With ambient AI, you don't prompt AI agents, AI Agents prompt you
Michael Neale, creator of codename goose, an on-machine, open source AI agent built to automate your tasks explores the emerging landscape of ambient AI—agents that don't just respond to commands, but actively observe, learn, and work alongside you throughout your day. Drawing from his experience at the intersection of developer tooling and AI, Michael examines three critical shifts happening right now:
- Ambient Agent Adoption: The radical trust required when AI agents have access to everything—your code, communications, calendar, and creative process. It's not just about project-specific AI anymore; it's about agents that understand your entire digital life and can act on your behalf.
- The New Economics of Intelligence: When AI token costs can represent up to a third of a creative professional's salary, we're not just buying software, we're accessing a new kin economy, much like when we got internet access in the 90s. Michael breaks down why this economics makes sense, even at twice the price, and what it means for the future of creative work.
- Universal Agent Architecture: Why the most powerful general-purpose agents aren't dumbed-down consumer apps, but sophisticated tools originally built for developers. Computers are for computation, and the future belongs to agents that embrace this complexity rather than hide from it.
This isn't a distant future—it's happening now. Come learn how to live productively with AI that knows you better than you know yourself.
Mic Neale
Michael Neale is a Principal Engineer at Block (formerly Square) and a veteran developer tools architect with deep expertise in AI agent systems. He is the co-founder of CloudBees, where he spent years building developer infrastructure and CI/CD tools.
Currently at Block, Michael leads the development of Goose, an open-source AI agent that goes beyond code suggestions to automate complex development tasks from start to finish. His work on Goose represents a significant advancement in AI-powered development tools, as the agent can build entire projects from scratch, write and execute code, debug failures, orchestrate workflows, and interact with external APIs autonomously.