@TheStalwart The simplest answer here is that it's probably not in the training dataset of the frontier labs yet - when it is, they'll probably get better. This is the whole jagged intelligence idea.
Good list to see everything that shipped, but putting dispatch in D tier (while missing channels entirely?) and putting Computer use in C tier is criminal.
They are both actual game changers. Auto mode should be nowhere close to S tier.
Anthropic shipped 120+ features in 90 days across Claude Code, Cowork, and Claude.
I ranked every single one.
S tier, A tier, B tier, C tier, D tier. What to adopt now, what to skip, and 4 workflows that chain them together:
🔗 https://t.co/U7YICGUXSV
@TheStalwart@tracyalloway@heyitsnoah Was listening to the pod and one thing that stood out to me was the confusion between Tracy's question about memory notes (something chatGPT web does) and file writing for Claude code and compaction. I feel like you guys should actually talk to @bcherny for way more deets!
Claude Code with Opus 4.5 is a watershed moment, moving software creation from an artisanal, craftsman activity to a true industrial process.
It’s the Gutenberg press. The sewing machine. The photo camera.
@NateSilver538@TheStalwart FWIW - I think these are active decisions made inside the big frontier model labs all the time - datasets for things like Coding, Math, Music, Writing, Quant skills are high ROI to add. biz/co will pay for them. Poker, Chess, Pokemon etc aren't, but you could be pretty easily.
@NateSilver538@TheStalwart I have a different take on this - LLMs are smart over what they've seen before. Poker/chess just aren't dedicated datasets for training frontier models yet. If someone took the corpus of all hist games + annot. for a good/bad plays, fed it into pre-training, perf would 🚀
Can one of the VCs in SF pls fund an internet company that provides good Internet and half decent service?
AT&T and Xfinity cannot be the best of what Silicon Valley has to offer. It's not venture scale; it won't make $$$, but pls do it anyway, just for for the love of the game.
What do you folks use to organize knowledge in 2025?
I consume a bunch of media - blogs, podcasts, news articles, tweets/threads etc etc.
Tell me what systems/tools work for you - anything from handwritten notes, to a personal obsidian, NotebookLLM - anything you actually use
Terminal rendering magic is very archaic and probably one of the less understood/used/loved for UI systems today - I find it a bit funny, but if not for claude code it would likely have stayed that way.
We’ve rewritten Claude Code’s terminal rendering system to reduce flickering by roughly 85%.
We wanted to share more about why this was so difficult, how the fix works and how we used Claude Code to fix it 🧵
A new product, a new customer, a new financing!
Introducing Superpower: a 42MW natural gas turbine optimized for AI datacenters, built on our supersonic technology. Superpower launches with a 1.21GW order from @CrusoeAI Backstory 🧵👇
🔥 Today we’re excited to announce new funding for `grep` (at a $1.3B valuation) to continue building the foundation of agent observability and text search infrastructure.
grep began as a humble UNIX utility in 1973. Since then, it’s evolved—through recursive innovation and the rise of ripgrep—into a core platform for developers, sysadmins, and agents. Our tools now power engineering and AI teams across @OpenAI, @Anthropic, @Meta, @Cloudflare, @Replit, @NASA, and thousands more.
Over the decades we’ve iterated from grep to `egrep` to `ripgrep`. Our goal has always been to figure out what intelligent agents of the future need to see, filter, and extract—and then build the tools that make that possible.
While our journey is still just beginning, we also want to take a moment to reflect on how the space (and our role in it) has evolved. You can read our reflections and details on this funding milestone here:
https://t.co/um8zFkOqDI
We also share more about the funding that will power our future there. Thank you to @IVP, @Benchmark, @Sequoia, @CapitalG, and the open-source community for their belief in the enduring power of regex.
What excites us most today is what’s next:
grep 5.0 with AI-assisted pattern synthesis
ripgrep Cloud, bringing distributed search to agent clusters
pgrepGPT, an agent-native process discovery layer
And new no-code integrations for autonomous observability pipelines
We’re in the midst of a transformation in computation itself. grep and ripgrep will remain at the core—helping humans and agents alike find what matters, faster.
@signulll No, if you do that - you announce to every enterprise customer that they will lose their business suite if they compete with Google in any market it cares about, there's no faster way to send customers running. The GSuite doesn't have the leverage, there's Oficce356 etc.
@GergelyOrosz Yes, but Grafana also sucks - it's what everyone is forced to use when they can't get something better. You need your observability tools to be mostly turn key and grafana just isn't.