For the many who claim to be contrarian or first principles investors
$now $shop $snow
All caught up in the “SaaSpocolypse” rerating and drawdown
Yet all are showing signs of AI tailwinds, as opposed to the inverse
Who has the courage to stay near-term “wrong” longterm right?
Software stocks this year:
Intuit: -52%
Asana: -51%
HubSpot: -50%
Atlassian: -47%
Monday: -46%
Workday: -40%
Figma: -39%
Duolingo: -38%
Bill: -34%
UIPath: -33%
ServiceNow: -33%
Salesforce: -32%
Adobe: -30%
GitLab: -29%
Docusign: -28%
SAP: -27%
Freshworks: -26%
Snowflake: -22%
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market still pricing SaaS like AI kills all software.
Reality: AI kills weak SaaS, but strengthens the platforms that own distribution + mission-critical workflows.
$SHOP and $SNOW becoming even more attractive.
Josh Kushner just bet $100M on Shopify.
smart money will follow
The market is pricing SaaS like AI kills it
Reality: AI kills weak (most) SaaS but supercharges the ones that own workflows, data, & transactions.
NOW, SHOP, DDOG are not getting replaced—they’re where AI actually runs
That disconnect = one of the best entry points in years
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The market is pricing SaaS like AI kills it
Reality: AI kills weak (most) SaaS but supercharges the ones that own workflows, data, & transactions.
NOW, SHOP, DDOG are not getting replaced—they’re where AI actually runs
That disconnect = one of the best entry points in years
I would have expected the market to start discerning between SaaS that is impacted by AI, SaaS that needs to evolve, and SaaS that benefits from AI. Analytical SaaS, Creative SaaS is in category 1, System or Record, Human workflow and Engagement and Productivity are in category 2 and Infrastructure SaaS and Cybersecurity are in 3. This constant paranoid reaction of the market will continue to create buying opportunities for the discerning.
No one should ever resort to violence + this should never happen
Unrelated and separately
“[Proud at] how much I held the line on not being willing to agree to the unilateral control he wanted over OpenAI”
So you’re proud you kept @elonmusk from keeping openai …open 😂
I wrote this early this morning and I wasn't sure if I would actually publish it, but here it is:
blog.samaltman.com/2279512
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Overstated IMHO
Switching costs are 0
Across our 2 dozen devs:
CC for heavy lifting / refactors / multi-file reasoning
Cursor for inline edits, navigation, fast iteration
Codex for debugging, edge cases, or second opinions
This is tool-stacking, not platform abandonment.
Every single dev and product team I speak to in the last 30 days has moved from Cursor to Claude Code.
1. Is this permanent?
2. If so, what happens to Cursor?
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We have subs to every tool you can name at Zaigo
Manus is the most breathtaking and valuable platform that has come out since 2022. Truly remarkable
(And we have 15 claude code licenses + cursor + Ralph jamming autonomously for hours)
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Agree w Miles.
But invert the logic
Public SaaS has already eaten the pain — now it gets the AI upside.
Private markets are still digesting fantasy marks
Interesting time to quietly buy the Shopifys and other large SaaS companies getting more efficient with AI…
💯💯
TL;DR: Nvidia is procuring / locking up *inference* — which now is 2 jobs:
• Prefill = loading big context (needs lots of memory)
• Decode = generating tokens fast (needs ultra-low latency)
GPUs are great at the 1st. Groq’s SRAM, the 2nd
So this reinforces $nvda ‘s stack
Nvidia is buying Groq for two reasons imo.
1) Inference is disaggregating into prefill and decode. SRAM architectures have unique advantages in decode for workloads where performance is primarily a function of memory bandwidth. Rubin CPX, Rubin and the putative “Rubin SRAM” variant derived from Groq should give Nvidia the ability to mix and match chips to create the optimal balance of performance vs. cost for each workload. Rubin CPX is optimized for massive context windows during prefill as a result of super high memory capacity with its relatively low bandwidth GDDR DRAM. Rubin is the workhorse for training and high density, batched inference workloads with its HBM DRAM striking a balance between memory bandwidth and capacity. The Groq-derived "Rubin SRAM" is optimized for ultra-low latency agentic reasoning inference workloads as a result of SRAM’s extremely high memory bandwidth at the cost of lower memory capacity. In the latter case, either CPX or the normal Rubin will likely be used for prefill.
2) It has been clear for a long time that SRAM architectures can hit token per second metrics much higher than GPUs, TPUs or any ASIC that we have yet seen. Extremely low latency per individual user at the expense of throughput per dollar. It was less clear 18 months ago whether end users were willing to pay for this speed (SRAM more expensive per token due to much smaller batch sizes). It is now abundantly clear from Cerebras and Groq’s recent results that users are willing to pay for speed.
Increases my confidence that all ASICs except TPU, AI5 and Trainium will eventually be canceled. Good luck competing with the 3 Rubin variants and multiple associated networking chips. Although it does sound like OpenAI’s ASIC will be surprisingly good (much better than the Meta and Microsoft ASICs).
Let’s see what AMD does. Intel already moving in this direction (they have a prefill optimized SKU and purchased SambaNova, which was the weakest SRAM competitor). Kinda funny that Meta bought Rivos.
And Cerebras, where I am biased, is now in a very interesting and highly strategic position as the last (per public knowledge) independent SRAM player that was ahead of Groq on all public benchmarks. Groq’s “many chip” rack architecture, however, was much easier to integrate with Nvidia’s networking stack and perhaps even within a single rack while Cerebras’s WSE almost has to be an independent rack.
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Super worthwhile thread @ttunguz
This one-pager is related to the hyperscaler shenanigans Tomasz mentioned in his tweetstorm
Would make for an interesting discussion @InvestLikeBest @BG2Pod @theallinpod
Nvidia just committed $110B in vendor financing—85% of annual revenue. Lucent's playbook in 2000? 20%. Is this the telecom bubble all over again? I analyzed the numbers. Thread 🧵
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Replying to @jjen_abel
@jjen_abel curious if you agree with this?
We built this internally for my own biz and has been a gamechanger. But maybe not for everyone?
spend enough time in sales and you realize
it’s seldom taught
best sales folks have no idea how they do what they do
it’s art
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Could be
But the part left out:
expensive robot rollout capex eats cash behind closed doors
…while union backlash (which makes for great headline news) hits in public
That’s a tricky storm to weather
$amzn will lay off tens of thousands of factory workers and drivers in the next five years, replacing them with robots and @zoox delivery trucks
margins will be bananas, giving them the ability to drop their already absurdly low prices and increase consumption
in ten years they will be able to be "lights out" in their delivery facilities -- 100% automation -- if they choose to.
Their stock will beat the market by 3x+ in next decade
I am very long
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Replying to @altcap
@altcap you did Bill dirty with the cover photo for ep 35!!! 😭😭
Also,
the end of the episode with the:
“Sunny’s gonna raise” comment was the best ever moment in 35 (very good) episodes 😂😂
Cc @BG2Pod @bgurley
As discussed on @BG2Pod, you should expect to see Western companies embrace the "open" AI eco-system. They will get the same benefits of this that the Chinese players do. Will be super-disruptive. Watch this space. Follow @drishanarora and @DeepCogito.
youtube.com/watch?v=fTqINzeu…
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Replying to @BudElliott3
@BudElliott3 the theory holds. A fascinating data point.
The below is summarizing 247 rankings (since its inception) graded against NFL draft outcomes. No 5 *to 3*s have ever made your crootin ratings look dumb
For all the recruiting nerds and personnel people who follow me, let's crowd source this:
Can you think of any QB who had a serious drop in the recruiting rankings and then played up to his initial high rating?
Have about 20 examples of kids who grow early, get rated highly as sophomores, get dropped and then bust in college.
But what about the reverse? Any QBs who made the recruiting industry look bad for a big drop?
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replace “the internet” with “frontier AI models” …
…and it’s maybe an order or magnitude greater across all 3?
This quoted post is unavailable.
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A good, albeit dated list (probably more apt during the decade+ long SaaS/☁️ era)
As companies pivot from the recurring, seat-based model to usage based…
…the highest quality revenue is sticky due to a GTM motions and/or product(s) with unassailable moats
This quoted post is unavailable.
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The more things change…
Stay long and overweight on all of those names
Btw - $NVDA will be the 1st $5 trillion co. late 2026 (barring macro shocks or some bs regulatory constraints)
And … i’ll say the 1st ever $10T company and gets there by 2030
Runawaytrain
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Blown away by Caryn — totally inspiring.
Top 1% CEO talent.
One of your best ever EPs @patrick_oshag
Caryn Seidman-Becker (@CLEARcaryn)…
• Built a successful hedge fund and was inspired by investing in Amazon, Apple, and Priceline
• then bought CLEAR for $6M out of bankruptcy and rebuilt it from scratch
• Envisioned CLEAR not just as a travel tool, but a universal identity platform
• Rebuilt software, tracked down old hardware, and relaunched in Orlando with no salary for 5 years
• Bootstrapped to profitability
• Once told a skeptical VC: "Because I'm a complete f*cking animal" when asked why she could be CEO
• Pioneered face-first biometric tech (NV) — 5x faster than previous methods
• Expanded CLEAR beyond airports into sports stadiums, healthcare, and digital identity
• Left finance because she didn’t want her tombstone to say she just picked good stocks.
I loved this conversation — including some very honest and raw elements about loss. And I too think Caryn is a complete f*cking animal, and the best kind.
Timestamps
0:00 Intro
0:54 The Vision for Clear
2:58 Lessons from Wall Street
4:38 The Journey of Clear
7:53 The Acquisition Story
10:11 The Power of Biometrics
13:55 Launching Clear 2.0
18:30 Challenges and Innovations
21:41 Public-Private Partnerships
25:44 The Future of Travel
37:03 Action vs. Thinking
41:10 Business Model and Financing
47:03 Public-Private Partnerships & Airport Innovations
52:05 The Importance of Free Cash Flow
55:20 Biometrics and Privacy Concerns
1:00:45 Expanding Business Horizons
1:05:46 Personal Challenges and Leadership
1:09:52 Genetic Screening and Health Advocacy
1:15:43 Leadership Qualities and Company Building
1:27:00 Future Innovations and Opportunities
1:30:58 The Kindest Thing






















