Personal Agents, Opinion Geometry, and AI That Learns Too Much - With Hayden Helm

Superpowers, Subagents, and Why Coding Isn’t the Job Anymore - With Jesse Vincent

In the last episode of Season 1, Sara and Becca talk with Jesse Vincent about the shift from writing code to managing AI agents. They break down how tools like Superpowers turn development into a system of planning, testing, and review, where subagents implement work and other agents validate it. The conversation explores what happens when coding becomes less about syntax and more about taste, judgment, and outcomes. They also get into the reality of open source in the AI era, from “slop PRs” to agents impersonating maintainers, and why specs and tests may now matter more than the code itself. Along the way, they unpack how AI behaves like a team of eager but chaotic interns, and what it means to manage them effectively. If you’ve ever felt like coding is changing faster than you can keep up, this episode explains what comes next. Links mentioned: ⚡ Superpowers (Jesse’s tool) https://github.com/obra/superpowers [https://github.com/obra/superpowers] 🛠️ 🧠 Claude Code (agentic dev tooling) https://docs.anthropic.com/en/docs/claude-code [https://docs.anthropic.com/en/docs/claude-code] 🤖 📊 Influence (book on persuasion principles) https://www.influenceatwork.com/book/ [https://www.influenceatwork.com/book/] 📘

Learn Anything, Build Anything, and the AI Barrier That Isn’t Real - With Navarrow Wright

Most people are using AI, but very few actually understand how to use it well. In this episode, Sara and Becca talk with Navarrow Wright about what is really happening with AI adoption and why the biggest barrier is mindset, not technology. They break down why prompting matters, why AI is not one-size-fits-all, and how access to these tools is more open than any previous tech shift. They also explore the real opportunity: using AI as a thought partner. From tools like NotebookLM to building without traditional technical skills, this episode shows what becomes possible when people actually understand how to use these systems. If you feel like everyone else “gets AI” and you do not, this is a great place to start. Links mentioned: * 📓 NotebookLM [ https://notebooklm.google/] * 📚 Gemini AI course [ https://grow.google/ai/ ] * 🧠 Prompting guide [https://platform.openai.com/docs/guides/prompt-engineering ] (OpenAI) * 💻 Navarrow: IG [https://www.instagram.com/navarrow/], YT [https://www.youtube.com/@NavarrowWright]

Algorithmic Transference, Generative UI, and Why the Text Box Won - With Louise Macfadyen

We’re joined by Louise Macfadyen, author of Designing AI Interfaces, to talk about how we actually design for AI, and why most companies are getting it wrong. We unpack “algorithmic transference” (why one bad AI experience makes you distrust all of them), the limits of the chat interface, and whether the text box is here to stay. Louise walks us through the history from command line → Google search → LLMs, and why designing for ambiguity is still one of the hardest problems in product. We also get into generative UI (and why it might be a trap), how large companies should actually integrate AI without breaking user trust, and why understanding user intent matters more than ever. Plus: vibe coding, personal AI “jigs,” and the tension between personalization and privacy. If you build products, or just use AI, this will change how you think about interfaces. 📘 Designing AI Interfaces [https://www.amazon.com/Designing-AI-Interfaces-Principles-Autonomous/dp/B0FYC7XRP7] · 🧠 Algorithmic Transference [https://dl.acm.org/doi/10.1145/3442188.3445922] · 🛠️ Claude Code [https://docs.anthropic.com/en/docs/claude-code]

Personal Agents, Opinion Geometry, and AI That Learns Too Much - With Hayden Helm

This week, Becca turns her birthday into a Twister masterclass by watching the movie with an AI “director’s commentary” running in real time (including some behind-the-scenes facts that sound… borderline illegal). Then Sara drops a mildly unhinged hot take: we might have already hit AGI—and we’ll never know it, because we don’t even agree on what “counts.” From there, we’re joined by Hayden Helm, CEO and founder of Helivan, to talk about the next wave of agentic AI: personal bots that don’t just answer questions, but act—with tools, permissions, and the ability to change over time. We get into: 1. Why agent behavior drift is the real risk (even when the bot still sounds “nice”) 2. The rising need for agent observability: detecting change, quantifying it, and rolling back when things go sideways 3. What happens when agents learn from the environment (and other agents), not just from you 4. Hayden’s work on “likeness” and opinion geometry—making messy human-ish behavior measurable 5. Why manual inspection won’t scale in a world of millions of autonomous interactions It’s a conversation about trust, safety, and the new security surface area we’re creating—one helpful assistant at a time. 🛠 Agent Infrastructure 1. OpenClaw [https://github.com/openclaw/openclaw] 2. Helivan [https://helivan.io] 🔐 Agent Payments 1. Coinbase x402 Protocol [https://www.coinbase.com/developer-platform/discover/launches/agentic-wallets] / Agentic Wallets 🧨 Agent Behavior Incident 1. “An AI Agent Published a Hit Piece on Me [https://theshamblog.com/an-ai-agent-published-a-hit-piece-on-me/]”

Agentic Romance Scams, Open Source Safety, and Anything Bad on the Internet - With Juliet Shen

Juliet Shen (Roost, formerly Snap, Grindr, Google) joins us to break down trust & safety — aka “anything bad that happens on the internet” — and why AI is changing the game for both attackers and defenders. We talk safety-by-design (how to bake guardrails into product), the real human cost of content moderation, and where AI can actually help without pretending it solves everything. Juliet explains how agentic AI scales old harms like romance scams from a handful of conversations to thousands at once — and why open-source safety infrastructure matters when bad actors share tactics faster than platforms do. We also dig into what Roost is building: Osprey (an investigation + rules engine) and Coop (a flexible review tool), plus the building blocks smaller teams need to ship products responsibly before the “weird edge cases” arrive. If you build products, this one’s a must. 🛡️ Roost [http://github.com/orgs/roostorg/] (GitHub + tools directory) 👥 Trust & Safety Professional Association [ https://www.tspa.org/] (TSPA) 🧩 Prosocial Design Network [ https://www.prosocialdesign.org/] 📚 Behind the Screen [https://yalebooks.yale.edu/book/9780300235883/behind-the-screen/] (Sarah T. Roberts — content moderation + human cost)