SteveA

@gregcroc @SpotHero To me, there are few worse things than driving around the city randomly looking for a spot.

@Steve_Aug @SpotHero This must be a Norcal thing 🤣 either that or my being a legit hermit

Intrigued to try this out. I don't think I have ever reserved parking, but would like to explore other use cases.

Resident Evil 2 looking amazing on the @Snapdragon X2 Elite Extreme 😍 youtube.com/watch?v=OnDe8J…

@draginol Done. I keep passing you folks onto anyone who asks, "What's an agent really do?"

Can *someone* please bookmark this so that in 2 months some Bay area person "discovers" that combining Agile with AI agents is the way to orchestrate agents someone can point out Clairvoyance was doing it already? It was already doing MD based knowledge bases and HTML outputs. I figure the next obvious thing will be Sprints.

@AndrewBedell1 @eric_seufert This is what we are going to learn. Much of SAS is not a software business. It is a trust, marketplace, and data management business.

@eric_seufert Very hard to do and no matter how good you can vibecode the software you will never get the inventory or demand.

AppLovin $APP released its Q1 2026 earnings: revenue of $1.842 BN (+59% y/y), Net Income from continuing operations of $1.206 BN (+67% y/y), Q2 revenue guidance of $1.915 BN - $1.945 BN.

@Penv31175 @cecianasta I'd like this tweet but there's no upside in it for me...

@cecianasta We live in endless series of promotional events. Everything is fake.

New: Manosphere influencer Clavicular is everywhere, and that’s not an accident. A paid marketing campaign is spreading video clips of his controversial antics across social media. bloomberg.com/news/articles/…

@analogint3rfac3 @Austen For sure, if all you are managing is YOUR inventory then you can roll your own. But if you are trying to keep your supply chain tight you need to connect that to your supply and channel partners. I don't think they are going to be ok just supporting your home grown APIs...

@Steve_Aug @Austen Inventory is likely easier than it seems even prior to AI coding era lots of large companies built their own inventory and warehouse management systems. The build versus buy analysis may shift that behavior down market now that building software is cheaper.

What is the SAAS companies are least likely to build internally? Honestly it's probably video conferencing (Zoom, Google Meet), CRM (Salesforce/Hubspot) and messaging (Google Workspace/Slack). Anything else I'm missing?

@packyM "... and this is why I'm certain this will fix the problem." On the 50th time I've tried to get help without it, in fact, fixing the problem.

Me: Can you tell me about [thing]? Claude: ah, yes. You’re probably asking because of your interest in [other thing], and honestly, those two things have more in common than you even realize. [Bastardized version of [thing] that contorts it to fit [other thing].]

@SemiAnalysis_ @dylan522p This new dating site is quite something.

Hi i'm dwarkesh! Grew up all over the US, now sf-based and always down to nerd out about AI, science & history :) a lil about me: 🟠 Host of the dwarkesh podcast 🟠 Studied at UT Austin 🟠 Just published a book on the history of AI scaling Lets grab coffee or do a fun activity this summer

@eric_seufert If OpenAI can buy TBPN...

I’m diversifying.

@TedMerz @TrungTPhan Super cool but not the first time an outsider was the source of aggregate data via public APIs. Honestly, it's surprising it took this long. Let me introduce you to Steam Spy. en.wikipedia.org/wiki/Steam_Spy

The best story about The New York Times this week didn’t appear in the paper. In fact it wasn’t an article at all, but a web site created by a freelance journalist named Ted Alcorn. Alcorn tapped into the paper’s public API to create a dashboard that provides some extraordinary insights. The first was that over the past 25 years, the Times employed – at various times – a total of 26,000 reporters who wrote 1.5 billion words to produce 2.2 million articles. You can use the dashboard to drill down to see which beats, topics and people have been covered the most and how that coverage has fluctuated. A few examples of the kinds of things Alcorn cited that he noticed: ➡️Trump dominates headlines vs everyone ➡️Maggie Haberman has the most bylines recently ➡️India has been undercovered per-capita ➡️China coverage peaked around 2014 ➡️Iowa stories surge every four years Political partisans will mine the site for ammunition to argue the paper of record is pro THIS or anti THAT. But that debate misses larger truths unearthed counting the number of stories in so many ways over such a long time period. The volume provides a measure of attention largely independent of ideology. Whether a news story about Trump is positive or negative doesn’t change the fact it is about Trump. And the fact that a story was published about Trump reflects interest in hm. It’s not a perfect system, but at this scale, breath and consistency, there is probably no better public dataset to measure what is on everyone's mind. What Alcorn built – whether he realized it or not – was effectively a better version of Google Trends. Google Trends provides comparisons based on search but they don't give you the actual data. It's normalized so you get relative percentages and that limits the comparisons you can make. The Times archive comes from a single institution with a mostly consistent editorial policy over 25 years. That makes apples to apples comparisons possible. It’s a clean cohort in a world where good data is hard to find. It provides a useful signal for understanding how attention has shifted among countries, companies, or individuals. Times reporters jumped on the site when it appeared, mostly to see where they ranked on the leader board. Times editors will likely use the tool to better understand how coverage has shifted. Given its utility, it’s sort of insane that it took an outsider to build it. But in an open API world, the best analytics often are built by people outside the wall. Alcorn explained the difficulty of reconciling data: Categories shift and reporters change names. The same subject gets coded differently over time. Some Times reporters flagged bugs and suggested features. But so far the paper hasn’t commented on the project, which he cheekily called Below the Fold. Here is the link to the @tedalcorn site tedalcorn.github.io/nyt/

@Austen True, in fact, this is how gyms, teams and (to some extent) schools are picked already.

Kids sports, but at the beginning of the season they ask parents to assign a percentage likelihood their kid will go pro and separate the league into 0% and not 0%

@JamesBorow @Meta Notice that high ad marbling? That's where the intense ad flavor comes from.

In a few months when @Meta launches ads in Meta AI, everyone is going to realize that Meta Ads are already AI, and that ads in AI look like Meta Ads.

@draginol @AiClairvoyance Almost all new interaction designs and business models, even those for work, come from the gaming industry. Slack is a perfect example.

I think the game industry will be the first to see the total transformation of their development workflow from AI. It'll be an "adapt or die" situation. Case in point: Human design team puts their first draft of a game design together. I work with @AiClairvoyance to make changes to it.

The Artemis II crew had the rare chance to see a solar eclipse from space. 🚀🌘☀️ This video stitches together views from Orion's solar array wing cameras throughout the eclipse, showing the Sun as it disappears behind the Moon, revealing a glowing halo around the lunar disk.

Super excited to see this launch!

Cool deal here!!!

Introducing Snapdragon Insiders Packs. Purchase a qualifying @ASUS laptop powered by #SnapdragonXSeries and unlock exclusive games and apps selected specifically for Snapdragon Insiders. Power your next play: bit.ly/4mjX3ZT

@Austen It remains to be seen but this could easily dwarf the Y2K investment the industry had to make. It will also, like Y2K, reset the baseline age for legacy systems and their refresh timelines.

Claude Mythos is showing us the entire internet and global economy has been wholly reliant on security by obscurity. A few smart bad actors with a whole lot of time and we’d be done for.