Tom Chen

1.7K posts

Tom Chen

Tom Chen

@TommayC

San Francisco, CA Katılım Mayıs 2009
314 Takip Edilen219 Takipçiler
Tom Chen
Tom Chen@TommayC·
@TMTLongShort You can’t view this in isolation. He also has options with codex, open models, etc. The equilibrium price on this is just as much subject to the competition as it is compared to human opex
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Just Another Pod Guy
Just Another Pod Guy@TMTLongShort·
On the fly math by 20VC estimates Benioff’s stated $300m in annualized Anthropic spend comes out to $1.2k per engineer per month or something like 3-5% of fully burdened budget per head. Thats retardedly low and reflects delusion on Benioff’s part when he frames it within his expectation of moderating over time instead of exploding higher. This is the problem with fat & lazy execs they remain calm because they understand the micro-structure of their immediate industry & vertical but fail to be paranoid enough and preemptively forecast the game theoretic equilibrium when there is a systemic shock from the top-down.
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Tom Chen
Tom Chen@TommayC·
@BernieSanders Can we please see a live debate between you and @JeffBezos? I would pay $$. And all $$ can go to your charity of choice
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Bernie Sanders
Bernie Sanders@BernieSanders·
Mr. Bezos: Let's have that debate. Under my 5% billionaires wealth tax, we'd: -Give $12K to a working family of 4 -Expand Medicare for dental, vision, hearing -Guarantee universal childcare -Raise starting teacher pay to $60K And you'd still be worth $269 billion after taxes.
More Perfect Union@MorePerfectUS

Jeff Bezos on CNBC: "If people want me to pay more billions, then let's have that debate, but don't pretend that that's gonna solve the problem. You could double the taxes I pay, and it's not gonna help that teacher in Queens.... Airbnb isn't causing high rents. What's really causing high rent is government intervention."

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Tom Chen
Tom Chen@TommayC·
@jasonlk Jason - are we sure we should be taking any sales tips from the hottest product company where 54% of enterprise logos came through self serve?
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Jason ✨👾SaaStr.Ai✨ Lemkin
54% of Anthropic's new enterprise logos in 2026 came through self-serve. Self-serve enterprise. Real ACV. Real terms of service. No AE in the loop. Anthropic's Head of Industries Eleanor Dorfman walked through at SaaStr AI 2026 last week how they rebuilt the entire sales org in 30 days after Claude Opus 4.6 broke their demand curve in December. 👉The constraint: couldn't 3x or 4x the sales team fast enough without lowering the recruiting bar. The thesis: don't buy a new stack. Thread Claude through the one you already have. What they kept: 1⃣ Clay for enrichment 2⃣LeanData for routing 3⃣ @salesforce as system of record 4⃣@Gong_io for call coaching 5⃣Ironclad for contracts 6⃣@slackhq for everything else What they added: Claude as the connective tissue between all six. The four moves: 1/ Killed the PLG vs SLG orthodoxy. Launched enterprise self-serve in January. Intercom Fin guides the buyer through the journey. Now 54% of new enterprise logos. 2/ Threaded Claude through the existing stack. Every AE starts the day with a "morning brief" Skill that pulls context from Gmail, Gong, Slack, Salesforce, @intercom, Greenhouse. 3/ Made Slack the front door for every support function. Slack ticket in, Jira ticket out. Claude triages and resolves inline if it matches precedent. Escalates with full context if not. 4/ Codified what the best reps do as Skills. Every new rep gets a sales plug-in with 5 Skills: morning brief, call prep, customer follow-up, competitive intel, create-an-asset. Anthropic didn't replace anything. They invested in the stack they already had and let Claude be the seam between everything. Most companies will spend 2026 evaluating AI-native sales platforms. But Anthropic did it with its current stack + Claude. Almost none of it required new software.
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Tom Chen
Tom Chen@TommayC·
@nikunj Finally someone that both says we are about to hit fully autonomous co workers and in the same paragraph say diffusion will take 20 years.
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Nikunj Kothari
Nikunj Kothari@nikunj·
Even in the AI pilled crowd of the Bay Area, I think VERY few people have priced in the fact that we have already gone from assistant -> coworker -> and soon entering autonomous workers.. Yes, "autonomy" truly doesn't work yet, but the harnesses and the model capabilities are going to get us there within this area for a large faction of jobs. This is quite evident from a) labs desire to collect long horizon task data in RL environments b) these model harnesses allowing longer and longer tasks (see /goal or Droid Missions) and c) how good these models are able to recursively correct its mistakes. AI has officially entered the diffusion era (not diffusion models) where models just need to be diffused in everything they do. And that will take the next 10-20 years or as I call it the last mile of the last mile.
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Tom Chen
Tom Chen@TommayC·
@clairevo The token burn is also really high. I barely can do one task before Im rate limited
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claire vo 🖤
claire vo 🖤@clairevo·
Been testing Claude Managed Agents + ChatGPT agents a bit, and even for tasks of moderate complexity tasks, I much prefer the turn/response style "chat" interface + tools than the "spin up a computer" experience of an Agent. Latency is too high and it does't feel the juice is worth the squeeze.
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Tom Chen
Tom Chen@TommayC·
@AOC Dumbest logic I’ve ever heard
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Alexandria Ocasio-Cortez
Someone can certainly *make* a billion dollars. That’s not the same thing as earning. Growing fast and disrupting markets also often means chasing and wielding market power, political influence, and scale. Take Airbnb. They heavily lobby politicians against passing housing laws to protect working class residents because it’s bad for their business model. Airbnb could not exist at its current scale and size without the housing market destabilizations, displacements, and exploits that are supercharging the evictions of working people everywhere from Puerto Rico to Jackson Hole. Now young people are planning for a future where they will never be able to afford to own a home while others have 20 and live off renting it out to them at extortionate rates with zero protections. Yes, a tiny amount of people can make billions of dollars doing that. And millions of everyday Americans are bearing the cost.
Paul Graham@paulg

Sure you can earn a billion dollars. I've been teaching people how to do it for 20 years. The way you do it is to start a company that grows fast. You don't have to do anything bad to make a company grow fast. You just have to make something people want. paulgraham.com/ace.html

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Tom Chen
Tom Chen@TommayC·
@0xdoug You’re also not accounting for non devs. I wasn’t a dev and I barely have enough time to use it, my Claude enterprise account ranges anywhere from 200-700 a month. And I barely use it
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Doug Colkitt
Doug Colkitt@0xdoug·
A lot of people objected to, were even outraged, that restricting the revenue analysis to American software workers. But let’s think about how much Anthropic revenue could be international. Excluding China and Russia (Claude not available), the US makes up about 20% of global devs. But one thing to keep in mind is, to get to $44 billion ARR, the only thing that really matters is devs paying $1k/month. Even Max subscribers don’t move the needle at that scale. Realistically, devs outside America aren’t expensive enough for this to make financial sense. Median software engineer salary in India (largest international dev market outside US and China) is $30k, is it reasonable believe that Indian firms are casually accepting a 50% cost hike on their software engineers to give them API scale token budgets? Again I believe many, if not most Indian devs are using Claude. But (like myself) my guess is the vast majority are using the much more cost effective subscription and managing limits. Same story in most other countries. Median software engineer salary in Europe is $60k, in Japan $50k, in Brazil $30k, in Britain $65k . I’m not saying there is zero API usage in these countries, but I think it’s unrealistic to think these countries have anywhere near the casual API spend that US software engineers have. I think a conservative upper bound on international API revenue is maybe 50%. If we go back to US devs being 20% of the global market, then assuming they have 2X Claude spend intensity seems reasonable. So at most, the original analysis has a 2X on the denominator. Doesn’t really fundamentally change anything in the order of magnitudes. To the extent software work is driving the Anthropic ARR, either near majorities of devs must be spending thousands per month, or there must be significant super users who are blowing through tens or even hundreds of thousand per month.
Doug Colkitt tweet media
Doug Colkitt@0xdoug

I’m really struggling to see how the back of the envelope math on this works out… There are generously 4 million characterized “software workers” in America. That’s pretty broad and includes a lot of people who aren’t really classical engineers don’t produce that much code. That comes out to nearly $1k per month of average Claude spend across every dev in America. Yes, there’s some international usage, but it can’t be that much. Yes there is some non software Cowork usage, but that doesn’t use that many tokens. Yes, some non engineers are using Claude to vibe code, but I really doubt many are spending hundreds per month on. Even if we assume 50% of all software workers are using Claude, that comes out to $2k spend per month per Claude user. Thats 10X more than the highest tier Max subscription. So almost all of Anthropics revenue has to be API billing So the only explanation is that something like 20%+ of software engineers are not only Claude users but on API billing and regularly spending thousands per month. At $5/m Opus tokens that means the average API user has to be going through something like 25 million tokens per day. *OR* the other possibility is API revenue is heavily power law dominated. Maybe there’s just something like 100k super users who are making up the majority of the revenue. For that to work the typical super user would have to be spending on the order of $50k/month and guzzling nearly 1 billion tokens per day.

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Doug Colkitt
Doug Colkitt@0xdoug·
I’m really struggling to see how the back of the envelope math on this works out… There are generously 4 million characterized “software workers” in America. That’s pretty broad and includes a lot of people who aren’t really classical engineers don’t produce that much code. That comes out to nearly $1k per month of average Claude spend across every dev in America. Yes, there’s some international usage, but it can’t be that much. Yes there is some non software Cowork usage, but that doesn’t use that many tokens. Yes, some non engineers are using Claude to vibe code, but I really doubt many are spending hundreds per month on. Even if we assume 50% of all software workers are using Claude, that comes out to $2k spend per month per Claude user. Thats 10X more than the highest tier Max subscription. So almost all of Anthropics revenue has to be API billing So the only explanation is that something like 20%+ of software engineers are not only Claude users but on API billing and regularly spending thousands per month. At $5/m Opus tokens that means the average API user has to be going through something like 25 million tokens per day. *OR* the other possibility is API revenue is heavily power law dominated. Maybe there’s just something like 100k super users who are making up the majority of the revenue. For that to work the typical super user would have to be spending on the order of $50k/month and guzzling nearly 1 billion tokens per day.
Tannor Manson@Futurenvesting

Anthropic is now showing off $44 BILLION in annual recurring revenue. This is up $14 billion (+46.6%) since last month! BULLISH for AI Infrastructure $NVDA $AMD

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Tom Chen
Tom Chen@TommayC·
@atelicinvest People who think they can do multi agent for 8 hours away never tried to play battlenet games for sc/sc2 for more than 2 hours straight.
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Unemployed Capital Allocator
Unemployed Capital Allocator@atelicinvest·
ngl man if you are using multiple agents all day long, and are getting stuff done, your brain should be absolutely fried by hour 3. there's so much high level direction setting, decision making, hallucination checking, system setting - to do. yeah sure, you might not be able to do the things you're offloading - similar to how if you use a calculator all the time, you might not be able to do 64*63-1/3 in your head anymore but ... i mean that's what the calculator is for? the activity is, for the most part, now economically not useful don't let anxiety get you
Muratcan Koylan@koylanai

Don’t outsource your thinking. Letting LLMs do your thinking is the new TikTok (or slot machine) addiction; intermittent reward, attention fragmenting across parallel streams you’re not really tracking. State management is one of the hardest problems in agent harnesses, and the moment you’re running more than three terminals at once, you’ve stopped managing agents and you’re just nudging them along while losing track of what they’re actually doing. I’d even cut it to one session. Make yourself sit with the problem before you hand it off. The reading, thinking and planning muscles returning in the first week will cause some discomfort. Slow down. Do the deep work.

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Tom Chen
Tom Chen@TommayC·
@shreyas Being self aware is more important than ever. The thing with AI is that people who are using it regularly to do things without ever attempted to have done those things manually have limited self awareness on those things.
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Shreyas Doshi
Shreyas Doshi@shreyas·
The good news: AI is making it easier than ever to acquire domain expertise and to leverage your team’s domain expertise. But you still need to *appreciate the importance of domain expertise*. This is often hard for consumer product people who spike on user empathy & creativity.
Shreyas Doshi@shreyas

Product people who have a) deep experience with consumer products *and* b) spike on user empathy & creativity find B2B products to be Easy Mode. They tend to have a high success rate with B2B products *as long as* they commit to acquiring deep domain expertise. Many don’t.

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Tom Chen
Tom Chen@TommayC·
@clairevo @lkr Loll. People who haven’t actually done it and talking out of their ass.
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claire vo 🖤
claire vo 🖤@clairevo·
@lkr I can’t think of a single huge company where this statement is actually true or practically possible unless that random employee is a sysadmin
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Laura Roeder
Laura Roeder@lkr·
it's absolutely nuts to me thinking of all these huge companies with random employees connecting claude code (or openclaw!) to the company's entire google workspace account, meanwhile no one even has any idea they're doing it
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Tom Chen
Tom Chen@TommayC·
@shreyas Don’t bank on the unlearning. Just hire 22 year olds.
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Tom Chen
Tom Chen@TommayC·
@GergelyOrosz You also don’t want the model to be sycophant. It doesn’t seem that easy to thread the needle on pushing back but also not be too arrogant about that vs their master.
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Gergely Orosz
Gergely Orosz@GergelyOrosz·
Opus 4.7 is the first model that feels like it is openly condescending towards me, as the customer with certain prompts. Whatever Anthropic did: I don't like it. If the model is condescending: I shouldn't be paying you to use it; you should be paying me! Who would have thought
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Tom Chen
Tom Chen@TommayC·
@planert41 There is now a genZ version of Asians that is also distinctly different imo.
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PPE
PPE@planert41·
This has been stuck in my head today There's a huge unappreciated generational difference between the Asian immigrants pre 1990 and post 1990 Jensen was from the generation of Asian immigrants that had to fight for every scrap they got. It's the generation that opened Chinese restaurants because they couldn't get a job. The generation of Vietnamese refugees that were high ranking officials in South Vietnam and had to work as janitors after moving to the US (true story). They're less educated, middle class at best. They learnt to do whatever it takes to survive. The newer Asian immigrants are mostly upper middle class, very well educated. These are your PHDs, professors, white collar professionals. That generation have been taught that there is a stable correct path to success. Go to college, get a grad degree, get a white collar job etc. And your job is to not fk it up and follow the path. They learnt to follow the rules. Much more important to figure out what the "right" way to do things are. And if you do them right in the right order, you'll succeed. You see this in Chinese immigrants pre Tian Nan Men vs post. The chinese restaurant owner vs the Chinese professors. So Jensen's approach of "dont think like a loser" vs Dwarkesh "but what is the correct answer" makes generational sense to me. It's the difference between the entrepreneur class (because they had to) vs academic class. It's the difference between "just do it" vs "but what is the correct way to do it" Curious if we saw this generational pattern in other immigrant groups too, like the Italians or Irish etc.
Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)@teortaxesTex

Dwarkesh and Jensen are civilized men so we didn't see *a lot* of sparks flying, but it is a profound disconnect between generations, cultures, and immigration stories. Jensen is the gangsta poster boy for American Dream. Dwarkesh is the Bay Aryan Thinkboy icon. irreconcilable

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Tom Chen
Tom Chen@TommayC·
@benitoz Agree. Peak podcast content in every way.
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Ben Pouladian
Ben Pouladian@benitoz·
Watching the takes on Jensen / Dwarkesh. Credit first: these were the best questions Jensen's been asked in a long-form sit-down. Dwarkesh didn't lob softballs. He pressed on commoditization, ASIC economics, margin compression, customer concentration. Real questions. But the consensus read that Jensen got "defensive" or didn't answer is missing what actually happened. A lot of his answers were operator clarity that only registers as evasion if you've never run the operation. "Without Anthropic, why would there be any TPU growth at all? It's 100% Anthropic. Without Anthropic, why would there be Trainium growth at all? It's 100% Anthropic" that's a CEO who has the customer concentration data on every competing silicon program and is mildly amused he has to say it out loud. The upstream supply chain answer telling supplier CEOs how big the industry would be, and them staking capacity on his word only reads as a flex if you've never had to underwrite a forecast to a supplier. It's how supply chains actually get built. The China section is where the frame gap was widest. Dwarkesh treats compute like uranium dangerous material to be controlled and withheld. Jensen treats compute like a platform propagate it, win the developers, win the stack. Two completely different theories of how American tech leadership actually works. Jensen's frame: 50% of AI developers are in China. Concede that market and you concede the standard. Win all five layers of the stack — silicon, systems, networking, software, models — on CUDA, or watch an open-source ecosystem grow on a foreign tech stack. Nvidia isn't a phone or a car. Export controls calibrated for consumer hardware misread the actual game. The gap in the interview wasn't curiosity or rigor. It was business framing. The questions kept circling "do you favor these customers" when the real mechanics are purchase orders, allocation, supply commitments, and the relationships that make any of it possible. Jensen's TSMC partnership predates most of this conversation. Hardware is hard. The scars matter. The parts worth pulling forward Token Dollar economics, supply chain prefetch, Anthropic-as-only-ASIC-customer, highest tokens-per-watt, win all five layers are operator answers to theoretical questions. The interview is better than the discourse around it. Worth the full watch.
Dwarkesh Patel@dwarkesh_sp

The Jensen Huang episode. 0:00:00 – Is Nvidia’s biggest moat its grip on scarce supply chains? 0:16:25 – Will TPUs break Nvidia’s hold on AI compute? 0:41:06 – Why doesn’t Nvidia become a hyperscaler? 0:57:36 – Should we be selling AI chips to China? 1:35:06 – Why doesn’t Nvidia make multiple different chip architectures? Look up Dwarkesh Podcast on YouTube, Apple Podcasts, Spotify, etc. Enjoy!

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Tom Chen
Tom Chen@TommayC·
@nikunj @8teAPi You can underwrite the scenario of AI automating this but you should also underwrite the scenario where black box at only 99% accuracy takes a long time to diffuse.
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Nikunj Kothari
Nikunj Kothari@nikunj·
@8teAPi At the early stages of any company, you’re mostly betting on the team, market and their unique insight. The best teams will figure it out if they are truly obsessed and will stay one step ahead regardless of competition. Betting on anything else seems like hopium.
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Tom Chen
Tom Chen@TommayC·
@nikunj @8teAPi I think folks also significantly underestimate the value of a stakeholder “knowing” the details. Let’s just say an AI system mirrors the exact slack system as diagramed. Unless you tell me it’s 100% accuracy on both, buyers/stakeholders will trust the version they understand.
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Tom Chen
Tom Chen@TommayC·
@GenAI_is_real I think his info is a few months out of date. Usually that’s not a big deal but at the current speed, think it’s actually mostly fake news.
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Chayenne Zhao
Chayenne Zhao@GenAI_is_real·
the most underrated point here is that the hiring freeze killed the information flow between companies. in normal times, every new hire brings knowledge about what tools and practices their previous company used. 18 months of zero movement means every company is operating in an information vacuum about where they actually stand on AI adoption. google thinking theyre doing fine because they enabled gemini for everyone is the same as every other company thinking theyre doing fine because they enabled copilot. nobody has a reference point anymore and thats how entire industries fall behind without realizing it @Steve_Yegge
Steve Yegge@Steve_Yegge

I was chatting with my buddy at Google, who's been a tech director there for about 20 years, about their AI adoption. Craziest convo I've had all year. The TL;DR is that Google engineering appears to have the same AI adoption footprint as John Deere, the tractor company. Most of the industry has the same internal adoption curve: 20% agentic power users, 20% outright refusers, 60% still using Cursor or equivalent chat tool. It turns out Google has this curve too. But why is Google so... average? How is it that a handful of companies are taking off like a spaceship, and the rest, including Google, are mired in inaction? My buddy's observation was key here: There has been an industry-wide hiring freeze for 18+ months, during which time nobody has been moving jobs. So there are no clued-in people coming in from the outside to tell Google how far behind they are, how utterly mediocre they have become as an eng org. He says the problem is that they can't use Claude Code because it's the enemy, and Gemini has never been good enough to capture people's workflows like Claude has, so basically agentic coding just never really took off inside Google. They're all just plodding along, completely oblivious to what's happening out there right now. Not only is Google not able to do anything about it, they don't seem to be aware of the problem at all. I'm having major flashbacks to fifty years ago as a kid at the La Brea Tar Pits, asking, "why can't they just climb out?" My Google friend and I had this conversation over a month ago. I didn't share it because I wanted to look around a bit, and see if it's really as bad as all that. I've been talking to people from dozens of companies since then. And yeah. It's as bad as all that. Google is about average. Some companies at the bottom have near-zero AI adoption and can't even get budget for AI. They may have moats and high walls, but the horde is coming for them all the same. And then there are a few companies I've met recently who are *amazingly* leaned in to AI adoption. One category-leader company just cancelled IntelliJ for a thousand engineers. That's an incredibly bold move, one of many they're making towards agentic adoption. In my opinion, that company is setting themselves up for a _huge_ W. As for the rest, well, it's the Great Siloing. Everyone's flying blind. With nobody moving companies, no company knows where they stand on the AI adoption curve. Nobody knows how they're doing compared to everyone else. Half of them just check a box: "We enabled {Copilot/Cursor} for everyone!" Cue smug celebrations. They think this is like getting SOC2 compliance, just a thing they turn on and now it's "solved." And they don't realize that they've done effectively nothing at all. All because of a hiring freeze.

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Tom Chen
Tom Chen@TommayC·
@bcherny @zeeg Claude cowork has way more. In comparison, going back to Claude code actually shows how much better it is in comparison
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Boris Cherny
Boris Cherny@bcherny·
@zeeg What bugs are you hitting? Here to help
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David Cramer
David Cramer@zeeg·
anthropic being down, rate limits, etc is understandable. huge hardware reqs and insane growth. claude code being bug filled is just a result of people vibe coding slop at anthropic and accepting it as ok. it is not ok you will lose your customers just as fast as you've gained them.
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Tom Chen
Tom Chen@TommayC·
@Roy_Wainer @buccocapital I think this is becasue as of now, the incumbents are critical to any of the agents working. No one is interested in doing migrations when their mindshare is on trying to deploy agents.
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Roy Wainer
Roy Wainer@Roy_Wainer·
Great post, but one comment - you said that since August there have been no new bull cases, only more bear cases. I think there is one strong bull case: the disruption just doesn’t show up in the numbers. We saw Q3 reports and nothing showed up. Then we said, okay, maybe we’ll see it in Q4, but still nothing showed up. Every company was pretty much in the same revenue direction as before: Oracle, Microsoft, Now, CRM, Hubs, even Adobe…and I’m not even talking about the vertical guys, or cyber, or data. And that’s bullish, because it shows that even if people are right about the potential disruption, it will be much slower than they believe. Enterprise software is…very sticky. I don’t think I’m telling you anything you don’t know, but I think that’s the biggest bull case. And every quarter that passes and these companies still grow, so does their FCF. Will they know what to do with it? That’s another question, but some, at least those with small SBC %, are starting to look interesting for value investors
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BuccoCapital Bloke
BuccoCapital Bloke@buccocapital·
New format - ripped this one off the cuff Checking In On The SaaS Bear Case(s): Dispatches from another red day Link below
BuccoCapital Bloke tweet media
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