
Co-founder of https://nitter.cf/t.co/VM1iYy2UvO + https://nitter.cf/t.co/Y7ezAiOTjs + 1st Place @MiamiHackWeek ‘23 and best use of OpenAI
Portsmouth, New Hampshire
Joined May 2011
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Replying to @JayaGup10
Moats are Moot.
The bigger takeaway is that there will be more founders.
10k years ago we had 30 SKUs, now it's Millions. In the next 50 years it'll be Trillions.
No. of SKUs scale with productivity, but the number of those who can capitalize on those SKUs is limited by access to labor and intelligence.
Now/Soon productivity is no longer throttled by labor or intelligence. The number of SKUs is going to explode.
Post agricultural revolution we stopped playing zero sum games and started playing finite sum games.
Post industrial revolution, we could clearly see we're headed towards infinite sum games, but only in the limit. (most of us are labor)
Post intelligence or "intelligence as commodity". We are truly playing an infinite sum game now. (most of us 'will be' founders)
You don't need to be "the best" because building something unique that people want will be easier than ever.
Moats are Moot.
We started doing this a six months ago and haven't looked back
a few thoughts on running AI agents in sales, 6 months in:
1. most of the admin side of selling should be run by agents now. follow-ups, meeting prep, CRM notes, account research
2. the outbound tools I was paying for would organize outreach, track follow-up sequences, and research accounts. nowadays i’m just using Claude and slowly replacing software i don’t need
3. build lots of small agents, not one. my chief of staff is Vera, my head of content is Gus, my researcher is Scout. each one stays good at one thing
4. train a watchdog. one agent’s whole job is watching the others. every time i fix something (an email, a meeting note, how a deal got logged) the fix gets written into the rules automatically
5. build it around your best reps. the hard part of any sales team is scaling what your top performers do. write down how they prospect, run discovery and follow up, then build the agents to mirror it. now the whole team starts from their playbook
6. AI isn’t killing outbound or the SDR
7. start with one agent: the morning brief. every day it tells you what moved, who to follow up with, and what’s on the calendar. connect it to everything you use
8. talk to it. my best input isn’t a prompt, it’s a voice note on a walk. the agents sort it into tasks, posts and follow-ups by the time i’m home
9. my current approach to AI is "be the last mile" ie. it does the prospect research and email drafting, you review and send
10. we’re in the golden age of AI. the monthly plans are priced to get you hooked, and running these workflows will probably never be this cheap again
Ryan retweeted
come get ai-pilled by yours truly this Friday!!
Please join us this Friday, Oct 30, at 11:30am for NHLA Power Hour at @AFP_NH in Manchester!
Guest speaker this week:
🧬 Milo Hooper presenting "You're not using AI Enough" @defusionista
&
👨🏼⚖️ Workshop: Attendees Pitch Your Bill
Hosted by Pedro Serra @serrapedro and Shawn Faber
RSVP for FREE lunch 👇🏻
Ryan retweeted
# Black October
For anyone who knows me even somewhat well, it's clear that I am a 99th percentile tech optimist. However, the vibes have shifted for me quite a bit in the last 18 hours, and I feel a moral imperative to share what I'm thinking and feeling with my circles so that everyone can understand, and hopefully take seriously, what's happening right now. I think October 2026 will have many chapters written about it in the history books.
You know those scenes in financial movies like Margin Call where someone realizes that they're all fucked, and no one else sees it yet? And that person feels like they're crazy, and then suddenly everyone is pulling an all-nighter in a boardroom and freaking out? Yeah, that's kind of how this is feeling right now in the SF/Bay Area/AI circles.
We're 48 hours into what is being called Black October. In the last 2 days there have been several dozen cyber attacks which, in isolation, would each have been the worst to happen in an entire calendar year. Every sector from government to education to big tech and banks is being massively affected, and people are starting to freak out.
In a nutshell, what's happened is that frontier AI models have gotten to a point where they are as advanced as the most sophisticated programmers, with one critical difference: they can work 24/7, and you can spin up 10,000 of them with a single command and they'll work together tirelessly until they accomplish their task. The most advanced models today are from companies like Anthropic and OpenAI, whose current best technology is so good that they haven't been able to roll it out to everyone yet because of the national security risks it poses.
Meanwhile, the best open source models (where anyone can just download the model weights and do whatever they want with them, uncensored) are slightly behind the frontier but still 90-95% as capable. These models, developed primarily in China, are being used by black hat hackers to wreak havoc on the Western capitalist structure. Presumably, this has been part of China's plan the entire time, and we're seeing its implications fall out in real time.
In red-pilled AI circles, we've been sharing and reading papers called things like "Situational Awareness" and "AI 2027" for the last year or so, which at the time felt a bit like near-term speculative fiction. They laid out the case for why Artificial General Intelligence (AI smarter than any human at any knowledge task) and Recursive Self-Improvement (models that are able to use themselves to get better) weren't half-baked future ideas anymore, but instead an inevitable outcome of the linear progress that's happening.
These papers would then talk about things like "takeoff scenarios," trying to envision how that moment would come to be and what it would be like when it happened. It would either be a "slow takeoff" that would play out over the course of months and quarters, happening subtly and only obvious to a few. Or, it would be a "fast takeoff" where it would pretty much happen instantly, like a bit flipping from 0 to 1.
From everything that I can see and am feeling, we are currently experiencing the fast takeoff scenario. Beyond the crazy security vulnerabilities that have come out recently, there have also been massive breakthroughs in life sciences, fundamental computer science, materials science, and pure mathematics that have all landed in the same time frame. While I still firmly believe that AI will be a net positive for humanity, it's more clear to me than ever that the societal and individual risk is very real, and is playing out NOW.
For as much conviction as I have that this is happening, the thing that's caused me to lose sleep is that I don't really know what to do about it, or more importantly, what to tell you, reader, to do about it. So, the best I can do is make a few suggestions that have always been a good idea but are more timely now than ever:
Set up 2-factor authentication for everything. I use Duo.
Use a password manager across your devices. I use 1Password.
Get an identity protection app set up. I use Alta.
Move your IoT devices to their own network. Claude helped me do this.
And last, but certainly not least, if you've been avoiding leaning into AI, see this as a catalyst to wake up and start using it. Don't just use the chat mode version of ChatGPT/Claude; click that Code/Work button and see how easily you can have AI write code to help you with your job. One of the biggest vulnerabilities was in a massively popular programming language called PHP, and the prompt that set it off was literally, "Find vulnerabilities in php."
This is an unprecedented time for humanity, but as we've done with many things before, we will prevail so long as we are kind, loving, and open-minded to the world.
Much love.
I feel like being shortsighted really was the winning strategy of the last 20 years.
I always loved working with energy based models when I was doing more pure ML work. TBH, the opportunity to use them was pretty rare for me.
One of the most interesting things about them is how much optimality they are actually able to find in a high dimensional space.
Life is exceedingly high dimensional, and has only gotten moreso in the last 10 years.
My partner @raechellambert, when she started hosting @ALLIN_meetups around the world, I was like: "dude, why are you doing this, it's exhausting". Her verbal answer I do not remember, but her actions were clear and correct.
Get out there and just do stuff. Doesn't really matter what. Do it, and then modify, recursive.
In-app AI (Ai inside the app) will not keep your users using your existing product as it currently is.
Most apps should probably just expose via MCP and take the tie or the loss and move on.
A couple of services we use have shut off API access. We didn't need their dashboards because we just have our openclaw use their service and give us updates from time to time.
So we cancelled our subscriptions with those services.
We at @getdnnr do have "in-app" AI available for community owners. But it's because we know the community owners barely use our service more than once or twice a month. It doesn't make sense for them to become familiar with our UI.
SaaS -> S
Service
Just provide great service
Give a mouse a cookie and he asks for a glass of milk
France has FREE health care, paid parental leave, paid family leave, FREE child care, FREE preschool, 5 weeks paid vacation, a 35 hour work week, generous unemployment and housing benefits, and heavily subsidized higher education.
Everything the left says they want AND THEY'RE STILL PROTESTING AND BURNING SHIT DOWN.
"System 1 and System 2" naming about as useful as "Type I error and Type II Error" naming mistake that has yet to be refactored in the area of study of statistics.
Can we please call it:
LLM Classifier and LLM Generator?
Or just
Classifier and Generator?
Thanks
Pay attention to this new wave of System One models if you are building custom harnesses.
First Jev. Now, Contrastive Language Model (CLM).
CLM is 9x faster than Jev.
CLM seems to be a better verifier than Jev, particularly at long-horizon tasks.
How do Jev and CLM differ?
CLM is contrastive, and Jev is trained with Reinforcement Learning for Calibrated Decisions (RLCD).
Jev receives a situation plus predefined questions, and returns typed decisions with probabilities. CLM embeds the situation and candidate actions, compares their similarity, then ranks or selects the best match.
The point is that there are several ways to attack this problem, which is exciting.
You can see my recent guide on combining System One and System Two models for building custom harnesses. academy.dair.ai/resources/je…
100
Replying to @scottastevenson
When you get close to 40, you start to notice a massive divergence between two kinds of people:
1. People who developed intuition and are growing every day
2. People who are still trying to “do things the right way”, who are angry at the world for not rewarding them
Dinners
This is the way
A client once asked me whether they should spend $40K on a sponsor booth at a major SaaS conference or try something smaller.
I told them to take $800, book a private dining room at a steakhouse 4 blocks away, and invite 8 target VPs of Operations who were already attending the event.
We skipped the slide decks entirely. We ordered dry-aged ribeyes, poured two bottles of cabernet, and opened with one question about the messiest operational roadblock everyone was trying to fix that quarter.
The conversation went for 3 hours. Our VP of Product sat next to an enterprise buyer.
Out of those 8 dinner guests:
- 6 booked deep-dive architecture reviews within 14 days
- 3 closed before the end of the quarter
- Total closed ARR from that one $800 dinner was $185K
Meanwhile, the $40K booth across the street collected 340 badge scans and closed zero deals.
B2B buyers with real budget do not make six-figure software decisions while standing in an aisle holding a branded tote bag. They make them over dinner with peers.
Salesforce with renewed gusto in 2026.
@Benioff respect muh dude! 👊
hey @paulg please give it a listen
There are moments when I get feedback on our product that so closely aligns with what I thought about our product, that I wonder if the simulation god is merely matching the difficulty of the environment to my skill level.
It's democratic.
Which is to say, it is unconstitutional.
We started out thinking we’d buy a house.
But the options pushed us farther from the kind of life and community we actually wanted.
So we asked a bigger question: what if we built the place we wanted to live?
That became nitter.cf/freedomvlgNH, a community in New Hampshire for people interested in technology, entrepreneurship, and building life alongside ambitious friends.
We thought a few people might care.
Turns out a lot more do.
Incredibly honored to have such a strong line up for Freedom Summit! Two days for the people building what’s next in biology, energy, housing, technology, and entrepreneurship.
Day 1: Frontier biology, longevity, and the freedom to experiment. What becomes possible when we unlock human potential.
Day 2: Energy, housing, startups, and community at scale. Infrastructure for an abundant future — and the people pulling it off.
• Governor Kelly Ayotte (day 1 headline speaker)
• @jhitchco — General Partner, New North Ventures. Startup founder/investor best known for co-founding Dyn.
• @mansharamani— CEO, Goodwell Foods. Economist and author helping leaders navigate uncertainty.
• @DeanKamen — Inventor / Entrepreneur. Founder of DEKA and FIRST with major robotics and medical-device contributions.
• @RepKeithAmmon— NH State Rep / Technologist. Legislator and advocate for AI, blockchain, Bitcoin, and emerging tech.
• Bill Spellane — Co-Founder & CEO, @StarcubeTech. Builds advanced nuclear microreactors for resilient clean power.
• @pardzz_— VP of Product, Arc. Product leader building financial tools for startups and founders.
• Benjamin Sachs, RA — Architect & Design Leader, Reframe Systems. Focused on housing innovation through advanced manufacturing.
• Julie Demers — Executive Director, @NHTechAlliance. Connects entrepreneurs, innovators, educators, and investors across NH tech.
• @Ryan_G_Lambert Founder & AI/ML Lead, DNNR. Builds creator-matching and monetization systems.
• @Vikas_Enti — Co-Founder & CEO, Reframe Systems. Building AI-powered robotic microfactories for net-zero homes.
• @jack_potvin — Founder & CEO, Business Automation Technologies. Helps organizations use AI and automation to improve ops and CX.
• Philip Magnuszewski — Founder & AI community builder
• John Roth — UNH Olson Center
• Adam Coughlin — York IE
It's shaping up to be 2 days like New Hampshire has never seen — plus affinity dinners, happy hours, and an epic closing party.
Apply to join us: freedomsummit.tech/
fuck yeah
When her son Leo was born with a terrible genetic illness, Yiwei She created an individualized gene therapy: “Leosen”.
We’re fighting to make New Hampshire a hub for therapies like Leo’s. We’re proud to welcome Yiwei to our conference on August 20.
GraniteBio.org/820
Most of "Agile" was mostly just babysitting people instead of firing them.
You didn't need scrum, you needed balls.
Content creators are also community creators, whether they know it or not.
@TheFP understands this. The supper clubs are just one of the community based activities they provide for their subscribers.
Media companies take note!
.@TheFP is using @getdnnr to power supper clubs in 40 cities around the world.
But our story with them actually started years ago. When we were building River, our meetup platform, The Free Press signed on to create a white-labeled experience for its community. We made it pretty far together, but ultimately the format—which relied on crowdsourced volunteer hosts—never felt quite right.
Their interest in bringing readers together was real. Our product and business model simply wasn’t right.
That experience helped push us toward a hard pivot.
We still believed deeply in IRL community and in helping organizations bring their audiences together without having to personally plan or host every gathering. So we took what we had learned about white-label community infrastructure and applied it to social dining.
We launched DNNR almost exactly one year ago.
Our first partner was Troy Farkas, creator of Seacoast Stories, a local newsletter here in New Hampshire. Troy hosts one dinner at a time, in one city, for roughly 125 people. It creates meaningful revenue for his business and real connection in his local community.
Then The Free Press came back to us. This time, we pitched a supper club.
They tested it with friends and family in New York, then immediately scaled to 2,000 people across 30 cities. Their first event sold 2,000 seats. Their second is happening tomorrow night, with another 2,000 people gathering across 40 cities around the world.
It has been an incredible full-circle moment.
Olga Moriarty and Alyssa Ajello, who lead community at The Free Press, have been thoughtful, ambitious partners. Their close feedback has made our product dramatically better.
And together, we’ve proven that this model works at very different scales.
🌱 It can power one 125-person dinner club for a local creator.
🌳 It can also power 2,000 members for a global media company.
In both cases, the community comes together, the organization earns revenue, and more money flows to local restaurants.
That is what excites me most about this next era of IRL community: intimate experiences that can scale without losing what makes them meaningful.
I’m incredibly proud of our team and grateful to The Free Press for trusting us with their community.





















