partner @boldstartvc - inception, technically interesting problems, enterprise. previously founded @darklang

Somerville, MA
Joined May 2008
I'm taking an extra long holiday Twitter break this year. I'll be off this app for November & December - email me if you need to reach me before January 4th 2023 📅
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Ellen Chisa retweeted
Introducing GEN-0, our latest 10B+ foundation model for robots ⏱️ built on Harmonic Reasoning, new architecture that can think & act seamlessly 📈 strong scaling laws: more pretraining & model size = better 🌍 unprecedented corpus of 270,000+ hrs of dexterous data Read more 👇
Ellen Chisa retweeted
A lot of people say AI will make us all "managers" or "editors"...but I think this is a dangerously incomplete view! Personally, I'm trying to code like a surgeon. A surgeon isn't a manager, they do the actual work! But their skills and time are highly leveraged with a support team that handles prep, secondary tasks, admin. The surgeon focuses on the important stuff they are uniquely good at. My current goal with AI coding tools is to spend ~100% of my time doing stuff that matters. (As a UI prototyper, that mostly means tinkering with design concepts.) It turns out there are a LOT of secondary tasks which AI agents are now good enough to help out with. Some things I'm finding useful to hand off these days: - Before attempting a big task, write a guide to relevant areas of the codebase - Spike out an attempt at a big change. Often I won't use the result but I'll review it as a sketch of where to go - Fix typescript errors or bugs which have a clear specification - Write documentation about what I'm building I often find it useful to run these secondary tasks async in the background -- while I'm eating lunch, or even literally overnight! When I sit down for a work session, I want to feel like a surgeon walking into a prepped operating room. Everything is ready for me to do what I'm good at. --- Notably, there is a HUGE difference between how I use AI for secondary vs primary tasks. For the core design prototyping work, I still do a lot of coding by hand, and when I do use AI, I'm more careful and in the details. I need fast feedback loops and good visibility. (eg, I like Cursor tab-complete here) Whereas for secondary tasks, I'm much much looser with it, happy to let an agent churn for hours in the background. The ability to get the job done eventually is the most important thing; speed and visibility matter less. Claude Code has been my go-to for long unsupervised sessions but Codex CLI is becoming a strong contender there too, possibly my new favorite. These are *very* different work patterns! Reminds me of @karpathy's "autonomy slider" concept. It's dangerous to conflate different parts of the autonomy spectrum -- the tools and mindset that are needed vary quite a lot. --- The "software surgeon" concept is a very old idea -- Fred Brooks attributes it to Harlan Mills in his 1975 classic "The Mythical Man-Month". He talks about a "chief programmer" who is supported by various staff including a "copilot" and various administrators. OK, so there is a super obvious angle here, that "AI has now made this approach economically viable where it wasn't before", yes yes... But I am also noticing a more subtle thing at play, something to do with status hierarchies. A lot of the "secondary" tasks are "grunt work", not the most intellectually fulfilling or creative part of the work. I have a strong preference for teams where everyone shares the grunt work; I hate the idea of giving all the grunt work to some lower-status members of the team. Yes, junior members will often have more grunt work, but they should also be given many interesting tasks to help them grow. With AI this concern completely disappears! Now I can happily delegate pure grunt work. And the 24/7 availability is a big deal. I would never call a human intern at 11pm and tell them to have a research report on some code ready by 7am... but here I am, commanding my agent to do just that! --- Finally I'll mention a couple thoughts on how this approach to work intersects with my employer, @NotionHQ First, as an employee, I find it incredibly valuable right now to work at a place that is bullish on AI coding tools. Having support for heavy use of AI coding tools, and a codebase that's well setup for it, is enabling serious productivity gains for me -- *especially* as a newcomer to a big codebase. Secondly, as a product -- in a sense I would say we are trying to bring this way of working to a broader group of knowledge workers beyond programmers. When I think about how that will play out, I like the mental model of enabling everyone to "work like a surgeon". The goal isn't to delegate your core work, it's to identify and delegate the secondary grunt work tasks, so you can focus on the main thing that matters.
Ellen Chisa retweeted
A lot of work goes into launching any product @zuplo, but we wanted a little extra for our AI Gateway, here's a peek behind the scenes...
Ellen Chisa retweeted
I’m excited to launch @tessl_io's first products! Introducing the Tessl Framework and Tessl Spec Registry, which integrate into any agent to keep it on rails and well informed using Spec-Driven Development. More details in the launch post: tessl.co/z01 It’s a big milestone in the journey towards AI Native Development🚩 I’m proud of our amazing team, and keen to get beta feedback from the community! ❤️ What’s the problem we’re solving? Agents are powerful, but they’re very unreliable. They hallucinate, claim false success and break things often enough that it’s hard - and tiring - to use them on production code. How are we helping? The Tessl Framework makes agents capture intent in specs before coding, aligning you and the agent on what to build. It adds tests as harder guardrails, and stores specs as long term memory of what your product should do. It’s available in private beta - visit our home page to request early access: tessl.co/2b3 The Tessl Spec Registry helps agents use open source better. It contains over 10,000 usage specs for using libraries, which you can add to your project like regular dependencies. It also lets you distribute your own guidance and policies to agents. It’s in open beta and free to use! Check it out here: tessl.co/jb8 Both products are just the beginning, and we’re committed to building them in the open. Check out the video or our launch blog post for more info: tessl.co/z01 Looking forward to hearing your thoughts, in the thread or our community Discord!
Ellen Chisa retweeted
15 years into building @Boldstartvc with @EdSim, 5 years into working with @ellenchisa I've learned it's all about people! 🔥 Up to Announce our 250MM fund VII to back bold technical founders building the autonomous enterprise @ inception! Thanks to our amazing founders + LPs
🔥 up to announce @boldstartvc Fund VII $250M to back bold technical founders building the autonomous enterprise. From Inception. Before the world believes. It always starts with an idea that feels insane… until it isn’t. 🎥👇🧵
Ellen Chisa retweeted
🔥 up to announce @boldstartvc Fund VII $250M to back bold technical founders building the autonomous enterprise. From Inception. Before the world believes. It always starts with an idea that feels insane… until it isn’t. 🎥👇🧵
Way more to come! Thank you to @edsim @etdurbin and all the founders and LPs who have enabled to do this.
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You get all three of us and @etdurbin and @edsim are some of the best partners anyone could ask for. There are things Eliot did for @darklang that I still only share in private. And @edsim sets the standard on how to engage across the board (and has the best newsletter).
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If that might be you - please reach out if: 1) It’s inception. There’s no too early but there’s definitely a too late. 2) You’ve solving a clear pain point. 3) You want to work with some other people who are fired up and ready to take on big problems.
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And many more, including teams I was so excited to back that I was writing checks two weeks after having a new baby. (Many are still 🤫) but excited to keep adding to this chart:
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To working with the Generalist team @peteflorence , Andy, @andyzeng_, and @E0M to push the capabilities of Dexterous manipulation:
Today we're excited to share a glimpse of what we're building at Generalist. As a first step towards our mission of making general-purpose robots a reality, we're pushing the frontiers of what end-to-end AI models can achieve in the real world. Here's a preview of our early results in autonomous general-purpose dexterous capabilities – fast, reactive, smooth, precise, bi-manual coordinated sensorimotor control.
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Ellen Chisa retweeted
congratulations to the @GeneralistAI_ team today - you've come a long way since inception!
We've been heads-down building.  The robots have gotten pretty good.  We'll be sharing a brief update soon.
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Ellen Chisa retweeted
So 🔥 up for this amazing team from @GoogleDeepMind, @BostonDynamics, @OpenAI... to show the world what its been quietly building As @peteflorence says: "We think we've hit a new point on the frontier of general purpose real world intelligence – new levels of simultaneously fast, smooth, precise, reactive, bi-manual coordinated dexterity." 🙏🏻 for @Boldstartvc @ellenchisa to be partnered from Inception The future is coming faster than we think
Today we're excited to share a glimpse of what we're building at Generalist. As a first step towards our mission of making general-purpose robots a reality, we're pushing the frontiers of what end-to-end AI models can achieve in the real world. Here's a preview of our early results in autonomous general-purpose dexterous capabilities – fast, reactive, smooth, precise, bi-manual coordinated sensorimotor control.
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Ellen Chisa retweeted
Nothing will stop @GeneralistAI_ robots from working!
Excited for Generalist to share their research preview today - they've achieved some amazing dexterous capabilities - check out the videos to see what robotics can feel like. My personal favorite is the lego demo.
Today we're excited to share a glimpse of what we're building at Generalist. As a first step towards our mission of making general-purpose robots a reality, we're pushing the frontiers of what end-to-end AI models can achieve in the real world. Here's a preview of our early results in autonomous general-purpose dexterous capabilities – fast, reactive, smooth, precise, bi-manual coordinated sensorimotor control.
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