Product Engineer before it became cool, building https://xitter.cf/t.co/T1tbJTw8ZG, https://xitter.cf/t.co/4aOC3dOPKC, https://xitter.cf/t.co/CMzl30WGzj. I'm so much more than I tweet :)

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Joined September 2018
We did a soft beta launch of Veet @joinveet and we got positive feedback from the community 🤌🏽
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Introducing Bygga! It walks you through assembling IKEA furniture step by step, with interactive 3D & voice instructions. 100% free & open source.
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It's very useful to understand the context around something, how others perceive it, what influences it, etc. I have scraped together all evidence in chronological order, from prophecies before his time, to the surviving documents of his disciples enjoy github.com/0xSero/all-histor…
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Getting @thallyio’s logo to show in Gmail sent me down a $990/year rabbit hole. Got it working for $0. The missing piece was one Google profile setting. Wrote up the steps for other solo and indie founders 👇 View article
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danwo 0.1.3 🎉 • Test Go & Python backends, not just Node • Fault a single-page app's own API calls (500s, dropped connections, lost answers) • Steadier on Linux, Windows fixes, security updates End-to-end tests that judge what happens behind the UI. danwo.dev/changelog
Coding agents made code cheap. Checking it is the bottleneck. Introducing dánwò: open-source e2e testing for the agentic era. It drives your app like a user, then checks what happened behind it: one charge, one webhook, one email. Then it breaks things on purpose to see what survives. npx @ danwo/cli init If you've ever shipped a payment bug your tests missed, I'd love to hear the story 👇 Fun fact: dánwò is Yorùbá for "try it and see." #opensource #e2e #e2etesting #testing #devtools #typescript #qa
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We believe voice is the most natural way to interact with intelligence, so we created Dessa, the most authentic full-duplex speech model ever built. Talking with it feels like talking with a person…full of emotion, nuance, pauses, and a natural cadence. block.xyz/dessa
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Coding agents made code cheap. Checking it is the bottleneck. Introducing dánwò: open-source e2e testing for the agentic era. It drives your app like a user, then checks what happened behind it: one charge, one webhook, one email. Then it breaks things on purpose to see what survives. npx @ danwo/cli init If you've ever shipped a payment bug your tests missed, I'd love to hear the story 👇 Fun fact: dánwò is Yorùbá for "try it and see." #opensource #e2e #e2etesting #testing #devtools #typescript #qa
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Introducing Eleven: reverse engineering with your agent. i've always wanted to open any app and just ask what a function does, instead of staring at assembly for hours. so i built it with Eleven you can: → open Mac apps, Android APKs, Windows and Linux binaries, and read every function as pseudocode, assembly, a graph or hex → ask Claude, Codex, Gemini, Cursor or any ACP agent about the code. it reads the binary with you and you watch every step → your agent renames functions and leaves notes as suggestions. you accept or skip, and everything can be undone → patch bytes safely (always a copy, never the original), compare two builds, and debug with lldb free and open source
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[L1nk in Thread] Earlier this year, I launched a new creative portfolio with a developer. It was elaborate, heavily designed, animated, and I genuinely loved what we made. Then I decided to build another one from scratch 😅 This time, I built it with Codex, Claude, and Antigravity. The goal was simple: make something I could update on the fly, experiment with freely, and keep restrained enough that the work and case studies stay at the centre. It is definitely not finished, and that is kind of the point. I’ll keep changing, breaking, and adding things over time. I also brought one of my recent experiments into it, an orbital media gallery where projects float around an invisible sphere as a spatial archive. If you’re on desktop, try Spatial Mode. There truly is no better time to be a designer. The distance between having an idea and being able to build, test, and put it into the world keeps getting smaller.
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Such an important point. If things don’t compute, don’t make a judgement about your « smartness », you just lack primitives. So, identify the primitives, focus on them and things will make sense. #SysConf #SysConf26
Listening to some Sysconf talks today and it makes me reflect on how much effort it required for me to understand some concepts intuitively. So if certain concepts are flying over your head, you aren't dumb; it just takes time.
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#SysConf26 is over! That was so good 😭.
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We're excited to announce Chowdeck (@chowdeck) as a Partner for SysConf 2026! Chowdeck builds the technology and logistics behind on-demand delivery of food, groceries, pharmacy orders and packages across Nigeria and Ghana. Chowdeck is a great example of engineering excellence. To run their app well, they have to solve on-demand delivery across a dozen cities: a hard systems problem that spans logistics optimization, ETA prediction, recommendations and fraud detection, amongst others. And they do. Now, with their support, we're able to further our mission at SysConf to share knowledge that teaches, shows what's possible, inspires technical excellence and strengthens our engineering ecosystem. See you at SysConf 2026! #SysConf #SysConf26
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Say hello to Aster ✳ A coding agent you run yourself. Your key, your model, your machine. No telemetry. withaster.dev
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Jev + Kimi K3 for fraud detection! TLDR: Jev classified 100 emails in 1.42 seconds, then I routed the uncertain cases to Kimi K3. The full pipeline got 96/100 correct for only ~$0.07. Video is not sped up, check out the live run! Here was my process: I gave Jev 100 emails to classify (a mix of 50 legit & 50 fraudelent emails). It classified all of them in 1.42 seconds. An underrated feature about Jev is it will give you the confidence score for a classification, so I routed any prediction under 95% confidence to Kimi K3 to be fully sure. 31 emails fell below that threshold. After routing those to Kimi K3, the combined pipeline reached 96% accuracy. The full run took 16 seconds & ~$0.07 in inference costs: - $0.068 from Kimi K3 on @togethercompute - $0.003 (1/3 of a cent) from Jev on @typesafeai. I think this is a really interesting pattern: use a fast specialized model like Jev for the narrow task, then route the uncertain cases to a larger LLM. I feel like this kind of approach could be a game changer for use cases like fraud or anything realtime. You can use the speed & low cost of Jev while having a larger LLM as a fallback to ensure high accuracy.
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Also have been playing with @typesafeai Jev, insane! So many immediate use cases and new apps are possible. What a time to be a builder! Sharing some experiments here starting with: Keystroke oracle / predictive launcher: Your launcher ranks by aliases, fuzzy match, and habit. Jev reads intent: type "the pdf I just downloaded" and the newest PDF is already the top hit with a full confidence on every keystroke, in ~100 ms
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Android Use on Aster, I gave my harness a phone instead of a PC. And not it can do anything I want it to do
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🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with native visual understanding. 🔹 Designed for greater capability, faster inference, higher throughput, and scaling to larger models. 1/6
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I resigned from Anthropic today. I spent the last three years doing pretraining research at both OpenAI and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our lives. More thoughts below.
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Today we're launching Mastra Factory. When we started building a factory, we weren't sure what to expect. But over the last few weeks it's has been writing 30% of our PRs, closing 60% of issues. Factory is free + open-source, now you can try it too: producthunt.com/products/mas…
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