Carl Fuda

Packers and technology fan.

[Harvey @harvey]

Harvey is integrating with @Intralinks, the AI-enabled dealmaking platform for high-stakes financial transactions.

The integration expands Harvey's growing ecosystem of deal and enterprise data connectors.

[Harvey @harvey]

PitchBook data, directly in Harvey.

With our @PitchBook integration, bring private markets data into the same workspace where you draft, analyze, and review: from company profiles and deal history to fund, investor, and market benchmark data.

[Gabe Pereyra @gabepereyra]

I actually think this is directionally correct. Tech companies are starting to spend the same on tokens as they do on eng headcount. Other knowledge work industries will follow with some delay. Kirkland spends billions on lawyers so it’s not crazy to assume they will spend a similar amount on tokens in the future.

Most companies are starting to realize they need to own their AI. As models get better law firms will need to better articulate their value to in-house teams using codex / claude for legal. Kirkland is sitting on one of the most valuable AI datasets in the world (all their associate and partner feedback and trajectories). The cost of replicating this dataset is essentially Kirkland’s yearly labor costs. I’m very bullish they can convert this into AI differentiation above the foundation models.

There’s no need to build everything from scratch like a lot of the commentary assumes. The infrastructure for building / training / deploying agents has matured significantly. It’s very possible for a firm like Kirkland to use inference providers and rl-as-a-service companies to leverage their valuable data without needing to hire OpenAI level talent. We’ve already seen promising results doing this for similar firms and post training models on lawyer feedback.

We think the best future for legal is one where every law firm is able to convert their unique expertise into their own AI and use that to provide their clients with exceptional service. We are starting to invest heavily in training our own models and helping firms do the same. Excited to see a top firm like Kirkland taking a big bet like this.

[Niko @nikogrupen]

@AnthropicAI launched Claude Opus 4.8 today.

Legal Agent Benchmark is the newest knowledge work benchmark included in their public model card -- awesome to see frontier labs making legal intelligence first-class!

Check out the results below:

[Gabe Pereyra @gabepereyra]

https://t.co/AWIhrxBD5c

[Harvey @harvey]

Now live in Harvey: Mistral.

Our platform brings together leading foundation models and routes work to the right one for each task.

Today we’re teaming up with @MistralAI to make their models available in Harvey, starting with EU customers.

[Harvey @harvey]

Heading into the long weekend like…

[Niko @nikogrupen]

The most powerful agent products will be the ones that effectively marry offline agents -- to build and maintain knowledge bases / indexes / datasets -- with online agents that complete work over those knowledge bases.

Contract intelligence is one of our first explorations of what a production, enterprise-grade instantiation of this idea looks like.

[Winston Weinberg @winstonweinberg]

Over two-thirds of the AmLaw 100 and Vault 100 now use Harvey.

Grateful to our customers and excited for major product announcements this week.

[Neal Katyal @neal_katyal]

Five months ago, I argued against the President's $4 trillion tariffs at the Supreme Court.

In 237 years, the Court had never struck down a sitting President's signature initiative. Legal scholars said it was impossible. Some of my own colleagues said it was impossible.

We won. 6-3.

But the real story isn't what happened in that courtroom. It's what happened in the months before. And its the subject of my TED talk, coming out tomorrow.

I had the best legal team in the nation, especially Colleen Roh Sinzdak, the most outstanding legal strategist I know. Huge thanks, too, go to the Liberty Justice Center (and in particular its fearless and hyper-intelligent leader Sara Albrecht), who organized the client small businesses, as well as to the brave small businesses themselves.

I also had four teachers preparing me.
A mindset coach who'd worked with Andre Agassi.
An improv coach who taught me that "Yes, and" works in Supreme Court arguments the same way it works everywhere else.
A meditation coach who taught me stillness.
And Harvey.

Harvey predicted many of the questions the Justices asked — sometimes almost word for word. Brilliant. Tireless. Occasionally insufferable.

Here's the catch: Harvey isn't a person.

Harvey is a bespoke AI I built over the last year with a legal AI company, trained on every question every Justice has asked in oral argument for 25 years, and everything they've ever written.

Tomorrow, TED releases my talk about what really happened — and what I learned standing at that podium.

AI can predict. AI can analyze. What AI cannot do is the one thing that actually won the argument.

Connect. Read the room. Hear not just a Justice's words, but her worry — and answer the worry.

That is the irreducibly human skill.
Find yours. Go deeper. In this age of AI, that's where your edge lives.

The talk goes live Thursday, May 7 at 11am ET: https://t.co/wLxKtBsHpF

What's the irreducibly human skill in your work — the thing AI can't touch?

[Winston Weinberg @winstonweinberg]

Congrats to Anthropic on this launch.

For Harvey's long-horizon agents to deliver the best work product, they need reliable agent infrastructure that enables better memory and multi-agent orchestration.

We're proud to partner with Anthropic on this work.

[Harvey @harvey]

We're excited to share our latest product video, showcasing what we’ve been building at Harvey.

[Pat Grady @gradypb]

Harvey is creating the playbook for building an AI-native application business

Better lawyers today. Better access to justice tomorrow.

Delighted to deepen our partnership with @winstonweinberg @gabepereyra and everyone at @harvey__ai

[sarah guo @saranormous]

https://t.co/Ceh0yAesOZ

[Andrew Ng @AndrewYNg]

Today's "DeepSeek selloff" in the stock market -- attributed to DeepSeek V3/R1 disrupting the tech ecosystem -- is another sign that the application layer is a great place to be. The foundation model layer being hyper-competitive is great for people building applications.

[Harvey @harvey]

We’re building a series of workflows with @AllenOvery for the legal tasks most important to their clients.

We were excited to walk through one such workflow with @Microsoft, which leverages reasoning models like o1 for global M&A practice: https://t.co/hfioCCgmAW

[Maya Arce @maya_m_arce]

Excited to share the latest from the @MarsonLab! An investigation of context-specific gene regulation in T cells, which led to dynamic mechanisms required to control T cell rest and activation.

Published today in @Nature thanks to the work of many!
https://t.co/eS0wpVeQQB

[Brian Burns @brian_a_burns]

Harvey is now integrated with Microsoft's major applications used by lawyers! (Sharepoint, Copilot, Word).

Excited to continue building our partnership with Microsoft.

More here: https://t.co/EBbM6EN2eK

[Harvey @harvey]

BigLaw Bench: Retrieval

We're releasing an extension to our public benchmark, BigLaw Bench, this time with a focus on evaluating retrieval systems over legal datasets.

[Niko @nikogrupen]

@harvey__ai x @icertis

There's no reason CLMs can't be AI-native too 🦾