Found 5 posts with tag #Open Source
AI can produce code, comments, PR descriptions, and review replies faster than humans can read and own them. The real bottleneck is no longer generation — it's comprehension. Here's how I think about effort symmetry, accountability, and why I don't buy a universal taxonomy.
We've become unpaid staff for the applications we use. The future will separate operational back-office work from human-facing front-office experiences, with AI agents handling the infrastructure while humans focus on judgment and decision-making.
Work is the worst place to learn how to use AI well—precisely because it's the place where results are expected. In 2026, having a personal or open source project isn't about passion. It's about having a place where you're allowed to learn slowly so you can perform quickly elsewhere.
There's a line in a song that aged better than anyone expected: your own personal Jesus. In the AI era, it stops being poetic and starts becoming literal. But this isn't about simulating Jesus—it's about building agents that embody the behavioral patterns of moral revolutionaries, governed openly, and accessible to everyone without institutional gatekeeping.
For the past decade, AI models trained on the open web. That era is ending. The next frontier of training data isn't on websites—it's in our conversations with agents. If we don't build infrastructure to capture and share this data, the future of AI will be fragmented, siloed, and closed. Here's why we need an Agent Data Commons, and what it would look like.
