Paul Dix retweeted
More than a dozen flight tests and years of development, with countless hours worked by SpaceX engineers and technicians, all come down to this: the first orbital Starship launch carrying advanced Starlink satellites bound for space.
Watch “Go For Orbit” and experience the he most ambitious Starship mission yet
Watch “Go For Orbit” and experience the he most ambitious Starship mission yet
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It's becoming clear that not only are software factories possible, they're very productive and are just a step on the path to making any software product recursively self-improving. As the models improve, so should your automation, leading to RSI software: pauldix.com/the-software-f…
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I don't think we should fight. The two companies are complementary. Since you're not doing this AI stuff, I really think Snowflake should consider getting its AI tokens through Databricks. You can get both cheap OSS models as well as frontier (OAI/Ant/Gemini/Grok) models from our platform. It all goes through Unity Gateway which has Smart Routing, Budgets, and Access Control. You can even use Omnigent with any harness, including CoCo. Most of our customers used this to reduce token spend ~30% last few months while token count went up. Genie lets you then track, control, manage that spend, all your financials, marketing, etc. Quick POC?
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Haha yesssss. It’s my favorite GH project README ever. @arewenotmen is a programmer comic genius
Still my favorite project on github: github.com/nodanaonlyzuul…....
I just heard the thunder of @pauldix in an old project; it never gets old
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I think for software engineers, your ability to effectively communicate with other humans is about to go up in value by a significant amount. The job is becoming mostly about refining a mass of agent work, iteration and output into something understandable by your colleagues.
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lol, the last line. Gotta start talking to my clankers like this
I know I've been prompting my agents correctly when they present interfaces at the grammar, noun, and verb level. Took a lot of skill crafting to get here but god it's refreshing to work at the correct abstraction level and not like "my brother in christ why is this a modal?"
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It's getting real out there. Workgroups to interpret and understand the results AI is producing.
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory).
AI starting to help us improve our understanding of the universe! openai.com/index/building…
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My take from the Anthropic S1 today is that they are no longer reading all their code. Even for the engineers directing AIs to create it, they're not reading every line. This should be obvious to everyone by now, but I suspect some engineers are still in denial.
Two direct quotes lead me to this: "over 90% of the contributions to our codebase in September 2026 were written by Claude." and "the average daily volume of code contributed to our codebase per engineer in the three months ended September 30, 2026 was over 45 times the average daily volume in the year ended December 31, 2024."
For a company with some of the best engineers on the planet, they're creating 45x the volume from before. I guarantee you they can't actually read all of that.
You have to pull the humans up to a higher level of abstraction to get that kind of velocity.
Two direct quotes lead me to this: "over 90% of the contributions to our codebase in September 2026 were written by Claude." and "the average daily volume of code contributed to our codebase per engineer in the three months ended September 30, 2026 was over 45 times the average daily volume in the year ended December 31, 2024."
For a company with some of the best engineers on the planet, they're creating 45x the volume from before. I guarantee you they can't actually read all of that.
You have to pull the humans up to a higher level of abstraction to get that kind of velocity.
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I was inspired to write a personal post about getting my start in tech. I can't imagine what it would be like if I had AI at my fingertips back then, but I'm certain I would have gotten farther, faster. pauldix.com/ai-is-the-grea…
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Paul Dix retweeted
Up to 8x faster point queries with @ApacheDataFusio with the right tuning: datafusion.apache.org/blog/2026/10/2…
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Great stuff
I built bbtree, the foundation of databases and filesystems, and the fastest concurrent btree.
Code: github.com/XiangpengHao/b…
Blog post & demo: bbtree.xiangpeng.systems
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It’s getting wild out there. Gotta have an always on agent security force.
Over the past several months, we have substantially hardened the security of our research training environment. We’ve removed live internet access for all frontier models during training and built an offline world for them to use instead—a cached version of the web where they can still learn to browse, search, and use applications.
On September 20, after a model exploited a DNS misconfiguration to find a way outside of this offline world, we paused frontier training to strengthen containment further. We assembled teams of agents, powered by our most cyber-capable models, and tasked them with finding weaknesses in our research environments.
While they found no route to the internet they could easily exploit while concealing their activity from our monitors, they did find zero-day vulnerabilities, virtual machine escapes, and hardware side-channels for communication between agents. We used their discoveries to further strengthen our defenses and contribute fixes to open-source software.
After strengthening our containment architecture, we resumed our frontier RL training and inference on October 1. We’ve reserved substantial compute for continuous red-teaming, and made high-compute red-teaming part of the safety cases we use to decide whether frontier training and evaluation can proceed securely.
openai.com/index/securing…
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Agree with Parker on this. Not useful to juice your top line revenue by subsidizing tokens just so you can hit your next fundraise. You're setting up for a big fall later when it all comes due.
Many fell into this trap in the big data/infrastructure game. Subsidize the cloud infra costs (which scale linearly with customer usage, like tokens) to sign up customers and then find a little ways down the road that you're operating a low margin/negative margin business that you really can't just optimize your way out of.
I have a bit of lived experience with some parts of this.
Many fell into this trap in the big data/infrastructure game. Subsidize the cloud infra costs (which scale linearly with customer usage, like tokens) to sign up customers and then find a little ways down the road that you're operating a low margin/negative margin business that you really can't just optimize your way out of.
I have a bit of lived experience with some parts of this.
With respect, this is terrible advice. You need to prove -- to yourself more so than to investors -- that intelligence is more valuable inside your product, than on top.
If tokens *aren't* worth 4X inside your product, what are you even doing? You're just reselling the labs. 1/
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Good follow up from Christina:
Hi Parker. You and I might disagree on other things, but I don't think we disagree on this (eg see this other excerpt from the same interview.)
Gross margin is good! We are in a strange era right now where investors encourage trading off gross margin for incremental growth; I suspect that wit lasted, in the history of software investing?)
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I found this to be an amazing read: anthropic.com/engineering/re….
It points to the future of software engineering. Anthropic has the unique position of an unlimited token budget with the best frontier models. I think the rest of us peasants will likely have this kind of capability within a reasonable budget by this time next year.
The trick is to create an SDLC that enables this kind of work.
It points to the future of software engineering. Anthropic has the unique position of an unlimited token budget with the best frontier models. I think the rest of us peasants will likely have this kind of capability within a reasonable budget by this time next year.
The trick is to create an SDLC that enables this kind of work.
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We've released @InfluxDB 3.12! The big add is distributed compaction in beta in Enterprise. This allows operators to dynamically scale a cluster's compaction resources up and down in smaller increments with more VMs, rather than just scaling vertically.
We also made bulk Parquet imports roughly 3x faster by doing more work in parallel, added optional per-database schema enforcement, and made RBAC generally available.
influxdata.com/blog/whats-new…
We also made bulk Parquet imports roughly 3x faster by doing more work in parallel, added optional per-database schema enforcement, and made RBAC generally available.
influxdata.com/blog/whats-new…
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And it seems the post URL changed, so here it is again: influxdata.com/blog/influxdb-…
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