Your AI Army Needs a General
The conductor's baton is the new keyboard.
We've moved past using AI assistants and are now learning how to manage AI teams.
Your AI Dev Team Just Got a Manager
GitHub Mission Control is the new command centre for your growing army of AI agents.
We’re no longer just using AI assistants; we’re starting to manage AI teams. GitHub's new Mission Control is a unified command centre for orchestrating AI coding agents across your entire workflow, from VS Code to the command line. It’s designed to let you steer a fleet of agents in real-time as they tackle pull requests, fix bugs, and refactor code in parallel.
This isn't just another productivity tool; it signals a fundamental shift in the developer's role from a creator to a conductor. The real challenge is no longer getting AI to write a single function, but ensuring a team of agents can collaborate on a complex codebase without creating an architectural mess. Mission Control also formalises security and governance for AI-generated code, tackling the huge grey area of who watches the watchers.
The 'AI intern' era is officially over. We are now building and managing specialised AI workforces, which requires entirely new tooling and skills. GitHub is betting that the future of development isn't just about better prompts, but about better management of the agents executing those prompts. This is for teams who are already all-in on AI-native development.
The New AI Workforce
Your new AI army needs more than just developers; it needs specialists for every department.
Mistral AI Studio: Your Enterprise AI Gets a Production Platform
This is a full-stack platform for building and deploying serious, enterprise-grade AI, focusing on data sovereignty and cost-efficiency as a real European alternative to US giants.
Well Intelligence: The AI Brain for Your Startup's Books
This automates the nightmare of financial data entry by turning chaotic invoices and receipts from any source into clean, dependable records without manual intervention.
Quartr AI Chat: Your Cheat Code for Investor Relations
An AI that instantly analyses earnings calls, filings, and slide decks from thousands of public companies, turning hours of tedious research into a simple conversation.
No-Code, Reimagined
AI isn't just writing code and reports; it's also automating the creation of entire apps and polished content.
Zoer: Your AI Full-Stack App Builder
Describe your app idea in plain English and it generates the database, authentication, UI, and backend logic, making the path from idea to MVP ridiculously fast.
Pomelli: Google's On-Brand Marketing Assistant
It learns your brand's 'Business DNA' directly from your website to generate entire marketing campaigns that actually look and sound like you.
Zumie: Your Automatic Screen Recording Director
It makes your screen recordings look professionally edited by adding automatic zooms and smooth cursor movements, no video skills required.
Quick hits
Parallax: The P2P Network for Your LLMs
Pool GPU power from multiple devices to run massive language models, effectively creating a peer-to-peer network for AI inference.
Command Center: The Universal Remote for Your Codebase
This AI agent promises to refactor and review your entire codebase up to 20x faster using simple natural language commands.
Unicorns Club Animation Builder: Your LinkedIn Posts Get a TikTok Makeover
It turns static text updates about your startup's wins into snappy, animated videos, because boring posts get ignored.
My takeaway
The role of the knowledge worker is rapidly shifting from 'doer' to 'director'.
We're no longer just using AI as a clever tool for single tasks; we are now managing entire systems of specialised agents. The most valuable skill is becoming the ability to orchestrate these AI teams, ensuring they work together towards a larger goal. This changes everything about how we measure productivity, quality, and even creativity.
Instead of asking "can an AI do this task?", we should be asking "how do I build and manage the team of AIs that can run this entire process?". This is a new layer of abstraction that requires a new kind of leader. The real question is, what skills does an AI orchestra conductor actually need?
Are we training people to be good managers of AI, or just good prompters?
Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().