The AI That Builds The AI
We've reached the meta-layer of automation.
We've officially reached the meta-layer of automation.
We're Now Building AIs That Build Other AIs
Latitude 2.0 shows we've moved past simple chatbots and into manufacturing autonomous workforces.
We're no longer just building AI agents to do our work. We're now building AI agents to build those AI agents for us. Latitude 2.0 is an open-source framework that takes a single prompt and creates a production-ready, autonomous AI assistant, complete with its own connected tools.
This isn't just another developer tool; it's a major step in abstracting away the complexity of AI creation. The goal is no longer to meticulously craft a single agent, but to define a task and have an AI architect the solution. We're moving from being users of AI to being managers of AI managers, focusing on system design instead of individual prompts.
This completely changes the game for developers and founders. It signals a shift from building AI features to orchestrating AI systems. The real challenge is no longer "can an AI do this?" but "can we effectively build, manage, and trust an autonomous system of AIs to run an entire process?"
The New AI Workforce is Logging In
While some AIs build other AIs, a new class of agent is ready to start work today.
Genstore.ai: Your AI-powered e-commerce team
This isn't just a no-code website builder; it's an attempt to automate the entire business stack from creation to marketing. It aims to turn ideas into assets with minimal human input.
Convo: Your invisible AI meeting wingman
This moves AI from post-meeting summaries to real-time conversational assistance. That is a much harder, and far more valuable, problem to solve for anyone in a client-facing role.
The Plumbing for Our AI Overlords
Building these autonomous systems requires a new generation of infrastructure.
Modal Notebooks: The GPU-powered playground for your data team
The value here is not just a better notebook, but the abstraction of infuriatingly complex infrastructure. It makes high-performance ML development accessible without needing a dedicated DevOps team.
Stytch Connected Apps: Turns your app into an auth superhero for agents
As agents become commonplace, secure, interoperable identity will be the bottleneck. Stytch is solving that critical infrastructure problem before most people even realise it exists.
Quick hits
Seedream 4.0: Your next ad campaign, created in a flash
ByteDance's new model generates 2K images in under two seconds, making professional content creation a speed game, not just a quality game.
YC Companies Map: The Marauder's Map for the startup world
This map of YC startups turns ecosystem networking into a visual search, making it easier to spot talent clusters and emerging trends.
10X PPC: Launch smarter campaigns, 10x faster
An AI agent that automates the work of a seasoned PPC strategist continues the trend of turning specialised marketing roles into software problems.
My takeaway
The most valuable skill is shifting from prompting AIs to designing systems of AIs.
We spent the last two years learning how to talk to a single chatbot. The next two will be about orchestrating dozens of specialised agents that talk to each other. This is a fundamentally different challenge that requires thinking like an architect, not just a user.
It moves the point of leverage from the prompt to the system design. This raises the bar for what a 'product' is and who gets to build it. The real question is, what happens when these systems start optimising themselves?
How do you manage, debug, and trust a workforce you can't directly command?
Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().