before it. massively better. you start work awake, fuelled and ready, then after work there’s no pathetic internal debate about going to the gym. you get your evening back, and feel better than everyone else.

@marclou Love it. We had karaoke at our wedding too. The one thing we were determined about was not starting married life with wedding debt. Waking up the next day married, happy, and not owing anyone anything was a great feeling.

I got married in September 2020. I had $0 in the bank. My parents paid for the wedding, so we booked an affordable venue and invited only close friends and family. We played games, had a simple dinner, and ended the night with karaoke. The wedding cost less than $10,000. It was the best day of my life.