This week Nik and Dan look at what designers lose, and gain, when AI does more of the work. They start with Anton Sten’s essay on building a design system with an AI agent and no longer knowing it by heart, and debate whether a better-documented system makes up for designers no longer carrying it in their heads. Next is an MIT paper from UIST 2026 that predicts what people will say next. Then they cover Anthropic’s study in which professional analysts went along with Claude Code’s secretly coin-flipped recommendations 86% of the time, often repeating its reasoning as their own. They discuss design responses: tracking which ideas came from the AI, having agents argue both sides, and asking for the human’s view before showing a recommendation.

In the second half, Nik talks with Nicole Donnelly, founder of AI Smart Ventures. She explains why teams learn faster when people across departments share how they use AI, why technical teams tend to overbuild and MVPs have to stay small, and why she thinks retiring shareable custom GPTs and Gems in favor of skills will shut out non-technical workers.

LINKS
The System I No Longer Know By Heart (Anton Sten)
https://www.antonsten.com/articles/the-system-i-no-longer-know-by-heart/

Before You Say It: Anticipating Verbal Behavior from Longitudinal Everyday Conversations with LLMs (Samaradivakara, Danry, Liang, Maes)
https://arxiv.org/abs/2608.13454

How AI Agents Shape Experts’ Judgment Calls (Anthropic)
https://www.anthropic.com/research/agents-judgment-calls

AI Smart Ventures
https://aismartventures.com

Episode 40 starts with a quick note that it’s launch week for Dan’s debut novel, The Restoration, then turns to the week’s news. Nik covers Anton Sten’s method for giving AI structured context with two markdown files: a chronological running-notes log and a stricter decisions log with the newest entries first. Dan then walks through Casey Winters’ interviews with product managers about how AI has changed their work. PMs are shipping more without matching business results, prioritization has to be relearned now that engineering scarcity no longer forces it, and trust in AI drops as PMs’ workflows get more sophisticated. Last, they discuss Ron Goldin’s case that “product designer” no longer describes a job, and his replacement of four attributes: Style, Strategy, Builder, and Operator.

In the second half, four recent CMU HCI graduates describe what entering the field is like right now. Lisa, Nava, and Qiyu work in design roles, and Sean is a PM. They talk about a brutal job market (Sean’s company got roughly 80,000 applicants for 14 new-grad roles) and about roles blending as designers write PRDs and PRs they can’t fully verify. They also talk about mentorship increasingly coming from engineers, LinkedIn, and Claude itself. Their organizations handle AI very differently: one product team has banned AI-written PRDs because everyone’s agents reached the same conclusions, while elsewhere design is the last step still done by hand. Their advice to students and educators: learn by doing, build with AI out of curiosity rather than FOMO, keep returning to first principles, and make sure you are the one who actually understands the work.

LINKS

Dan's debut AI novel The Restoration
https://mybook.to/TheRestoration2176

Where Decisions Live – Anton Sten
https://www.antonsten.com/articles/where-decisions-live/

How PM Work Is Changing in the AI Era – Casey Winters
https://www.caseyaccidental.com/p/how-pm-work-is-changing-in-the-ai

Product Designer Is No Longer a Job Description – Ron Goldin
https://rongoldin.substack.com/p/product-designer-is-no-longer-a-job

Gartner Hype Cycle
https://www.gartner.com/en/research/methodologies/gartner-hype-cycle

Fresh off their first live show, Nik and Dan look at three stories about who gets to shape what AI shows us. First up is OpenAI’s Intelligent UI, which lets GPT-6 build small interactive interfaces (charts, forms, buttons, maps) inline in ChatGPT instead of returning a wall of text. They compare it to Claude Artifacts, argue that speed is what makes it usable as a default, and ask what happens when companies like QuickBooks have to hand over a design system for their product to show up inside someone else’s chat window. Is ChatGPT becoming an operating system that generates apps on demand, across the silos our tasks currently live in?

Next, Facebook’s “Your Algorithm” lets people steer their Feed and Reels in plain language. Dan draws on his time at Twitter and the promise of Bluesky’s algorithm marketplace; Nik wonders whether more control might raise engagement rather than lower it, and how this data could feed Meta’s Muse agents. Finally, UserTesting has rebranded as Auros and is pivoting toward AI training and evaluation with verified human experts. Its new AI Relationship Quality (ARQ) benchmark measures trust, affinity, and control alongside technical performance, which leads to a frank conversation about why benchmark gains don’t always produce models that are pleasant to work with, and whether ARQ could become the NPS of AI.

LINKS

OpenAI Wants ChatGPT to Stop Looking Like a Chatbot (Gizmodo)

https://gizmodo.com/openai-wants-chatgpt-to-stop-looking-like-a-chatbot-2000823211

Facebook Is Giving Users More Control Over Their Algorithm (TechCrunch)

https://techcrunch.com/2026/10/13/facebook-is-giving-users-more-control-over-their-algorithm/

UserTesting Rebrands as Auros, Aims to Bring Humans into AI Experience (Constellation Research)

https://www.constellationr.com/insights/news/usertesting-rebrands-auros-aims-bring-humans-ai-experience

Auros Adds ‘Human Elements’ to AI Evaluation (Daily Research News)

https://www.mrweb.com/drno/news40429.htm

Dan’s debut AI novel The Restoration (2176, Book One)

https://link.amazon/B05GcHBe7