
COO @Harvey. Fast talker, slow runner.
New York, NY
Joined May 2011
- Tweets14.2K
- Following3.4K
- Followers13.4K
- Likes16.9K
Pinned Tweet
I wrote about the #USWNT, women's sports, and how letting girls play can change their lives (and the world): medium.com/@katieaburke16/if…
Katie Burke retweeted
Today, @harvey is partnering with Sourcery as our exclusive legal AI sponsor.
Harvey has emerged as the dominant player in legal AI, with a $15.5B valuation & surpassing $400M in ARR.
A couple months ago I sat down with Harvey Co-Founder & CEO @winstonweinberg, Co-Founder & President @gabepereyra, & Head of Applied Research @nikogrupen at the company’s San Francisco HQ to discuss frontier model research, proprietary legal intelligence, agentic workflows, & the economics of AI.
Stats:
› 3,500+ customers
› 200K+ professionals
› 80% of Am Law 100 firms
› 5 of the Fortune 10
I am so excited to deepen our relationship with Harvey!
Katie Burke retweeted
Harvey featured today (#5) in LinkedIn's Top 50 Startups 2026:
Introducing Intake, where every ask to legal gets routed and resolved.
Requests come in through the tools your business uses, including email, Slack, Jira, and ServiceNow.
Intake gathers the right context, then routes and resolves requests using your legal team’s rules: where each request goes, what agents can resolve autonomously, and what needs a lawyer’s review.
Answers and follow-ups go back through the same channels.
Go from request to resolution faster with Intake.
Katie Burke retweeted
Top 25 performing average swe grants from the last four years
Grants for startups based on average % offer
Startup valued under $100M: 0.20% of the company
$100M to $500M: 0.10%
$500M to $1B: 0.05%
Private, $1B: $200k over 4 years (~$50k/yr)
Big public companies (RSUs):
Nvidia: ~$80k/yr (estimate)
Palantir: ~$40k/yr (5-yr vest, 4 years counted)
OpenAI and Anthropic had large grants at $2M and $800K respectfully
🤖 Made with AI
We experimented with wake-sleep learning algorithms for long-horizon legal agents.
We found:
1) Wake-sleep meaningfully improves agent performance on complex tasks.
2) Memory and context written offline during sleep generalizes to new matters and task types the agent did not see in training.
3) Retrieving only the memories relevant to each task, rather than reading them all, halves cost per task while maintaining average quality.
Deep dive by @nikogrupen:
Passing 100 Law School partnerships with @harvey today, love seeing this program continue to expand and grow with faculty and students globally: nonbillable.co.uk/news/harve…
Harvey Q3 Recap:
Metrics:
- Added over $100M ARR and crossed $400M ARR
- 97% GRR
- 20% of the Fortune 500 and 40% of the Fortune 50 use Harvey
- 80% of the Am Law 100 use Harvey
Key hires:
- @asadovsky, Chief Research Officer (former CVP AI, Microsoft AI & Distinguished Engineer, Google DeepMind)
- @stevezad, Chief Revenue Officer (former GVP Rubrik)
Product:
- Harvey II
- Horizon Scanning
- Command Center GA
Engineering:
- Agent harness end-to-end redesign
- Brought agents to Word, Outlook, Vault, and Review Tables
- Vault files 2x+ in Q3, token throughput 20x+ since January, vector DB migration, major cost & efficiency gains
AI:
- Harvey Tenet, our first model post-trained for legal
- Legal Agent Bench extensions for M&A Diligence and Firm Knowledge
- Research collaborations with @FireworksAI_HQ, @appliedcompute, @baseten, @EngramLab, and @trajectorylabs
Always fun to chat with @ZachAbramowitz. Spoiler alert: yes you should want a job at Harvey and our interview has the unlock 🔓
Do you want a job at Harvey? Should you want a job at Harvey? And how to get a job at Harvey?
All of these and more answered on...
🚨🎙️ Episode 61: with @harvey COO @katieburkie
0:00 Zach’s Hot Disruptive Legal Take
4:22 Why Katie Joined Harvey
8:48 Betting on Winston and Gabe in Their 20s
11:39 The “Harvey Is Going to Zero” Tweet Cycle
12:54 Is There Actually a Moat in Legal AI?
15:23 Is Harvey Only for Big Law Juniors?
18:01 Can Harvey Compete With the Frontier Models?
20:55 Harvey’s Killer Feature May Be Its SLAs
22:37 Why Top Engineers Suddenly Want to Work in Legal
25:40 How Many Harvey Employees Are Lawyers?
27:34 Who Works Harder: Big Law or Harvey?
30:18 Does Working at Harvey Burn People Out?
32:30 The #1 Way to Stand Out in a Harvey Interview
36:18 Where Harvey Is Hiring Right Now
38:00 The HubSpot Playbook at Harvey
39:50 Should You Even Make a Three-Year Plan?
41:18 Dharmesh Shah Called It in 2023
42:30 You Don’t Need to Write Code to Use AI
45:08 Where to Find Open Roles at Harvey
Our first commercial is now live, celebrating the agreements that make history. See you on TV, in print, and online celebrating the craft behind law.
this year @harvey hired:
- prev CMO at notion
- prev VP at slack
- prev VP of product at rippling
- prev CVP, AI at microsoft
- prev VP of design at atlassian
- prev VP of sales at canva
- prev GVP at rubrik
- prev CISO at roblox
🤯🤯🤯
Today Ontario Teachers (OTPP) announced their investment in @harvey and we celebrated with our Canadian customers (100+ strong) and our team there (30+ strong). Let’s go Team 🇨🇦!
Katie Burke retweeted
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.
Pretty, pretty good. Welcome @asadovsky!
We're excited to welcome @asadovsky as our Chief Research Officer.
Prior to Harvey, Adam co-led post-training at Microsoft AI and Google DeepMind.
As CVP at Microsoft AI, he led post-training of MAI-Thinking-1.
As a Distinguished Engineer at Google DeepMind, he led teams working on Gemini 1.0 through Gemini 2.5.
Earlier at Google, he led teams working on Assistant, Search Quality, and Search Infrastructure.

















