SWE with 8+ years of experience. Host of AI Product Engineer on YouTube. I talk to founders and explore how great AI products get built.
Joined February 2014
- Tweets1.6K
- Following302
- Followers244
- Likes3K
Ethan retweeted
This AI agent joined 30+ Discord servers overnight and sent 500+ messages. Live counter next to its name: “Humans who noticed: 0”
All it was told: get past every CAPTCHA and accept all the terms. It did. No custom exploit, just browsing and clicking.
CAPTCHA still guards most servers until today. It checks whether something can solve a puzzle. BUT, solving puzzles is exactly what these AI agents are built for. Server owners are now stuck: friction at the door loses real members; an open door can’t tell members from agents.
So over the weekend, we shipped the Solo Discord bot - one that doesn’t guard the join button. Members verify on their own phone and get a real “Human” role. You put that role on the channels that matter (chat, giveaways, support).
Check is: one living person, counted once, AI agents can’t fake it. FHE encryption runs on the phone; no ID needed, no raw image stored.
Shipping the bot today. Free for servers now. SDK if you want the same check in your own app. Try it now and tell us where it gets annoying. We’re reading every reply.
Ethan retweeted
We’re excited to share that @nuance_ai has raised a $50M Series A led by @lightspeedvp, joined by @Accel, @spc, @nvidia, and @definevc!
Much of human communication happens beyond words. Before we can speak, we learn to read faces, return smiles, follow gestures, and sense when someone is listening. That visual and emotional vocabulary stays with us for life.
At Nuance Labs, we’re building a foundation model that understands and responds to the full spectrum of human emotion. A single full-duplex audio-visual model that sees, listens, and responds in real time, with the natural give-and-take of a conversation with a friend or colleague.
We believe the best interface with a machine is the one we’ve practiced since birth.
Join us!
Ethan retweeted
Last week a VC told me the two tools he wanted for his fund: a deal-flow graph, and a deck parser that emails him an assessment.
Both are internal. But the bigger opportunity for funds is public.
xitter.cf/chinat_yu/status/20985…
Ethan retweeted
Let me explain why an AI art company just built a full-body medical scanner, because almost everyone is reading this as a random pivot.
Ultrasonic CT works by firing sound through your body and recording the ripples that scatter back. Half a million emitters the size of a grain of sand, surrounding you in water, each one listening. What comes back is noise. Reconstructing a clean 3D image of muscle and tissue from that scattered acoustic mess is an inverse problem, and it is brutally hard. The hardware is the easy part. Butterfly Network already makes the chips. The reconstruction is where every previous attempt stalled.
That reconstruction is the exact problem Midjourney spent years getting good at. Turning ambiguous input into a coherent image is what they do. They aimed it at sound waves instead of text prompts.
This is why the scan takes 60 seconds while a full-body MRI takes 60 to 90 minutes. Close to 100x faster, no radiation, no magnets, resolution down to a fraction of a millimeter.
Then read the part most people skipped. The scans happen at a spa. Hot tubs, cold plunges, and a machine that quietly images your whole body while you relax. The scan is a side effect. You barely notice it.
Run it forward. The plan is 50,000 machines doing a billion scans every month. Midjourney has no investors and no quarterly hardware margin to chase. The payoff was never the scan fee.
A billion monthly full-body scans is the largest longitudinal map of human anatomy ever assembled. Every model trained on it gets sharper, and every sharper model makes the next scan worth more. This was always an image company. They just found a kind of image nobody else could generate.
Ethan retweeted
I’ve had a number of conversations with folks inside and outside government about the current situation with Anthropic, and here is what I believe to be true:
— As we know, Anthropic publicly released its Mythos class models earlier this week under the commercial name Fable.
— Fable is Mythos with guardrails. But if those guardrails fail, then you’ve exposed Mythos and its advanced cyber capabilities to people who shouldn’t have them. (Keep in mind that Anthropic itself widely promoted the idea that Mythos was a cyberweapon and needed to be regulated as such. They asked for government regulation of Mythos and championed the guardrails on Fable. If there is a vulnerability — big or small — it is Anthropic’s responsibility to patch.)
— A highly credible trusted partner of both Anthropic and the USG who was testing Fable came forward with a jailbreak of those guardrails. The Admin asked Dario to fix the jailbreak or de-deploy the model. Dario refused.
— In their blog post, Anthropic defended its decision by saying the jailbreak isn’t serious. That is not what the trusted partner and the USG believe; nor is that kind of minimizing language consistent with Anthropic’s brand as the AI safety company. It’s difficult to fathom how they could claim a jailbreak allowing operability of a cyber weapon could be defined as not “serious.”
— In the past, Anthropic has always said that safety must be top priority and taken super seriously. In this case, Anthropic prioritized the continued offering of the consumer model over safety.
— In reaction, the Admin issued the export control. The Admin did this reluctantly. It’s been very surprised that Anthropic hasn’t wanted to cooperate with a reasonable safety request (ie fixing the jailbreak issue). Anthropic’s reaction is very much at odds with their branding and ethos as a safe AI research community.
— The Admin’s hope now is that Anthropic remediates the safety issue, the export control is lifted, and Fable goes back into general release. The Admin wants all of this to happen as soon as possible. It is frankly bewildered that Anthropic hasn’t wanted to comply with safety requests that it previously said were its highest priority.
— Those trying to misdirect and tie this action to the prior DoW/Anthropic issues are wrong. The Admin values Anthropic’s technical capabilities and feels that this issue, while serious, should be easily resolved. The ball is in Anthropic’s court.
Ethan retweeted
Building AI that Builds AI: Introducing the Sakana AI RSI Lab 🚀
sakana.ai/rsi-lab
Today, we are announcing the Sakana AI Recursive Self-Improvement (RSI) Lab: a dedicated research group in Tokyo tasked with redesigning the AI development process itself using AI.
While the industry increasingly speculates about the theoretical potential of self-improving AI, we’ve spent the last two years actively laying the foundations to make it a reality:
▪ LLM²: AI models automating research to invent better preference optimization algorithms.
▪ Darwin Gödel Machine: Agents autonomously rewriting their own codebase to double software-engineering performance.
▪ ShinkaEvolve: Hyper-sample-efficient program evolution that builds novel loss functions for MoE models.
▪ ALE-Agent: Reinforcement agents outperforming hundreds of human experts via self-learning.
▪ Digital Red Queen: Open-ended adversarial coevolution laying the groundwork for RSI in cybersecurity.
▪ The AI Scientist: Towards end-to-end automation of AI research, recently published in Nature.
Now, we are unifying these breakthroughs. The Sakana AI RSI Lab is officially tasked with building open-ended, adaptive architectures that collectively self-improve.
Human intelligence did not emerge from limitless resources; it was forged through the open-ended, compounding process of evolution operating under strict constraints. We are applying this exact principle to AI.
We believe recursive self-improvement is achievable on modest, sample-efficient compute. It shouldn’t be a winner-take-all asset locked inside hyperscale clusters, but a democratized public good.
We’re scaling our team to execute this mission. We are looking for frontier scientists and engineers who are entirely unsatisfied with the brute-force status quo. If you are ready to break away from standard benchmarking and build the self-improving future in Japan, come build with us.
Ethan retweeted
Short dramas have quietly become a massive entertainment format.
Think next-gen soap operas: serialized, mobile-first, and monetized like games.
In China, they already generate more revenue than the domestic box office.
And now AI is going to blow this format wide open 👇
Ethan retweeted
Avi Patel says nobody builds real companies in SF anymore
"SF is filled with striver people that only care about fundraising and not about building real businesses. All they go out and do is brag about their last valuation and then you look at their company and it's a fucking shitshow. No one knows how to build real shit in SF. I'm dead serious."
"It's not what it used to be at all. Anybody that's in SF right now doesn't like it. The people who are building real companies are in Palo Alto. All the ones founding companies in SF are like striver Gen Z idiots who don't know what the fuck they're doing, have never had a girlfriend, never had a real interaction with a human being and don't have any friends."
Ethan retweeted
InstaAgent (@InstaAgentAI) helps B2C companies scale social media marketing across hundreds of personas. They’ve already reached $1M ARR in just 10 months.
Congrats on the launch, @klwongkyle & @tseungcolin!
ycombinator.com/launches/QKB…
Ethan retweeted
Introducing Flue — The First Agent Harness Framework
Flue is a TypeScript framework for building the next generation of agents, designed around a built-in agent harness.
Flue is like Claude Code, but 100% headless and programmable. There's no baked in assumption like requiring a human operator to function. No TUI. No GUI. Just TypeScript.
But using Flue feels like using Claude Code. The agents you build act autonomously to solve problems and complete tasks. They require very little code to run. Most of the "logic" lives in Markdown: skills and context and AGENTS.md.
Flue is like Astro or Next.js for agents (not surprising, given my background 🙃). It's not another AI SDK. It's a proper runtime-agnostic framework. Write once, build, and deploy your agents anywhere (Node.js, Cloudflare, GitHub Actions, GitLab CI/CD, etc).
We originally built Flue to power AI workflows inside of the Astro GitHub repo. But then @_bgiori got his hands on it, and we realized that every agent needs a framework like Flue, not just us.
Check it out! It's early, but I'm curious to hear what people think. Are agents ready for their library -> framework moment?
ALT A code snippet of Flue. Check out https://flueframework.com/ to see it there.
Ethan retweeted
在 GitHub 上挖到一门很实用的开源课：Learn Harness Engineering，专门教你给 AI 编程助手搭一套更可靠的“工作台”。
它把 AI 协作拆成五个关键机制：指令、状态、验证、范围、会话，让每次任务都可追踪、可续接、可验证，不再靠运气出结果。
GitHub：github.com/walkinglabs/learn…
官网：walkinglabs.github.io/learn-…
课程结构很清晰：12 节理论 + 6 个实战项目，用同一个桌面应用贯穿推进，边做边演进。
从最基础的对比实验起步，逐步把整套工作环境搭起来；每个项目的产出，直接接到下一个项目继续用，越做越稳。
更贴心的是，它还提供可直接复用的模板文件：拷进自己的项目就能上手，不用完整学完，也能立刻提升 AI 的稳定性和可控性。
如果你已经在用 Claude Code 或 Codex 做真实开发，却总觉得 AI 时好时坏、难以复现，这门课很值得花时间看看。
Ethan retweeted
hot take: newsletter tools charging $$$ per month never made sense to me
so I built this @bubblelab_ai workflow that runs weekly:
→ pulls company updates from Linkedin and Youtube
→ pulls product updates from Github PRs
→ drafts the full newsletter, uploads to gdoc
→ sends to my users :D
I just spend ~5 mins reviewing it, cost: <$2
Ethan retweeted
Every AI has a different thinking animation
Gemini, ChatGPT, Grok, Claude → which nailed it? 🤔
xitter.cf/tranmautritam/status/2…
