Offshore
Photo
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
tweet
$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
tweet
Offshore
Photo
Dimitry Nakhla | Babylon Capital®
Berkshire Hathaway adds one new position:
$GOOGL $GOOG
Small allocation, still nice to see https://t.co/PUEGoyhN0a
tweet
Berkshire Hathaway adds one new position:
$GOOGL $GOOG
Small allocation, still nice to see https://t.co/PUEGoyhN0a
tweet
Offshore
Photo
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
tweet
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
tweet
Offshore
Photo
App Economy Insights
Berkshire just added $GOOGL to its portfolio.
A new $4.3B position (1.6% allocation). https://t.co/vnQN1WAaQj
tweet
Berkshire just added $GOOGL to its portfolio.
A new $4.3B position (1.6% allocation). https://t.co/vnQN1WAaQj
tweet
Offshore
Photo
Finding Compounders
Lecture by Costco co- founder and former CEO Jim Sinegal https://t.co/xnRlX9PK7B
tweet
Lecture by Costco co- founder and former CEO Jim Sinegal https://t.co/xnRlX9PK7B
tweet
Offshore
Photo
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.
tweet
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