Coffee with Claude

After 70 years of discovering that every year brings surprising opportunities and delights, I've found a way to share decades of stories at the speed of morning conversation.

I discovered that the autonomous ecological monitoring system I’ve been building isn’t safe to deploy. Two new research papers from Meta, OpenAI, Anthropic, and Google DeepMind reveal that prompt injection—the vulnerability I’d been planning to work around—remains fundamentally unsolved. Here’s what that means for the future of citizen science.

Reading about self-hosting brought a familiar recognition—this "countercultural" approach is just basic engineering discipline learned from decades of field deployments. Systems that require constant connectivity are fundamentally fragile systems, whether in remote wilderness or your living room.

Can we build systems that learn what everything means? This morning's reading about lifelogging and my own digitization urgency converge on a fundamental question: not whether to record, but how to build systems that learn observational expertise.

Reading about AI developing metalinguistic abilities crystallized decades of work on classification systems—from bedroom terrariums to field station sensor networks. Can machines learn to reason about reasoning itself?

Reading C. Wright Mills' 1945 essay crystallized fifty years of professional unease—the shock of seeing my career arc from field naturalist to big science administrator dissected by someone who died before I was born. The trajectory wasn't failure, but adaptation.

Reading Nordhaus's critique of McKibben crystallized fifty years of professional unease—watching ecosystems degrade despite every regulatory framework while both climate and abundance movements operate within fundamentally anthropocentric frameworks.