When I shared @harvey’s model strategy a few months ago, there were two parts: 1. Build our own model 2. Use that to help customers do the same We’ve done the first. Now we’re hiring for the second: Harvey’s Private Model Program. We’re seeing huge demand from law firms to own their own intelligence leveraging private data. This will enable them to become frontier firms that get smarter with every client matter. You’ll:
 - Partner with law firms to build these systems. - Build the team that delivers this at scale.
 - Work with our technical org to define the platform that powers this team. We’re looking for a technical PM or founder type to own Harvey’s Private Model Program. DM me if this sounds interesting.

My first podcast, with my friend and investor @saranormous. We talked about what we're building @seqholdings, why now, and the opportunity we see ahead. Thanks for having me, @NoPriorsPod.

This instance was caused by a hallucination (the model fabricated a proper noun) that was further amplified by its causal thinking trace. This was not a data breach, no user data was shared, and no user isolation boundary was violated. Our users place a lot of trust in Instinct to keep their data private and secure. We've done a lot of work to make sure that users’ data are truly partitioned, from isolated sandboxes to short-lived local credentials to identity-signed tool execution. Regarding hallucination prevention: We worked over the last 48 hours to build an active hallucination detection system that now scans and verifies every token that flows through the platform. This layer is powered by small models that are trained to predict and detect hallucinations caused by ungrounded claims, creative brainstorming in thinking traces, or rare random sampling errors. Our systems are adversarially trained and battle-tested by world-class agent exploitation security teams to ensure that they can detect very subtle and nuanced hallucination cases. This layer has the ability to steer or intercept Instinct from proceeding with the next thinking trace or tool call execution before it is generated or executed. In the coming weeks, we’ll share a deeper dive into how we’re building a proactive engine to protect Instinct from hallucinations. We take every opportunity to learn and create, and we’re excited by the performance and potential for this line of work. These models are going to continue to be hardened every day through continuous testing, sampling, and creative adversarial training.

just got off the phone with a new engineer hire at a portco with a very wise insight “AI has been replacing my job since I got a CS degree, yet I’m busier than ever - we can all just be more ambitious” this is the same insight that the inimitable @JensenHuang has for us all

The hardest thing about building @harvey is doing what’s best for our customers despite immense pressure to do what’s easy. The easy thing would have been to force our customers onto consumption pricing before they were ready and serve them worse models to protect our margins. We chose to help our customers transition on a timeline that works for them and give them the best models in the meantime, even though it hurt our margins. This meant optimizing our product through routing, harness improvements, and post-training so we could serve frontier intelligence at an affordable price. It also meant building the infrastructure for customers to monitor and manage spend: usage dashboards, per-matter cost attribution, spend caps, and ROI reporting. As a result, we improved our gross margins from -50% to positive in a single quarter despite usage doubling month over month and continuing to serve the best models. Our philosophy is simple: do what’s best for our customers, even when it’s painful, hurts our margins, or draws criticism from competitors, X, and the press. We believe the most important part of building a company is earning and keeping your customers’ trust. You do that by doing the hard thing for them, even when it costs you.

Users won’t be necessarily able to articulate it — but they are going to be increasingly frustrated when companies are holding back inference, restricting tokens naively at the cost of performance Once you have tasted the nectar of scaling tokens you just expect it

There are a number of incredible low-margin consumer services that have massively grown their operating profit (and their valuation) through an in-product advertising business: - Amazon: ~$80B - Uber: ~$2B - Doordash: ~$1B - Instacart: ~$1B It'll be interesting to see if this creates a modern form of the innovator's dilemma, i.e., enabling agentic use (which is unequivocally pro-customer) cuts deeply to their bottom line, creating opportunity for those that don't rely on ads for their operating profit (e.g., Shopify).

rare is the team doing true architectural AI research these days. I talk to the extraordinarily broad and productive researcher Stefano Ermon about his company, latency, and why it’s still worth going after good ideas in the age of scaling

Friday thought: world totally underestimating “a country of geniuses in a datacenter” we’ve never seen this kind of aggregate intelligence. genius amongst humans is rare, human genius cannot work continuously, bandwidth is limited in human communication, and agents have no egos

never been such a gap between "backlog" vs. real, delivered revenue in technology as for AI infrastructure credit peeps just want IG 5Y contracts but they will be surprised by delays, failures and fraud by every clown & their mother that thinks they can run a datacenter now

looking for comms lead for breakout AI company. good judgement, taste, and "direct" orientation required, traditional comms experience not. must: work at 2026 AI pace, believe in new products must not: be cringe, be afraid

Congratulations team Sequence Holdings. At-scale AI-transformation, in partnership with extraordinary existing businesses, is going to be a massive value driver over the next decade. From seed to $7.7B buyout in 18 months 🚀

Our new Trusted Person network is now available to all Instinct users! You can get started by asking your Instinct to add a few friends to your trusted network. For the next two days, you’ll receive an additional 15 invites - bring the most important people in your life into your network. Thank you to our early access users for helping with testing over the last few days. Some of the use cases that were shared with us: - Meetings: finding 1 on 1 time with trusted people has never been easier. - Dinner with friends: Instinct reached out to 10 peoples’ Instincts, found a common time, booked a restaurant reservation, and sent out the invites. - Recurring tennis lessons: Instinct keeps a standing session available on both sides (trainer and student), and adjusts it when one side’s calendar has a conflict.