segmenta

Rowing Rowboat (YC S24). Prev: Co-founder/ CTO Agara AI (acq. Coinbase), Coinbase AI, Twitter AI

[segmenta @segmenta]

Introducing Rowboat.

An AI coworker that compiles your emails, meetings, and work into a living knowledge graph, then uses it to actually get things done.

Open source. Local-first. Voice-powered.

Karpathy described the idea last week. We've been building it for a while.

[bayes @bayeslord]

They didn’t mean pause AI research, they meant pause *your* AI research

[Andrej Karpathy @karpathy]

This is a super exciting release - Claude Fable 5 is the same underlying model as Mythos but with added safeguards. The benchmarks are great and it's SOTA on everything by a margin but I'll add that *qualitatively* also, this is a major-version-bump-deserving step change forward (imo of the same order as Claude 4.5 was in November), peaking especially for long problem-solving sessions on very difficult problems. You can give it a lot more ambitious tasks than what you're used to, the model "gets it" and it will just go, and it's never felt this tempting to stop looking at the code at all (but don't do this in prod!). The model still has quirks that people will run into and the safeguards are configured to be a little too trigger happy for launch, which can hopefully be tuned over time.

I feel a lot of things changing as working software increasingly comes out on a tap. The Jevon's paradox kicks in and I feel my own demand for software growing substantially. You can ask for anything - explainers, visualizers, dashboards, bespoke single-use apps (e.g. a full wandb that is hyper-specific just for your project), you can 10X your test suite, auto-optimize code, run giant research projects with custom HTML for the results, anything! "Free your mind" (Matrix ref). Really looking forward to all the things people build!

[Claude @claudeai]

Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use.

Its capabilities exceed those of any model we’ve ever made generally available.

[Garry Tan @garrytan]

So close to product market fit is still not product market fit

[MTS @MTSlive]

SITUATION DETECTED: For the first time in internet history, agentic traffic has surpassed human traffic online, per Cloudflare Radar.

[segmenta @segmenta]

Today I asked latest Opus how to enable mic and speaker on a remote mac mini on AWS. Its top suggestion was ‘why don’t you just use your macbook’. Please don’t pause AI development.

[Anthropic @AnthropicAI]

Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.

It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx

[sarah guo @saranormous]

a lot of very successful companies look like a series of pivots (tacking?) in a general direction

[segmenta @segmenta]

@bryan_johnson This should be temporary, correct?

[Tim Soulo 🇺🇦 @timsoulo]

In the last 6 months at @Ahrefs, we analyzed over 1 billion data points across 14 studies. Here's what we learned about AI search optimization:

1) "Best X" blog listicles are the single most prominent content format cited by AI chatbots. They make up 43.8% of all page types cited by ChatGPT specifically.

2) 67% of ChatGPT's top 1,000 citations come from sources marketers can't influence: Wikipedia (29.7%), homepages (23.8%), app stores (6.6%). Only 32.3% are influenceable content like educational pages, reviews, news, and blog posts.

3) 28.3% of ChatGPT's most-cited pages have zero Google organic visibility. These pages get cited repeatedly by ChatGPT despite not ranking in Google at all. A completely separate discovery layer.

4) ChatGPT only cites about 50% of the URLs it retrieves. It fetches dozens of pages per query but uses half as background context without attribution. This means that being retrieved and being cited are very different things.

5) Adding schema markup had zero meaningful impact on AI citations. AI Overviews actually dipped −4.6%, while AI Mode (+2.4%) and ChatGPT (+2.2%) showed changes indistinguishable from zero.

6) YouTube mentions have the highest correlation (0.737) with AI brand visibility out of all the factors we studied (including all the conventional SEO metrics like backlinks, page count, DR, etc). This held true for both Google-owned and OpenAI products.

7) AI Overviews reduce clicks to the #1 result by 58%. That’s up from 34.5% just 10 months earlier. The trend is accelerating.

8) 99.9% of AI Overviews appear on informational intent queries. Transactional, navigational, and local searches are almost entirely AIO-free. Shopping triggers AIOs just 3.2% of the time.

9) For a given search query, Google’s AI Mode and AI Overviews reach the same conclusions 86% of the time — but cite almost entirely different sources (only 13.7% citation overlap).

10) AI Overviews change every 2.15 days on average, with 70% of content differing between consecutive observations. But semantic similarity stays at 0.95. The words, sources, and entities constantly shuffle, but the actual meaning barely moves.

[segmenta @segmenta]

For the longest time I thought Costco brand Kirkland was building AI stuff and found it amusing. Now terribly disappointed to learn that the Kirkland ppl were talking about is a law firm 🤦‍♂️

[FleetingBits @fleetingbits]

some thoughts on kirkland building its own harvey

1) kirkland is spending $500m over four years in order to build its own internal ai legal tools; kirkland intends to spend $100m this year

2) i suspect that kirkland is doing this because they have told themselves that they have valuable data and because they want to appear differentiated

3) i think the first issue is that kirkland probably does not have differentiated data from other elite law firms; at least, not at the level a harvey would absorb

4) all the elite firms probably have similar internal workflow data and so long as some of them defect, that is enough to commoditize the data kirkland wants to use for its platform

5) and, to the extent that they do have different internal workflows, harvey and legora will end up representing a better version of them and this will put kirkland at a disadvantage

6) moreover, companies like kirkland will have difficulty building their internal legal platforms because they do not have experience with software development

7) and, there are both cultural and structural issues with them managing software developers, like they cannot give non-lawyers equity in the firm due to regulation

8) so, i think firms like kirkland are better off using tools like harvey and legora and then looking to focus on where their value really is now: client relationships, local knowledge (litigation, regulation) and legal r&d (novel structures, etc...)

9) anyway, this seems to me like a phenomenon that ai creates across a lot of industries, where firms that were previously vertically integrated become unbundled due to ai because part of the intelligence gets moved to the labs or otherwise gets commoditized

10) and so, a new set of companies are created whose job it is in order to provide services complementary to the labs: forward deployed like harvey and legora and data providers like mercor, surge and handshake

[segmenta @segmenta]

"patience is the moat"

[Garry Tan @garrytan]

Be your self, not someone you were assigned to be!

Bezos won on time horizon, not AWS or 1-Click.

If your bets have to work in 3 years, you compete with everyone. Every smart, funded team is chasing the same 3-year problems. Short horizon, crowded field.

Stretch to 7 and the field collapses. Investors want returns, employees want vesting, founders want proof. Almost nobody can sit in a bet that doesn't pay for most of a decade. The patience is the moat, and it costs you, that's why it works.

But you can't fake a 7-year horizon on a problem you don't actually care about. Pick the users and the problem Moloch assigned you, the safe ones, the fundable ones, and you'll bail the first hard year. Pick the ones that are actually yours and you'll still be there when everyone else has quit.

So the real prerequisite isn't discipline. It's knowing yourself well enough to choose a problem and a set of people you care about that you'll serve them for decades.

[segmenta @segmenta]

@AdamRackis I saw the same thing today!

[🎭 @deepfates]

I fear not the man who vibe coded 50 new apps, but the man who vibe coded one new app 50 times

[Paul Graham @paulg]

@charliermarsh Sometimes they're a good reason to work on something. When people say a market is "crowded," what that often means is that there's a real problem and none of the solutions are good enough yet.

[Beff (e/acc) @beffjezos]

AI is a talent amplifier, not a talent replacement

[segmenta @segmenta]

Screens are proactive in a way. Forming a question takes a lot more cognitive effort than looking at screens.

[Jason Fried @jasonfried]

I think you're going to see it's all going to converge back to screens and data and panels and buttons.

People don't want to ask the same question over and over. They'll ask something, it'll be set up to show something, and that thing will be saved as something they can always look at. Stable pre-defined glances, not blank slates each time. Common questions will become buttons and panels again.

Most people ask the same kinds of questions about what they work on most of the time. Having to start from scratch with the questions every time seems like a step backwards.

Another way to put this: Questions are wonderful for a deeper dive, but not a daily drive.

Not sure you're suggesting questions always, but the comparison screenshots looked that way.

[Garry Tan @garrytan]

Exactly right. The bottleneck has never been compute or capital. Its taste and judgment about what humans actually want. Infinite compute just makes the great founders faster and the confused ones more confused. https://t.co/AmPmal8NYF

[segmenta @segmenta]

A really good point

[segmenta @segmenta]

@IterIntellectus I would probably start by asking them for a demo. What if they solved climate change or something?

[Claude @claudeai]

Introducing Claude Opus 4.8: it builds on Opus 4.7 with sharper judgment, more honesty about its own progress, and the ability to work independently for longer than its predecessors.

Available today at the same price.