Building brands in software, apps, services & media. Building. ☕ https://xitter.cf/t.co/Zj0APa4Wd2 🎯 https://xitter.cf/t.co/LWnqQLPgLP 🖊 https://xitter.cf/t.co/j3z7Zk5eGi 📁 https://xitter.cf/t.co/plyPgsop2F
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Joined May 2009
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Chris Riley retweeted
jevon's implications on rl tasks might be somewhat obvious but worth spelling out
as models saturate human work, the surface area for capability & alignment gains starts to shift as the industries transform
take finance: a good task (literally 3 months ago) might be take an earnings call for a stock and update an existing Excel DCF with new mgmt assumptions
model needs taste to "read between the lines" on expectations vs mgmt guides -> you can't take mgmt teams at face value -> the models are now very good at this
finance now moves faster -> pms want live updating dashboards instead of excel workbooks as soon as the mgmt call comes in
consequently, the new surface area shifts:
1. can the model distill the earnings call to the 3 data points that move the stock such that the pm can make a decision faster than her competitors?
2. can the model make a dashboard that is interactive and in-line with house firm style?
3. can the model leverage historical traces and memory to understand how the pm has historically traded this name?
Chris Riley retweeted
Translating @elonmusk here:
He’s basically saying the easy money for AI data center startups just dried up. Prior to this if you had a pulse, power contracts and GPUs, you could raise gobs of money.
Lenders have stopped giving loans to companies whose only business is building GPU farms (aka neoclouds). Unsurprisingly they now want companies that already make real money from something else. @SpaceXSI can still borrow billions for GPUs because it has @Starlink and rocket revenue. Most of the 200+ pure-play neoclouds don’t have that, so a lot of them are going to run out of cash, fail, or get bought cheap.
Pretty much.
As of the past few weeks, debt markets have almost entirely shut off access to money for any company that doesn’t have substantial revenue independent of AI data centers.
SpaceX closed $40B of debt for GPUs, but we’re investment grade and have Starlink & launch revenue.
That means the 200+ neoclouds are going to see guppy-level death and consolidation. Some will make it through, but not many.
Chris Riley retweeted
Most investors are still massively undervaluing data.
I was also skeptical when I left a data co for Altos in 2025. Today, I’m all in on data.
Every software company will become a data company. Most will lose. Many more will win than we think.
Chris Riley retweeted
there's a million dollars trapped in your macbook you just have to sell data to frontier labs to get it
Chris Riley retweeted
There is just no way things don’t work out.
I’ve never seen a future so bright.
All doom is fake.
Things are amazing and only getting better.
I’ve never seen more people winning, in every conceivable way possible.
Losing shouldn’t even enter your conscious
Chris Riley retweeted
The three startup types
1. Model companies
2. Deployment companies
3. Data companies
You might start as one, but chances are you’ll end up being multiple
Chris Riley retweeted
My entire X feed is
- software is dead
- distribution is the moat now
Original thought is dead.
Chris Riley retweeted
proves to be more true everyday
Today micro1 is announcing a commitment to spend $1B over the next 12 months on the acquisition & licensing of enterprise data for AI training, with financial backing from Citi and Hercules.
micro1.ai/blog/micro1-commit…
Chris Riley retweeted
licensing data will become one of the most common revenue line items for companies worldwide, similar to how ads became a default monetization model. for many companies, it will become core to the business.
Chris Riley retweeted
these companies that “fired their whole marketing team and replaced them with AI” have been awfully quiet lately
Chris Riley retweeted
Lots of new valuable guideline data dropped by Google!
Reminder, you can send your content directly in the editor to an expert for fact-checking and review!
🚨 Another critical Google Guidance update: Stop using deceptive authorship information, fabricating creator profiles (to make it look that the content is created by experts with it’s not the case). These make the page untrustworthy and a signal of a low quality page.
This was again something that was obviously deceptive and shouldn’t be expected to replace the actual profile from a known expert of experienced human but given the state of things, like the guidance to review and fact check AI content accuracy … very much needed.
Check it out along with the other updates to the Creating helpful, reliable, people-first content guidance.
Stay up to date with these and more search updates with the SEOFOMO newsletter: seofomo(.)co
Coverage by @rustybrick : seroundtable.com/google-help…
Chris Riley retweeted
People after booking their flights in 2 clicks instead of talking to LLM for half an hour
Chris Riley retweeted
YC and dropout culture have convinced us the ideal founder is 22, straight out of school, but the data tells a different story.
Some interesting data:
- An MIT study of 2.7 million US founders found that the average founder was 47 when starting a company that later exited through an acquisition or IPO.
- The same study cited that the founders of the fastest-growing 0.1% of U.S. startups were 45 years old on average when they started their companies.
- A 50-year-old founder was approximately twice as likely as a 30-year-old founder to produce an acquisition or IPO.
- Founders with at least three years of relevant industry experience were twice as likely to build a top-0.1%-growth company as founders with none.
So it seems that experience is one of the strongest advantages a founder can have.
Two lessons here:
1. It's never too late to start
2. It might actually be TOO early to start; getting work experience is worth considering
Chris Riley retweeted
@bullseye Act as my head of sales. Using Bullseye, find the 3 companies showing the strongest buying intent on our site this week - multiple people from the same account, pricing or demo page visits, ICP fit. For each one, tell me who visited, what they looked at, and why it matters, then write me a 2-line personalized opener for the best contact at each. End with one account I should ignore and why.
