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AkhenOsiris
Here are the results of the survey in order of how they were shared onstage:
What will be OpenAI’s annualized revenue be at the end of 2026?
Median answer: $30 billion.
What will Nvidia be worth at the end of 2026?
Median answer: $6 trillion.
What year will an independent committee of experts, as dictated by the Microsoft-OpenAI agreement, declare that we have reached AGI?
Top answer: 2030
Which venture capital firm’s AI portfolio are you the most jealous of?
The top three most voted for, from first to last: Andreessen Horowitz, Khosla Ventures, and Sequoia.
If you could put money in any private technology companies today, what would they be?
Top five companies in order from first to last: Anthropic, OpenAI, Cursor, Anduril, SpaceX, and OpenEvidence.
What global company’s model will top the LMArena web development leaderboard at the end of 2026?
In order from first to last: OpenAI, Anthropic, Gemini, Grok, Qwen.
If you could short a $1 billion-plus valuation startup, which would it be?
First place was Perplexity. Second place went to OpenAI. Other names shown onstage: Cursor, Figure, Harvey, Mercor, Mistral, and Thinking Machines.
What stood out to me from these results (Newcomer has also published the full slides for his paying subscribers):
A softening on OpenAI: Given that Sam Altman has said OpenAI plans to end this year with $20 billion of annualized revenue, this group of AI insiders doesn’t expect next year to be as exponential for the business as the leap from 2024 to 2025. The prediction that AGI won’t be declared until 2030 suggests a lack of faith in model progress meaningfully improving in the near term, although that answer could also be clouded by the complexity of how OpenAI and Microsoft must settle on how it’s decided. (I’m still waiting for either company to share information on who its “independent committee of experts” will be and how they’ll decide.) It was also notable that more attendees wanted to buy Anthropic stock than OpenAI’s, despite the consensus being that OpenAI would lead LMArena next year.
From Newcomer's Summit, as posted by Heath at Sources:
https://t.co/oPNe9NFAI3
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Here are the results of the survey in order of how they were shared onstage:
What will be OpenAI’s annualized revenue be at the end of 2026?
Median answer: $30 billion.
What will Nvidia be worth at the end of 2026?
Median answer: $6 trillion.
What year will an independent committee of experts, as dictated by the Microsoft-OpenAI agreement, declare that we have reached AGI?
Top answer: 2030
Which venture capital firm’s AI portfolio are you the most jealous of?
The top three most voted for, from first to last: Andreessen Horowitz, Khosla Ventures, and Sequoia.
If you could put money in any private technology companies today, what would they be?
Top five companies in order from first to last: Anthropic, OpenAI, Cursor, Anduril, SpaceX, and OpenEvidence.
What global company’s model will top the LMArena web development leaderboard at the end of 2026?
In order from first to last: OpenAI, Anthropic, Gemini, Grok, Qwen.
If you could short a $1 billion-plus valuation startup, which would it be?
First place was Perplexity. Second place went to OpenAI. Other names shown onstage: Cursor, Figure, Harvey, Mercor, Mistral, and Thinking Machines.
What stood out to me from these results (Newcomer has also published the full slides for his paying subscribers):
A softening on OpenAI: Given that Sam Altman has said OpenAI plans to end this year with $20 billion of annualized revenue, this group of AI insiders doesn’t expect next year to be as exponential for the business as the leap from 2024 to 2025. The prediction that AGI won’t be declared until 2030 suggests a lack of faith in model progress meaningfully improving in the near term, although that answer could also be clouded by the complexity of how OpenAI and Microsoft must settle on how it’s decided. (I’m still waiting for either company to share information on who its “independent committee of experts” will be and how they’ll decide.) It was also notable that more attendees wanted to buy Anthropic stock than OpenAI’s, despite the consensus being that OpenAI would lead LMArena next year.
From Newcomer's Summit, as posted by Heath at Sources:
https://t.co/oPNe9NFAI3
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Offshore
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AkhenOsiris
$DASH
Deductive's system builds what the company calls a "knowledge graph" that maps relationships across codebases, telemetry data, engineering discussions, and internal documentation. When an incident occurs, multiple AI agents work together to form hypotheses, test them against live system evidence, and converge on a root cause — mimicking the investigative workflow of experienced site reliability engineers, but completing the process in minutes rather than hours.
The technology has already shown measurable impact at some of the world's most demanding production environments. DoorDash's advertising platform, which runs real-time auctions that must complete in under 100 milliseconds, has integrated Deductive into its incident response workflow. The company has set an ambitious 2026 goal of resolving production incidents within 10 minutes.
"Our Ads Platform operates at a pace where manual, slow-moving investigations are no longer viable. Every minute of downtime directly affects company revenue," said Shahrooz Ansari, Senior Director of Engineering at DoorDash, in an interview with VentureBeat. "Deductive has become a critical extension of our team, rapidly synthesizing signals across dozens of services and surfacing the insights that matter—within minutes."
Deductive has root-caused approximately 100 production incidents at DoorDash over the past few months, with its accuracy improving with each investigation. For an organization of DoorDash's size, the company estimates this will translate to more than 1,000 hours of annual engineering productivity savings, with an estimated full revenue impact "in millions of dollars," according to Ansari. At location intelligence company Foursquare, Deductive reduced the time to diagnose Apache Spark job failures by 90% —t urning a process that previously took hours or days into one that completes in under 10 minutes — while generating over $275,000 in annual savings.
https://t.co/D0CWM25NT0
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$DASH
Deductive's system builds what the company calls a "knowledge graph" that maps relationships across codebases, telemetry data, engineering discussions, and internal documentation. When an incident occurs, multiple AI agents work together to form hypotheses, test them against live system evidence, and converge on a root cause — mimicking the investigative workflow of experienced site reliability engineers, but completing the process in minutes rather than hours.
The technology has already shown measurable impact at some of the world's most demanding production environments. DoorDash's advertising platform, which runs real-time auctions that must complete in under 100 milliseconds, has integrated Deductive into its incident response workflow. The company has set an ambitious 2026 goal of resolving production incidents within 10 minutes.
"Our Ads Platform operates at a pace where manual, slow-moving investigations are no longer viable. Every minute of downtime directly affects company revenue," said Shahrooz Ansari, Senior Director of Engineering at DoorDash, in an interview with VentureBeat. "Deductive has become a critical extension of our team, rapidly synthesizing signals across dozens of services and surfacing the insights that matter—within minutes."
Deductive has root-caused approximately 100 production incidents at DoorDash over the past few months, with its accuracy improving with each investigation. For an organization of DoorDash's size, the company estimates this will translate to more than 1,000 hours of annual engineering productivity savings, with an estimated full revenue impact "in millions of dollars," according to Ansari. At location intelligence company Foursquare, Deductive reduced the time to diagnose Apache Spark job failures by 90% —t urning a process that previously took hours or days into one that completes in under 10 minutes — while generating over $275,000 in annual savings.
https://t.co/D0CWM25NT0
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Dimitry Nakhla | Babylon Capital®
Berkshire Hathaway adds one new position:
$GOOGL $GOOG
Small allocation, still nice to see https://t.co/PUEGoyhN0a
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Berkshire Hathaway adds one new position:
$GOOGL $GOOG
Small allocation, still nice to see https://t.co/PUEGoyhN0a
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Quiver Quantitative
BREAKING: Warren Buffet's Berkshire Hathaway just filed a portfolio update.
They opened a new $4.3B position in Google, $GOOG.
Full holdings up on Quiver, link below. https://t.co/RoJTmS5xhJ
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BREAKING: Warren Buffet's Berkshire Hathaway just filed a portfolio update.
They opened a new $4.3B position in Google, $GOOG.
Full holdings up on Quiver, link below. https://t.co/RoJTmS5xhJ
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App Economy Insights
Berkshire just added $GOOGL to its portfolio.
A new $4.3B position (1.6% allocation). https://t.co/vnQN1WAaQj
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Berkshire just added $GOOGL to its portfolio.
A new $4.3B position (1.6% allocation). https://t.co/vnQN1WAaQj
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Finding Compounders
Lecture by Costco co- founder and former CEO Jim Sinegal https://t.co/xnRlX9PK7B
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Lecture by Costco co- founder and former CEO Jim Sinegal https://t.co/xnRlX9PK7B
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EndGame Macro
A Move Born Out of Fog
The drop in the 10 year this morning wasn’t sparked by new inflation data or a surprise consumer report, there was no data. The government shutdown delayed everything, so traders walked into the day without the usual morning anchors. When markets have no numbers to react to, they start trading the atmosphere. And the atmosphere lately has been…
“The Fed is easing, QT is ending soon, and maybe the economy is softer than we thought.”
With no fresh information to contradict that story and with thin early trading you got a drift lower in yields from around 4.12% into the low 4.07s. It wasn’t conviction. It was speculation filling a vacuum. The front end of the curve is already adjusting to a world where QT is basically done, and some folks briefly pushed the idea that the long end might follow.
A Shift in Rate Cut Expectations
At the same time, odds of a December rate cut quietly slipped. You could see it in Fed funds futures and the prediction markets, enough to show that traders were becoming less sure the Fed would cut again this year. That shift created tension..the early morning buying in bonds was based on “maybe we still get another cut,” while the broader pricing was slowly saying, “actually, maybe we don’t.”
The key is that both things, the brief rally in the 10 year and the rise in no cut probabilities were signs of the same uncertainty. The market was trying to feel out where policy expectations really sat now that QT is ending but the economy isn’t offering clean signals.
Reality Reasserts Itself
Once the initial drift lower ran out of emotional steam, reality stepped back in. Nothing in the fundamental landscape had changed…
•Treasury is still issuing aggressively
•The TGA is hovering near $950 billion
•Bank reserves haven’t recovered
•Services inflation is easing, but slowly
•QT hasn’t formally ended yet
There was no new catalyst to keep long yields down. So the move snapped back. Dealers hedged into supply. Macro funds reset their shorts. Real money accounts waited for better levels. And yields went right back above where they started, finishing closer to 4.14%.
The Simple Read
Today wasn’t about a hidden data release or a big macro surprise. It was the market feeling around in a data vacuum, testing an idea in the morning, then discarding it when nothing supported it. The reversal wasn’t dramatic; it was the tape settling back into the reality of supply, deficits, and a Fed that may be done cutting for now.
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A Move Born Out of Fog
The drop in the 10 year this morning wasn’t sparked by new inflation data or a surprise consumer report, there was no data. The government shutdown delayed everything, so traders walked into the day without the usual morning anchors. When markets have no numbers to react to, they start trading the atmosphere. And the atmosphere lately has been…
“The Fed is easing, QT is ending soon, and maybe the economy is softer than we thought.”
With no fresh information to contradict that story and with thin early trading you got a drift lower in yields from around 4.12% into the low 4.07s. It wasn’t conviction. It was speculation filling a vacuum. The front end of the curve is already adjusting to a world where QT is basically done, and some folks briefly pushed the idea that the long end might follow.
A Shift in Rate Cut Expectations
At the same time, odds of a December rate cut quietly slipped. You could see it in Fed funds futures and the prediction markets, enough to show that traders were becoming less sure the Fed would cut again this year. That shift created tension..the early morning buying in bonds was based on “maybe we still get another cut,” while the broader pricing was slowly saying, “actually, maybe we don’t.”
The key is that both things, the brief rally in the 10 year and the rise in no cut probabilities were signs of the same uncertainty. The market was trying to feel out where policy expectations really sat now that QT is ending but the economy isn’t offering clean signals.
Reality Reasserts Itself
Once the initial drift lower ran out of emotional steam, reality stepped back in. Nothing in the fundamental landscape had changed…
•Treasury is still issuing aggressively
•The TGA is hovering near $950 billion
•Bank reserves haven’t recovered
•Services inflation is easing, but slowly
•QT hasn’t formally ended yet
There was no new catalyst to keep long yields down. So the move snapped back. Dealers hedged into supply. Macro funds reset their shorts. Real money accounts waited for better levels. And yields went right back above where they started, finishing closer to 4.14%.
The Simple Read
Today wasn’t about a hidden data release or a big macro surprise. It was the market feeling around in a data vacuum, testing an idea in the morning, then discarding it when nothing supported it. The reversal wasn’t dramatic; it was the tape settling back into the reality of supply, deficits, and a Fed that may be done cutting for now.
And now 10Y yield at session high https://t.co/QvB3Fu5vTj tweet