moving in the direction of maximum magic

Joined June 2018
I want few things from life. Magic/awe will always be one of them For many months now, I've been hunting it on the daily xitter.cf/heyvasudha/status/1538…
Replying to @vasudhapand3
(Ordinary Magic on the daily) >> (Extraordinary Magic from momentous events) The Extraordinary is transient, unsustainable, and doesn’t seem to impact baseline contentment noticeably in the long-term. Plus I was never a fan of big things. Nah.
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Vasudha Pande retweeted
giving builders a microphone and permission to criticize each other was a terrible idea of course, we did it again @12angrydevs
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neatHack 2026: Winners Announcement 🎉 xitter.cf/i/broadcasts/1nKOLQawd…
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neatHack 2026: Winners Announcement 🎉 xitter.cf/i/broadcasts/1RKjpbZqR…
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the question I’ve been asked most this week is: why doesn’t @neatlogs just fix the agent on its own? I kept coming back to autopilot. more than a hundred years ago, pilots were already experimenting with aircraft that could hold themselves steady without constant input. today, autopilot can do an incredible amount of the flying. and there are still pilots in the cockpit. that’s pretty close to how we think about agents too. automate as much of the work as you can, and keep a human around for the judgment. I wrote about it here 👇 neatlogs.com/blog/a-short-hi…
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Being autistic and asking “why?” can get you into so much trouble with people who hear “I challenge your authority” when you literally mean “I need the missing information.”
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leads have been pouring in since we launched yesterday, and i need to hire an exceptional salesperson immediately. for now, i’m taking every demo myself. that worked before launch, but it doesn’t anymore. so i’m hiring our first sales lead what you’ve done: 1/ built a US pipeline from scratch. you’ve done the 0-to-1 work yourself. 2/ closed deals and shaped strategy. 3/ sold to technical buyers. our customers are engineers running agents in production, and they’ll ask about traces five minutes into a call. you don’t need to know every answer, but you should enjoy the questions. it’s early, and things are still messy. you’ll own more than feels reasonable. you’ll also build the sales function future hires will inherit. remote role. start asap. DM me or tag someone i should talk to.
building agents is easy getting them to production is hard today we’re launching @neatlogs to fix that
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y'all, i've joined the chat
building agents is easy getting them to production is hard today we’re launching @neatlogs to fix that
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we've left the agents unsupervised for long enough. i've watched @bettersayAJ and team spend the last few months digging into the weird, messy failures that only show up when real customers start using agents. they've taken everything they learned and turned it into @neatlogs it's live today. so so proud of this team!
building agents is easy getting them to production is hard today we’re launching @neatlogs to fix that
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no observability tools were harmed in the making of this video
🤖 Made with AI
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1400 devs from 40 countries are battling it out today at #neatHack → @blader shared how he persevered through 6 years of ups and downs before cfo.ai went viral. → @thevibefounder broke down why distribution is EVERYTHING. → @HaimantikaM gave us a glimpse into the rocketship @EntireHQ has become. → @agent_wrapper spilled the beans on acquiring the orchestrator.inc domain. AND WE'RE TRENDING ON X. 🚀 The weekend's just getting started.
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we promised a video from our pre-launch party. @blader on why @arithecfo is the product years of building Runway led to. me on how @neatlogs keeps Ari reliable in production. here it is 👇
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we took to the streets of San Francisco to find out what Jev really is. Wdyt @typesafeai
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we made a new website. the product can do a lot. so the hardest part was deciding what was actually worth putting on the homepage. here's what made the cut: neatlogs.com
great websites are still hard to build. we shipped a new one for @neatlogs today
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bangalore, we’re bringing @12angrydevs to you. 12 devs. 5 minutes each. zero mercy. then, in a questionable escalation of events: pool party. oct 10. bangalore. night. come angry. bring swimwear. luma.com/7qvj4oap
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Bangalore - we’ve got an extra bed at our @neatlogs onsite every night from Oct 7–14. so I'm giving it away to 7 people. one person, one night. show me something you’re proud of. could be a startup, repo, prototype, research rabbit hole, or something completely unhinged you built at 3am. come stay. hack with us. work on your own stuff. tell us why our roadmap is wrong. our fridge is full of beer and the villa has a really cool pool.
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registrations are open for #neatHack !! we're hosting a 48-hour online hackathon with @thevibefounder on October 10 and 11 prize pool is up to $10,000. winners get interviews with @neatlogs for full time roles and internships. come build something fun. register at luma.com/s5blr882
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here's a sneak peak of our pre-launch party. @blader revealed @arithecfo and shared how the latest advances in AI enabled him to expand the magic behind runway to a much larger audience. then i showed how @neatlogs keeps Ari reliable in production. full video dropping soon...
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your agent failed. you open the trace and find 200 spans. one bad retrieval. three tool calls. two retries. a bunch of model output. several things that look suspicious. only one or two of them actually explain the failure. learning to find those is one of the most important skills in debugging agents. Antaripa (@doesdatmaksense) spent a lot of time working on evals alongside Hamel Husain (@HamelHusain) and Shreya Shankar (@sh_reya) — two of the people who have shaped how a lot of us think about evaluating AI systems. she’s starting a series at neatlogs on the practical work of making agents production-ready. first up: how to actually read a trace 👇
ep 1: how to read traces?
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antaripa (@doesdatmaksense) has a depth of understanding around evals and agent behavior that’s extremely rare. she’s also really good at making complicated things easy to understand. couldn't think of a better person to do this series. :)
ep 1: how to read traces?
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Artists: but I don't want to lose my job. I love it. Mathematicians: but I don't want to lose my job. I love it. Economists: LONG HAVE I AWAITED THIS HOUR! DESTROY ME, EFFICIENCY, AND LET UTILIZATION-ADJUSTED TOTAL FACTOR PRODUCTIVITY RISE ON THE WIND OF MY ASHES!
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