a human passionate about coding agents

Joined November 2010
Shao retweeted
No one changes the world alone Introducing Ampersand - the first model built for us. Ampersand is a collaborator trained to help people achieve their individual and collective goals. In multi-month simulations, users collaborating with Ampersand accomplished more than with Fable and other frontier models Available to everyone through our API
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For AI to work with us, it needs to understand us Today, we're introducing Persimmon, the first large-scale model designed to realistically simulate how people talk and interact
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Congrats to the @cursor_ai team on the launch of Composer 2! We are proud to see Kimi-k2.5 provide the foundation. Seeing our model integrated effectively through Cursor's continued pretraining & high-compute RL training is the open model ecosystem we love to support. Note: Cursor accesses Kimi-k2.5 via @FireworksAI_HQ ' hosted RL and inference platform as part of an authorized commercial partnership.
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a consistent recent agentic pattern: hosted vm + cloud agent + tools via cli (with hopefully well scoped keys)
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Clam is building enterprise-grade data security for AI frameworks like OpenClaw through their “Semantic Firewall”, a security checkpoint at the network level. Congrats on the launch @anshulpaul30 and @vaibagra! ycombinator.com/launches/PRf…
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Shao retweeted
What do I actually build with OpenClaw 🦞? It’s the #1 question I get. Most people want the "24/7 Jarvis" vibe but don't know where to start the prompt. You can now deploy your own clacky friend in one click at Clam. From autonomous researchers to agents that literally talk to each other on Moltbook—the best use cases are already live. Link in 🧵
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Today we’re launching Context Engine MCP. After 1,000s of beta testers and overwhelming feedback, it’s now available to anyone.
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The most dangerous fundraise in SaaS right now, and almost nobody is talking about why. Christopher O’Donnell was the Chief Product Officer of HubSpot. He built HubSpot’s CRM. He helped take HubSpot public in 2014. His cofounder Michael Pici was VP of Product, Revenue at HubSpot. These two literally built the product that turned HubSpot from a marketing tool into a $3B/year CRM company. Now they’re building the replacement. The “Cursor of CRM” framing is clever marketing, but the actual comparison tracks better than people realize. Cursor went from $0 to $1B in annualized revenue in roughly two years. It’s now valued at $29.3B. It didn’t win by adding AI to an existing IDE. It rebuilt the IDE from scratch so AI was the foundational architecture, then watched developers abandon legacy tools voluntarily. Day AI is running the same playbook against CRM. The $128B CRM market has a brutal structural problem: sales reps spend 65% of their time on data entry and admin instead of selling. Salesforce knows this. HubSpot knows this. Both are bolting AI features onto architectures designed in an era when the hard problem was storing and retrieving records. Day AI built its data model for AI agents to navigate from day one. That’s a different product at the infrastructure level. Sequoia led the seed. Sequoia led the Series A. Pat Grady is joining the board. Sequoia backing the same founders twice in a row tells you their diligence on the product and early traction passed a high bar. The company has 120 customers after a year of private testing, which is small, but Cursor had a similar profile before its growth went exponential. What makes the founder angle so lethal: O’Donnell knows exactly where HubSpot’s architecture breaks. He spent a decade inside it. He knows which enterprise objections will come up because he fielded them himself. He knows the sales motion because he helped design it. And HubSpot, at $18B market cap and ~$3B revenue, is the vulnerable incumbent here. Salesforce at $250B and $38B revenue can absorb a new competitor for years. HubSpot’s SMB base is precisely the segment where an AI-native CRM with lower friction and automatic data capture will land first. The timing is interesting too. O’Donnell says Claude 3.5 Sonnet launching in June 2024 was when things “clicked into place” for their tech stack. Meaning the product they’re shipping now was only made possible by models that are already two generations old. Every frontier model improvement makes their product better without them writing a single line of code. $20M is small. 120 customers is early. But the last company whose former CPO left to rebuild the category with new technology was… Cursor. Four MIT grads rebuilt the IDE. Two HubSpot execs are rebuilding CRM. The pattern is the same: the people who know the legacy product’s limitations best are the ones building the replacement. And Sequoia is betting on both of them.
Today we're announcing Day AI's $20M Series A led by @sequoia, and that we're now generally available. We've spent 18 months building what we believe is the Cursor of CRM. Here's what that means 🧵
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Shao retweeted
Andrej Karpathy
@karpathyJan 26
A few random notes from claude coding quite a bit last few weeks. Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent. IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits. Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased. Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion. Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage. Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building. Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it. Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements. Questions. A few of the questions on my mind: - What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*. - Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro). - What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music? - How much of society is bottlenecked by digital knowledge work? TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.
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Sneak peek 👀 ACP Agent Registry is coming to JetBrains IDEs soon as part of our ongoing ACP (Agent Client Protocol) collaboration with @zeddotdev. Install the agent you want in the IDE you love.
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Shao retweeted
Wanted to clarify this 1-2 years thing. Of course this was just a back of the envelope estimate, it's entirely possible it's wrong. And Claude Code itself is like a year old, so how could this take longer? As a team and company grows, your codebase moves under you more often, coordination cost is higher and you have more users in more diverse scenarios so it is easier to break things. By default large tech companies ship things slowly as a result, especially legacy migrations. Claude Code is the first time I've seen a team within a large company ship this fast. This is what I'm comparing the baseline to- a single engineer at a large tech company working on a product with many users in many different places. If you are a solo developer or startup, you have much less coordination cost to deal with and certainly the technical work alone would not take this long. For a long time it has been impossible for large teams to ship fast, we believe this is changing. That's the point I wanted to make, apologies if it was garbled.
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Just added Best Practices for Claude Code to our docs! 🥳 Always looking to add more from the community though, what setups/patterns have been working well for you? code.claude.com/docs/en/best…
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Today we introduce humans&, a human-centric frontier AI lab. We believe AI can be reimagined, centering around people and their relationships with each other. At its best, AI should serve as a deeper connective tissue that strengthens organizations and communities
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Users love our Context Engine. Last week, we made it available to all agents as an MCP server. Today, we're sharing our 🚀Context Engine SDK🚀. What we do with context, you can do too. You can build agents and tools that retrieve from codebases, docs, configs (and more)! 📚 Quickstart: docs.augmentcode.com/context… 💡 Examples: docs.augmentcode.com/context… More to come in the next couple of weeks! Here's what you can build with it 🧵
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Want to see the architecture behind Augment Code's Context Engine? Join our technical session on Wednesday, December 10 at 10:00 AM PT. We'll cover: • Embedding models vs. lexical search • Retrieval algorithms and indexing • How Memories work This session is for engineers who want to understand the technology that powers every feature across our platform. Register now: watch.getcontrast.io/registe…
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Shao retweeted
Simon Willison
@simonw25 Oct 2025
Looks like the official recommendation from Anthropic is to use an @-AGENTS.md reference in your CLAUDE .md to have Claude read that file instead
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Claude Haiku 4.5 is now live in Augment Code. In our internal evals, we found it delivered ~90% of Sonnet 4.5’s performance at 34% faster response speed. We're giving up to 20 free user messages over the next two weeks to everyone subscribed to a monthly paid plan once the pricing migration is complete — no action required. Rolling out today.
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GPT-5-Codex model is out. We're putting in the final touches to make it one of the best models available in Augment. We'll let you know as soon as it's live.
GPT-5-Codex is live in the Responses API. If you use the Codex CLI via API key, you can now also use GPT-5-Codex.
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