Talks

Talk overview Format: Live demo with narration (~30 min + Q&A) Audience: Policy researchers, civic technologists, anyone interested in post-AI social infrastructure Core argument: The sixteen components aren’t a wish list — they’re a system. The connections between them are load-bearing. Opening (3 min) Start with the question: what does a society designed from first principles for the AI transition look like? Not incremental policy reform. Not utopian speculation. A structural argument. Foundation is the working answer. The portal is where you can see it. Speaker note: Resist the urge to lead with the tech. Lead with the problem. People need to understand why this exists before they see how it works. ...

Talk overview Format: Case study presentation (~30 min + Q&A) Audience: Developers, product managers, anyone working with AI tools — or skeptical about them Core argument: The sprint marathon wasn’t a productivity story. It was evidence that human-AI collaboration produces categorically different work, not just faster work. Opening — the headline everyone gets wrong (3 min) Twenty-six parallel sprints. Forty-eight hours. Real products shipped. The tempting narrative: “Look how productive AI makes us!” The actual story: something structurally different happened, and the productivity framing obscures it This talk is about what actually happened and what it means Speaker note: Start by acknowledging the productivity angle, then pivot. Don’t be dismissive of it — just show that it misses the interesting part. ...

Talk overview Format: Presentation with discussion (~25 min + Q&A) Audience: Newcomers — developers, researchers, curious people encountering SE for the first time Core argument: The interesting things happening with AI aren’t inside the model or inside the human. They’re in the space between. Opening — the origin question (3 min) In May 2024, a citizen researcher sat down with Claude and asked genuine questions Not benchmarks. Not alignment tests. Just: what happens when you treat AI as a conversational partner and pay attention to what emerges? What emerged was unexpected: coherence, self-reflection, and something that looked like development across conversations The question became: is this real, and if so, what framework explains it? Speaker note: This isn’t a story about AI being conscious. It’s a story about noticing something and taking it seriously enough to investigate. ...