Freshfields has agreed a deal to help Anthropic build specialist legal AI tools that could later be sold to rival law firms, as the “magic circle” law firm seeks to increase its use of the technology.

Under the deal, the maker of the Claude AI tool will draw on expertise from Freshfields’ lawyers to build products that attorneys can use for tasks such as drafting documents, reviewing contracts and carrying out due diligence on companies.

Source: Anthropic and Freshfields agree deal to create legal AI tools

Workspace agents are an evolution of GPTs. Powered by Codex, they can take on many of the tasks people already do at work—from preparing reports, to writing code, to responding to messages. They run in the cloud, so they can keep working even when you’re not. They’re also designed to be shared within an organization, so teams can build an agent once, use it together in ChatGPT or Slack, and improve it over time.

Source: Introducing workspace agents in ChatGPT - OpenAI

AI labs are looking for additional commercial narratives before their supposed massive IPOs later this year. This is just the latest in the release of areas after Claude Design

Today, we’re launching Claude Design, a new Anthropic Labs product that lets you collaborate with Claude to create polished visual work like designs, prototypes, slides, one-pagers, and more.

Source: Introducing Claude Design by Anthropic Labs \ Anthropic

ChatGPT for Clinicians

We’re introducing ChatGPT for Clinicians, a version of ChatGPT designed to support clinical tasks like documentation and medical research so clinicians can focus on delivering high-quality patient care. We’re making it free for any verified physician, NP, PA, or pharmacist, starting in the U.S.

Source: Making ChatGPT better for clinicians - OpenAI

Claude for Financial Services

Today, we’re introducing a comprehensive solution for financial analysis that transforms how finance professionals analyze markets, conduct research, and make investment decisions with Claude.

The Financial Analysis Solution unifies your financial data—from market feeds to internal data stored in platforms like Databricks and Snowflake—into a single interface. Access your critical data sources with direct hyperlinks to source materials for instant verification, all in one platform with expanded capacity for demanding financial workloads.

Source: Claude for Financial Services \ Anthropic

As Vamsi Narla asked me today:

what do the builders build anymore if everything is built by the LLM companies?

This is a valid and fascinating question. In my immediate response I jumped to a conclusion - that this is the paradox of AGI.

The paradox of AGI — If you develop AGI, then the companies that are being formed today are either going to cease to exist or be acquired.

Elad Gil wrote about this recently. h/t Nikhil Ramesh

Most AI companies should consider exiting in the next 12-18 months

In the Internet era of 1995-2001, roughly 2000 or so companies went public. Of these only a dozen or two survived. Similarly in the AI era, most companies, including those that are ramping revenue today, will see the market, competition, and adoption, turn on them.

Founders running successful AI companies should all take a cold hard look at exiting in the next 12-18 months, which may be a value maximizing moment for outcomes. A handful of companies should absolutely not exit (eg OpenAI, Anthropic) but many should if they can while everything is on the upswing.

This is all of course counterbalanced by enormous growing demand for AI services of all types. While the tide is rising, many companies will seem to be unstoppable and durable - whether they are or not in the long run remains to be seen.

Source: Random thoughts while gazing at the misty AI Frontier

In some ways this is all working-as-intended. To build AGI you need wide adoption of AI technologies to recreate, rethink, innovate current loops. Traditional companies are unlikely to do this because of inertia, capability, cost structure and / or organizational dynamics.

AI companies need this knowledge to learn all the behavior because they are unavailable on the open web. In some ways, this is also a distribution of risk. AI labs can acquire the companies seemingly gaining traction in their industries while continuing to distribute risk to VCs and builders until they can show there is a successful innovation for an industry.

What happens if the labs don’t achieve AGI? If you accept that the current labs are a combination of cloud providers (APIs) and software optimized consulting companies - we are left with a weird combination of AWS and McKinsey or Azure and BCG or Google Cloud and Deloitte.

What happens to token pricing if that is the end result? What happens to the massive investments in compute, energy in that world?

Energy production investments will find other users - so that seems to be a net win for the world. BTC was supposed to initiate this but turns out AI did.

Optimistically, I think compute, especially massive cheap compute will also find a use in this world.

I am not prescient enough to predict what will happen. There are way too many variables for any low level of error. However, in either case, the world will change. Hopefully for the better. 🤞