Bryce DeFigueiredo

@jambroli Kimi is having a generational run right now

love watching Kimi this season

The beauty of AI is that it unlocks the unexpected

@jspujji GEO

I’m in a WhatsApp gc with 23 CMOs of 8-fig biz. Last week this CMO texted that Claude recommends his product in 9 out of 10 prompts. Site traffic’s up. LLM traffic CVR is higher than ever. This guy is 25 years old and knows more about Claude / ChatGPT naming your brand on search than anyone else I know. I asked him to give a masterclass for my team. We’re 90 days in, with similar outcomes: +% of traffic with high intent to buy. 4x meetings from AI literally saying GrowthAssistant. I asked him to share everything you’d need to know about the first 3 months of starting a GEO program. He sent me this guide that breaks down his entire process: – High visibility channels + how to play on each one – Tool suites he trusts and what metrics he lives by – The easy wins to amplify any size brand in search Comment “GEO” and I’ll DM this playbook with you.

The tools you choose to build with are so important. @vercel AI Gateway / @aisdk - `caching: 'auto'` boom, providers that need explicit prompt caching, handled for you in one line - Spend limits? Handled - Break down costs by model, user, custom tag? Handled - Wanna run your evals against different models to see if a cheaper one can get the job done? Handled, just put the model string in. To go fast AND safely, a lot of times it comes down to the tools you choose. Tools tools tools.

this is a huge unlock instead of manually digging through data, use this mcp to separate the signal from the noise

I was skeptical of Anthropic’s idea that coding agents are the path to AGI, but with things like this, that argument makes a bit more sense.

Vercel cooked on this one. just-bash is great because rather than waiting for models to get better at agentic tasks you care about, you just transform your tasks into a shape LLMs are already really good at.

Burton's new site is live and has Anagram's Site Agent on every product page. I grew up riding Burton. My whole family did. Now our product helps their shoppers pick the right board, bindings, and gear. Proud of this one.

We spent months building an AI chat experience for e-commerce brands. A big takeaway is that one of the things people care most about is the analytics. Turns out, seeing the questions a hundred shoppers ask on your product page is more convincing than any A/B test. Analytics are great, but seeing what people ask organically on your site is like running customer interviews at scale.

@loganthorneloe Congrats, Logan!!

Hit 10k followers yesterday! More deep AI content to come.

@ansh_chokshi gtm

i'm a technical founder who had never sold anything to an enterprise, and then i had to run gtm from scratch. no playbook, no coach, just me. here's everything i learned taking mireye's gtm from 0 to 1, and the exact loop i'd run again. tldr: gtm is mostly pattern recognition and positioning. and both of those you can engineer. the exact loop i run every day: thesis → prospecting → messaging → outreach → followups → retro → repeat and for the entire first month i had one goal. not revenue, not logos. maximize calls booked. it's a simple game theory move: collapse the whole game to one win condition, and every decision answers itself. does this book a call, yes or no. everything else is noise. week 0. thesis. > pick one. an insight, a customer conversation, a problem you hit yourself. don't overthink it, it will change anyway. > mine was "data center developers want a cited site report in minutes and cheap, everything on the market today is slow and expensive." broad, and a little wrong. > doesn't matter. a thesis isn't meant to be right, it's meant to be tested. write your best guess and go. week 1. find the first 50 by hand. > no lists, no scraping. i read 200 company sites one by one to find my first 50. > my first list had xai and coreweave on it. reading their pages back to back, it clicked: those are the exact companies that will never buy from me. > then the email. write as a founder, five sentences, no fluff. the bar is embarrassingly low. it just cannot read like ai wrote it. no links. don't ask for a call. simple cta. > my first version opened with "80+ cited fields across 31 datasets." silence. the version that got replies was plain: "we'll analyze your site in minutes." same product. i just said it like a human. week 2. run the loop by hand. automate nothing. > i'm an engineer, so every instinct screamed automate this on day one. ignoring that was the best decision i made. > because week 2 isn't about sending emails. it's about collecting the exact words people use for their problem. that vocabulary becomes your positioning. > so i went from 10 emails a day to 15, all by hand, and after every call i wrote the problem down in their language. > then two calls in one week cracked it open. one founder came from real estate, one came from oil and gas. completely different worlds, both walking into data centers, both missing the same thing: knowing which land actually clears. > that overlap became my entire icp. that's the pattern recognition, and it only shows up when you do it by hand. > helped us change the thesis and product positioning: agents will comb through every parcel in the country to find you off market sites that meet your exact requirements. week 3. proof first, then automate. > the signal i waited for: different people describing the same problem in the same words, all around the same company size, and 10% response rate. > my icp went from a vague guess to three sharp ones: 1. land developers who just crossed into data centers chasing the ai boom. 2. developers whose site just got rejected, carrying a fresh loss i could fix. 3. powered-land flippers hunting land that already has power. week 4. build the machine. now its a numbers game. > i turned every step of the loop into its own claude skill. prospecting, messaging, crm, followups. now claude and i run the same loop every day and learn together. > the stack is simple: @ExaAILabs agent to find prospects @EmailHunter api to find and verify emails @meetgranola mcp to read my call notes @Superhuman mcp to send > a csv for a crm. yc agent when i want a second brain on a strategy call. > company brain with all the learnings md files. > a diligence doc before every demo, a learnings doc after every call. > before one demo i ran our own screen on the prospect's own site and found a air-permit issue they didn't know about. i walked in knowing their land better than they did. that's how you win a call. but the highest-leverage thing i did? followups. > someone opens my email, and i reply with the close: here's what we do, the value, demo pdf and call link. > i've booked more calls on that second email than on any first one. once they've read you, you're in. you just have to show proof. the lesson under all of it: do things that don't scale, on purpose, to learn anly what you've proven works. i still read every draft before it sends. if it smells like ai, i rewrite it by hand. pattern recognition from the retro. positioning from their own words. both engineered by running the loop. if i can do it, so can you. comment "gtm" and i'll send you my skills.

@thedennis HOOKS

We turned every hook pattern that keeps winning for us into one resource. 100 frameworks. Fill in the blanks. Sorted by trigger, curiosity, pain, proof, authority, and by the problem you're actually solving. Reply "HOOKS" and I'll send it.

This is the truest depiction of building a startup I’ve seen

@devahaz Outside of Bay Area tech, taste means one thing, but inside, it's basically a synonym for judgement.

I don’t think anyone takes “SF/SV taste discourse” seriously. Bay Area taste icons last few decades basically Steve Jobs and Jony Ive. But fashion/design taste points of view? Maybe a few like Marissa Mayer and Jack Dorsey but not like they’re influential tastemakers at all.

@blader Whelp...

something happened an hour ago that made fable 5's chances of coming back next week go from 15% to 60%

@jehovahscript Sheesh, spot on

@max4c_ Feeds are essentially a dopamine slot machine asking for attention every waking moment of the day. Love this idea.

I used a flip phone for a year, so people assume I'm anti-screen. I'm not. I'm anti-feed. The problem isn't computers, it's the architectural choices tech giants made to extract as much from us as they can. The harms are designed. They're choices. Smartphone Free Childhood makes that case better than anyone, and I agree with them: delay the phone. But a phone and a computer aren't the same machine. One is built to consume. The other can be built to make and learn. So delay the feed, and give kids something that points them back at the world instead of mining their attention. That's the computer I'm building at @DasoComputer

@lulumeservey The problem with Avi’s position here is that it assumes a false dichotomy between making money and doing something you believe in. If you’re pro-nuclear, it *must* be about the money. (Because he can’t imagine anyone being a true believer).

This is such a genius psyop by the company making money selling tokens