Jon Lexa retweeted
This essay by @alexolegimas is the best thing I've ever read on why AGI won't lead to mass unemployment. A compelling argument backed up by substantial empirical data.
Jon Lexa retweeted
LLM Knowledge Bases
Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating knowledge (stored as markdown and images). The latest LLMs are quite good at it. So:
Data ingest:
I index source documents (articles, papers, repos, datasets, images, etc.) into a raw/ directory, then I use an LLM to incrementally "compile" a wiki, which is just a collection of .md files in a directory structure. The wiki includes summaries of all the data in raw/, backlinks, and then it categorizes data into concepts, writes articles for them, and links them all. To convert web articles into .md files I like to use the Obsidian Web Clipper extension, and then I also use a hotkey to download all the related images to local so that my LLM can easily reference them.
IDE:
I use Obsidian as the IDE "frontend" where I can view the raw data, the the compiled wiki, and the derived visualizations. Important to note that the LLM writes and maintains all of the data of the wiki, I rarely touch it directly. I've played with a few Obsidian plugins to render and view data in other ways (e.g. Marp for slides).
Q&A:
Where things get interesting is that once your wiki is big enough (e.g. mine on some recent research is ~100 articles and ~400K words), you can ask your LLM agent all kinds of complex questions against the wiki, and it will go off, research the answers, etc. I thought I had to reach for fancy RAG, but the LLM has been pretty good about auto-maintaining index files and brief summaries of all the documents and it reads all the important related data fairly easily at this ~small scale.
Output:
Instead of getting answers in text/terminal, I like to have it render markdown files for me, or slide shows (Marp format), or matplotlib images, all of which I then view again in Obsidian. You can imagine many other visual output formats depending on the query. Often, I end up "filing" the outputs back into the wiki to enhance it for further queries. So my own explorations and queries always "add up" in the knowledge base.
Linting:
I've run some LLM "health checks" over the wiki to e.g. find inconsistent data, impute missing data (with web searchers), find interesting connections for new article candidates, etc., to incrementally clean up the wiki and enhance its overall data integrity. The LLMs are quite good at suggesting further questions to ask and look into.
Extra tools:
I find myself developing additional tools to process the data, e.g. I vibe coded a small and naive search engine over the wiki, which I both use directly (in a web ui), but more often I want to hand it off to an LLM via CLI as a tool for larger queries.
Further explorations:
As the repo grows, the natural desire is to also think about synthetic data generation + finetuning to have your LLM "know" the data in its weights instead of just context windows.
TLDR: raw data from a given number of sources is collected, then compiled by an LLM into a .md wiki, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance the wiki, and all of it viewable in Obsidian. You rarely ever write or edit the wiki manually, it's the domain of the LLM. I think there is room here for an incredible new product instead of a hacky collection of scripts.
Jon Lexa retweeted
openai and anthropic probably have terrible sales reps
they're talented, but they've never actually had to sell anything.
ben horowitz said it best in a recent conversation: "right now with openai and anthropic, everybody wants to buy ai. they're already predisposed to buy."
that's order-taking, not selling.
let's zoom in on this distinction.
1) the order-taker problem
cloudflare's CEO admitted in 2023 their product was so good that "many of our sales team succeeded largely by just taking orders." deals were like "fish jumping right in the boat."
then the economy shifted and they fired 100 salespeople who'd contributed just 4% of new business.
when your product sells itself, mediocre reps look like rockstars. they crush quota, win the president's club, and get promoted into leadership.
nobody knows they can't actually sell until the fish stop jumping in the boat.
2) why hard sells matter
ben won't shut up about ptc, a 90s cad/cam company. the product "wasn't that great." "the windshield wiper didn't work."
but that forced discipline. you had to map accounts systematically, lay traps for competitors, and build airtight technical cases.
his favorite hire was ryan gabrisco at databricks, who came from a company selling secure ftp as a public company. think about how good you have to be to make quota selling that.
when ben hires sales leaders, he looks for people from companies where the product was hard to sell because that's the only way to test if someone can actually sell.
3) what happens when markets turn
every hot market eventually cools. i'll give you a few examples.
salesforce in 2001. facebook ads in 2012. aws in 2015. the order-takers got exposed every time.
modern AI sales reps don't know how to qualify prospects who aren't already sold or how to systematically lock out competitors or how to build pipeline when inbound dries up.
ben's story about hiring at Okta: two candidates, one super enthusiastic, the other said "let me talk to your customers first." ben told the ceo: "you want the guy qualifying YOU. that's what good salespeople do."
4) openai scaled their sales team from 10 to 500 people in under two years. anthropic is scaling fast too. but how would anyone know if they're good?
you can't test sales ability when customers are lined up begging to buy.
when real competition arrives, the kind where enterprises have three viable options and care about pricing, support, and vendor risk, AI companies will discover which GTM leaders can actually sell and which ones were just processing waitlists.
5) how to hire right
if you're building a GTM team right now, think like a value investor.
resumes don't matter. look for human capital that the market has significantly underpriced.
someone who's had to sell a product that didn't sell itself, someone who's built discipline through necessity, not abundance (no order-takers).
find the person who sold enterprise software at a company nobody's heard of.
find the person who had to fight for every deal because the competitor was already embedded in the account. the person who figured out how to systematically lock out competition even when they were the underdog.
those skills matter.
for AI companies, the question is whether they can close deals when the market shifts.
because when inbound dries up (it always does), you'll discover who can actually sell.
Jon Lexa retweeted
I'm going to make some obvious points.
(1) Blowing up all the oil infrastructure in the Middle East is an insane idea, and may well result in a global economic crash and humanitarian crisis unrivaled in the lives of those now living. We're talking about the price of everything everywhere rising, from food to gas, at a moment when inflation was already high. All of that will be laid at the feet of the authors of this war.
(2) The antebellum status quo of Feb 27, 2026 was just not that bad, but we're unlikely to return to it. Expect indefinite, long-term, ongoing disruptions to everything out of the Middle East.
(3) Also assume tech financing crashes for the indefinite future. The genius plan to get the Gulf states caught in the crossfire has incinerated much of the funding for LPs, for datacenters, and for IPOs. Anyone in tech who supported this war may soon learn the meaning of "force majeure" as funding gets yanked.
(4) Many capital allocators will instead be allocating much further down Maslow's hierarchy of needs, towards useful basic things like food and energy.
(5) It's fortunate that all those progressives yelled about the "climate crisis." Yes, their reasoning about timelines was wrong, and much of the money was wasted in graft, but the result was right: we all need energy independence from the Middle East, pronto. It's also fortunate that Elon and China autistically took climate seriously. Now they're going to need to ship a billion solar panels, electric vehicles, batteries, nuclear power plants, and the like to get everyone off oil, immediately.
(6) It's not just an oil and gas problem, of course. It's also a fertilizer problem, and a chemical precursor problem. Maybe some new sources will come online at the new prices, but it takes time to dial stuff up, particularly at this scale, so shortages are almost a certainty.
That said, China has actually scaled up coal-to-chemicals[a,c] (C2C), and there's also something more sci-fi called Power-to-X[b] which turns arbitrary power + water + air into hydrocarbons. But all of that will need to get accelerated. I have a background in chemical engineering so may start funding things in this area.
(7) Ultimately, this war is going to result in tremendous blame for anyone associated with it. It's a no-win scenario to blow up this much infrastructure for so many people. Simply not worth it for whatever objective they thought they were going to attain. But unless you're actually in a position to stop the madness, the pragmatic thing to do is: scramble to mitigate the fallout to yourself, your business, and your people.
[a]: reuters.com/business/energy/…
[b]: alfalaval.com/industries/ene…
[c]: reuters.com/sustainability/c…
Jon Lexa retweeted
Sana AI Summit is coming to New York City. Mark your calendars for May 21, 2026 and register interest now: sanalabs.com/events/sana-ai-…
Jon Lexa retweeted
Today marks a defining moment for Sana:
We’ve entered into a definitive agreement to be acquired by Workday.
Sana will continue to build Sana Agents and Sana Learn—only now, at an even faster pace and greater scale. I’ll continue to lead our incredible team.
Over the past months, we’ve had the privilege of getting to know Workday’s leadership. They are brilliant, kind, and hungry to win. I’m excited to build alongside Peter Bailis, Aneel Bhusri, Carl Eschenbach, Gerrit Kazmaier, and their nearly 20,000 Workmates.
Sana has always been about two things: creating a place where people can do their life’s work, and building products that accelerate how the world accesses knowledge. This partnership lets us stay true to that vision while massively expanding our impact.
When I founded Sana in 2016, I had just read Organizing Genius and early AI breakthroughs like AlphaGo had recently been released. I set out to build an AI research lab to change how people access knowledge. Joined by a group of pragmatic dreamers, we built a team, a culture, and tools that have reimagined how over a million people learn and work.
Thank you to everyone who believed in us—our customers, investors, and most importantly, Sanians.
This is a win for Europe, for beauty, for idealism, and for caring more.
Now, a new chapter begins. The infinite game continues. Let’s go make history.
Jon Lexa retweeted
Sana is collaborating with @nvidia to support the next generation of innovators.
Startups participating in the NVIDIA Inception program can now access Sana Agents on the Team plan at 50% off for the first year. We look forward to what you’ll build next.
Learn more about the program and apply: nvda.ws/4jW48Op
Jon Lexa retweeted
Announcing @NEA Venture Partner Hilarie Koplow-McAdams as our newest board member.
@HilarieKM knows the software industry inside out—having catalyzed its evolution as an operator, advisor, and investor over three decades. Prior to joining NEA, Hilarie held President roles at New Relic and Salesforce. We are humbled to have her on our mission.
Jon Lexa retweeted
A couple reflections on the quantum computing breakthrough we just announced...
Most of us grew up learning there are three main types of matter that matter: solid, liquid, and gas. Today, that changed.
After a nearly 20 year pursuit, we’ve created an entirely new state of matter, unlocked by a new class of materials, topoconductors, that enable a fundamental leap in computing.
It powers Majorana 1, the first quantum processing unit built on a topological core.
We believe this breakthrough will allow us to create a truly meaningful quantum computer not in decades, as some have predicted, but in years.
The qubits created with topoconductors are faster, more reliable, and smaller.
They are 1/100th of a millimeter, meaning we now have a clear path to a million-qubit processor.
Imagine a chip that can fit in the palm of your hand yet is capable of solving problems that even all the computers on Earth today combined could not!
Sometimes researchers have to work on things for decades to make progress possible.
It takes patience and persistence to have big impact in the world.
And I am glad we get the opportunity to do just that at Microsoft.
This is our focus: When productivity rises, economies grow faster, benefiting every sector and every corner of the globe.
It’s not about hyping tech; it’s about building technology that truly serves the world.
Readers added context they thought people might want to know
Microsoft's supporting paper, published in Nature, does not support the claim that they have created a topological qubit. nature.com/articles/s4158…
Peer reviewers of the Nature paper expressed concern that the paper misleadingly implies that a topological qubit was demonstrated or otherwise achieved: static-content.springer.com/esm/art%3A10.1…
Jon Lexa retweeted
Introducing Agentic Object Detection!
Given a text prompt like “unripe strawberries” or “Kellogg’s branded cereal” and an image, we use an agentic workflow to reason at length and detect the specified objects. No need to label any training data. Watch the video for details.
Jon Lexa retweeted
A viral thread about a growing number of "quiet quitting" SWEs was seen 15M+ times (and led to a crack down at Box)
My DMs have been full of ppl telling me that people badge in for 30mins/day and go on 5+ intl vacations/yr at these companies.
Here's what went down..
1/4
Jon Lexa retweeted
🧠 What if your organization could access all its knowledge, instantly? @joelhellermark, CEO of @sanalabs, has built a solution that makes this possible, one that’s especially crucial in challenging times. During the pandemic, Sana’s AI-powered learning system helped upskill over 150,000 nurses in record time. Learn how Sana is empowering organizations worldwide in our latest Q&A with Joel and NEA's @luke_pappas
nea.com/blog/sana-ceo-joel-h…
#ai #founders #interview #founderforward
Jon Lexa retweeted
Today, we released our State of Generative AI in the Enterprise, which draws on real-world budget data and insights from 450+ enterprise executives to unveil the evolving landscape of AI adoption, market trends, and how the future may play out.
The biggest surprise? Despite all the hype, enterprises aren’t spending big dollars just yet.
And, while the report reveals that today’s market favors incumbent players, it also reveals three areas of opportunity where STARTUPS have the best chance to break out. 🚀🚀🚀
Read the full report mnlo.vc/Ent_AI_Report or check out @VentureBeat’s article via @taryn_plumb mnlo.vc/Ent_AI_venturebeat
via Menlo’s @npilosof and @derekgxiao
Jon Lexa retweeted
Imagine you were born in 1900.
When you're 14, World War I begins and ends when you're 18 with 22 million dead.
Soon after a global pandemic, the Spanish Flu, appears, killing 50 million people. And you're alive and 20 years old.
When you're 29 you survive the global economic crisis that started with the collapse of the New York Stock Exchange, causing inflation, unemployment and famine.
When you're 33 years old the nazis come to power.
When you're 39, World War II begins and ends when you're 45 years old with a 60 million dead. In the Holocaust 6 million Jews die.
When you're 52, the Korean War begins.
When you're 64, the Vietnam War begins and ends when you're 75.
A child born in 1985 thinks his grandparents have no idea how difficult life is, but they have survived several wars and catastrophes.
Today we have all the comforts in a new world, amid a new pandemic. But we complain because we need to wear masks. We complain because we must stay confined to our homes where we have food, electricity, running water, wifi, even Netflix! None of that existed back in the day. But humanity survived those circumstances and never lost their joy of living.
A small change in our perspective can generate miracles. We should be thankful that we are alive. We should do everything we need to do to protect and help each other.
Jon Lexa retweeted
Stockholm-based learning platform Sana has announced a suite of generative AI tools along with an extension to its Series B round, bringing its total funding to $80 million. trib.al/33QZ9cr
