Josh Gen @Josh__Gen

@anamitra Thanks anamitra!

Really excited to publicly announce our acquisition by Rogo! It’s been an incredible journey over the last year, and I’m proud of what we built and the splash we made. More to come as we integrate our product into Rogo and keep building!

Rogo @RogoAI

6 days ago

We've acquired Rivanna, to bring full AI-native due diligence to the Rogo platform. Deal execution today is fragmented across data rooms, models, trackers, and inboxes. With Rivanna, and Rogo's Deal Room, deal teams can integrate natively with entire data rooms and get

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@mlaurencechen @pratik_satija @chetanfs I’m down

Did some traveling recently (touched grass) and have some ramblings: * You don’t realize how much power/weight words have until you don’t speak the language. And not because you don’t understand what people are saying, but because you see communication in its raw form. I could make a combination of sounds with my mouth and it could make someone blush, or make someone angry, or get me kicked out of the place I’m in. Even when those sounds mean absolutely nothing to me, they can have huge impacts on people. Kind of like how as a kid you learn curse words in other languages, and it’s funny because it’s meaningless to you, but it gets a rise out of people who know it. * I’m team Fahrenheit. It was made to put the weather we typically experience on Earth on a 0-100 scale and it makes real world temperatures way better instead of dealing with Celsius decimals. * Donkeys are bigger in real life than they are in Shrek.

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What gets missed with AI productivity gains is that by and large, most roles will continue to be as sophisticated as the tools allow. This is why also thinking through “today’s jobs will be replaced with AI” is a fallacy. Everyone thinks the market is static, but it’s not. As a result of everyone having access to the same technology which augments our work, then users of the tools will increasingly raise their level of output to the point where the prior definition of the job is no longer relevant. Thus, those that understand their particular field and grow in their skills will continue to be differentiated vs. others. If you can do far more, then you start to tackle bigger and harder problems. If you do that, then the expertise still is required to get the job done fully. The engineer with AI is going to be far more productive and capable with AI than the non-engineer trying to build the same piece of software. Building a lightweight app is no longer the definition of getting by in software development. Reviewing a contract will no longer be the definition of a paralegal. Splicing a video won’t be the definition of a video editor. Providing basic financial research won’t be the job of the financial analyst in the future. Simply put, AI will naturally cause most roles to actually grow in complexity rather than reduce in complexity, because we can do far more with the tools.

andrew chen @andrewchen

4 months ago

hot take :) The biggest and most productive people in the AI era are the folks who are already good at their jobs. AI as a multiplier, not an equalizer/democratizer

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New essay on the economics of structural change and the post-commodity future of work. 1. Almost any question about the impact of advanced AI on the economy needs to start at the same place: what is still scarce? Answer that, and the analysis becomes pretty straightforward. This essay explores what becomes scarce if AI really can replicate most of what humans do in production, and what this mean for the future of jobs. 2. My conjecture, working through the economics: labor reallocates across sectors, and the sector it reallocates to has properties that keep labor a meaningful share of the economy. Ultimately this is about the structure of demand itself. For this, we have to go back to Girard, Augustine and Rousseau: once people's base needs are met, their preferences shift to comparative motives (e.g., status, exclusivity, social desirability). This motive is inherently non-satiated. 4. The key paper is Comin, Lashkari, and Mestieri (Econometrica 2021). As people get richer, they don't buy proportionally more of everything. They shift spending toward sectors with higher income elasticity. They estimate income effects account for 75%+ of observed structural change. 5. The ironic consequence: the sector that gets automated becomes a smaller share of the economy, not a larger one. Agriculture got massively more productive and its share of employment collapsed. Manufacturing too. The "stagnant" sectors absorb the spending and the jobs. 6. So the question is: which sectors have high income elasticity in a post-AGI world? I argue it's what I call the relational sector. Categories where the human isn't just an input into production, it is part of the value. 7. Why does the relational sector have high income elasticity? Because human desire has a mimetic, relational dimension. We don't just want things for their intrinsic properties. We want what others want, and we want it more when others can't have it. Girard, Rousseau, Augustine, and Hobbes all saw this. 8. In work with Kristóf Madarász, we showed this experimentally: WTP roughly doubles when a random subset of others is excluded from the good. And in new work with Graelin Mandel, AI involvement kills the premium. Human-made art gains 44% from exclusivity; AI-made art only 21%. 9. This all comes together for the core argument. The sector that absorbs spending as AI makes commodity production cheap is one where human provenance is part of the value, and demand for it grows faster than income. Exactly the profile that keeps labor meaningful. 10. To be clear about the claim: I'm NOT saying aggregate labor share must rise. It may fall. The claim is about sectoral composition, i.e., where expenditure and employment go once commodities get cheap, and the fact that the sector that will absorb reallocated labor maps to a substantial component of human preferences and desire. 11. If you're interested in the formal model, a linked companion technical note works out all the economics. Read the essay here: aleximas.substack.com/p/what-will-be…

Software devs have spent the last 50 years making abstractions. Now that LLM’s write code, all of that is getting peeled back. Lots of the abstractions were just for us, and aren’t necessary for LLMs. * ORMs on top of SQL -> write raw SQL * Python and JS packages to edit xlsx, pptx, etc -> edit underlying raw XML directly * Sdk’s that wrap APIs -> call APIs directly thru curl or http requests

It’s crazy how quickly we went from AI is a bubble to AI is displacing all software. Those are totally contradictory but they were the prevailing narrative 3 months apart from each other

How cool you are as a person is directly proportional to how cool your Claude buddy is. Im pretty cool

Funny claude maxxing experience: I’m filling out a security template excel file from a customer. All the questions are easily answerable if Claude could just access Vanta. So next step, hook up Vanta to Claude! Here was the next sequence of events: 1. Try to use Claude to set up the connection ❌ 2. Add Vanta as a custom Connector with their MCP. Auth failed ❌ 3. Add Vanta MCP to Claude code per their docs. Auth failed ❌ 4. Give up and tell Claude to just use the browser, where I was already logged in.✅ C’mon Vanta. Took longer but it filled out the Excel file, downloaded relevant files, and put it all in an email draft reply. Claude, Maxxed.

The way we've been building @linear since 2019. Don't create the Henry Ford style assembly line of software, but have craftsmen with blended roles.

claire vo 🖤 @clairevo

9 months ago

shot called a year ago

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Hello world