The AI Marketer, Agentic Systems and What Makes Life Meaningful?

"Yesterday" is a bet on stagnation. Tomorrow is a bet on the future.

Good morning

Hope you are doing amazing. Next week's newsletter will be sent on Tuesday, and I can’t wait.

In today's edition, among other things:

• The Rise of Legal AI Tech

• The AI Marketer

• Software Automation via Agentic Systems

• How Actors Remember Their Lines

• Understanding Market Size: TAM, SAM, and SOM

• Developing an LLM: Building, Training, Finetuning

• What Makes Life Meaningful?

Onwards!

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The Rise of Legal AI Tech

The rise of legal AI tech is shaking up the traditional law firm model. For decades, law firms have relied on the billable hour to make money. But with AI automating much of the grunt work, that model may no longer make sense. And there are plenty of questions with 90% of law firms plan to increase their investment in generative AI over the next 5 years.

Some insights from Battery:

Through our analysis and conversations with over 70 legal AI startups, we’ve identified three key areas where AI is poised to revolutionize legal workflows:

1. Legal Research and Review: AI can streamline discovery and search, quickly identifying relevant data and automating document reviews.

2. Contract Drafting and Negotiation: From implementing playbooks to automated hyperlinking, AI can expedite document creation and assist in negotiations.

3. Patents and Intellectual Property: We anticipate the emergence of tools that can parse complex documents and identify prior art, completely transforming the patent landscape.

Here’s the total landscape:

What’s important is that the legal team and lawyers differ as any other customer segment and it’s not one persona or ICP you can address. It’s much more nuanced (as with every buyer persona and ICP):

With 1.3 million active lawyers in the U.S. alone, this is a huge market with both new startup and incumbent potential. The one thing I’m seeing is that so many companies bet on chatbots as the only way to solve legal firm problems with AI.

Chatbots are bets on AI stagnation.

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The AI Marketer

The above-mentioned bet on Chatbots and beyond is already seen in marketing, when after a myriad of marketing co-pilots and chatbots we are seeing the transition to more autonomous solutions with Agentic Systems (more on that below). Via a16z:

The next stage after equipping the marketer with copilot tools is automating the marketer’s work by using marketing agents. In this phase, we expect marketing to shift from a one-to-many model to a one-to-one hyper-personalized activity. Rather than creating a campaign that appeals to the average customer, marketers will be able to personalize each ad shown to a customer based on specific audience and preference data, which performs better than more generic content shared with a broad audience. 

We are just beginning to see companies that are using AI agents to complete narrow, end-to-end (e2e) marketing tasks: A/B testing specific campaign assets, optimizing ad bidding and buying, tracking attribution and analytics, iterating content based on performance, and then making creative decisions (vs. just providing content and insights for the team to use). These agents integrate with performance data (e.g., CTRs) and content creation tools and use judgment to experiment with new variations of content to drive results. They can also likely help gather market research and competitive intelligence, and work across ecosystems from social media to connected TV.

For example, email automation has existed for some time, primarily around templates and workflow around scheduling and tracking emails. But in its future state, an “email marketing agent” will be able to automatically generate the content, personalize the content, set the send schedule, monitor open rates, and adjust the content based on performance metrics —  based on information ingested from product pages, audience demographics, campaign cadences, and parameters selected from connected customer data.

With this landscape:

Here’s the kicker: I think the biggest winners in every vertical will not be the companies who are first to co-pilot/agents/autonomous systems, but the ones who will rethink their users problems from first principles and then build a solution solving that problem with an AI-first approach.

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Software Automation via Agentic Systems

Autonomous AI Agents that you probably have heard of (I’ve been writing about them for the past 2 years) are AI systems that can perform tasks and make decisions independently, without constant human supervision or control.

They have some key characteristics: