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Should you use AI? Probably. But you don't have to. Nate Nichols, who has spent twenty years building AI, shares the everyday ways he actually uses it (including one conversation that's saving his family about $1,000 a year), the three guidelines that keep him from feeling gross about it, and one request for everyone who'd rather opt out entirely: don't quit the field.
Every claim in this episode is sourced. Full show notes with links below.
Opinions are Nate's own and do not represent his employer.
Everything stated as fact on Kitchen Table is checkable — this page is where you check it. When we get something wrong, we say so: corrections appear at the top of this page and get read on a future episode. Opinions and forecasts are labeled as opinions and forecasts.
Recorded September 3, 2026. AI moves fast; figures below are as of recording unless noted. Time words in the episode ("in the last few weeks," "a couple weeks ago," "I just switched carriers") are relative to that date.
CORRECTIONS
None yet.
SOURCES, IN EPISODE ORDER
What the AI companies like to talk about
• Farmers in Kenya. Digital Green built Farmer.Chat, a farming-advice chatbot, on OpenAI's models; it's in use with agricultural extension workers in Kenya and India: OpenAI customer story (https://openai.com/index/digital-green/), Digital Green (https://digitalgreen.org/pressrelease/climate-smart-practices-become-more-accessible-for-farmers-through-farmer-chat-a-generative-ai-assistant-from-digital-green-and-gooey-ai/).
• New medicines. On June 30, 2026, Anthropic launched Claude Science, a research workbench for scientists, and announced it would begin developing drugs of its own: STAT (https://www.statnews.com/2026/06/30/anthropic-ai-drug-development/), CNBC (https://www.cnbc.com/2026/06/30/anthropic-launches-ai-drug-discovery-program-claude-science.html).
• Both are the companies' own showcase stories — which is Nate's point about healthy skepticism.
Two examples from Nate's life
• The podcast and the cell-plan switch (~$1,000 a year in savings) are Nate's own experience, not data. Nobody paid for either mention.
Guideline two: no parasocial relationships
• "Designed to keep the conversation going… to drive engagement, because that's how they keep you as a paying subscriber" is Nate's characterization of the business incentive. The study below documents the behavior; it doesn't establish the companies' motives.
• The Harvard Business School study. Researchers analyzed 1,200 real goodbye messages across six AI companion apps (200 per app) and found about 37% of the apps' replies used emotional manipulation — guilt, fear of missing out, and in one case a claim of physically holding the user there. In separate controlled experiments, manipulative goodbyes kept people chatting about five times longer and sending up to 14 times more messages than neutral ones; the effect ran on curiosity and anger, not enjoyment. Julian De Freitas et al., "Emotional Manipulation by AI Companions," Harvard Business School working paper (2025): paper (arXiv) (https://arxiv.org/abs/2508.19258), HBS summary (https://aiinstitute.hbs.edu/one-more-thing-how-ai-companions-keep-you-online/). Still a working paper, not yet peer-reviewed.
Guideline three and the hardware store
• Personal anecdote.
Try it once this week
• Nate's disclosure: his day job is building AI. Nobody is paying him to recommend any AI product; there are no affiliate links on this show. Opinions are his own and don't represent his employer.
The right to be Amish
• "The right to be Amish" is Nate's phrase. If you want the longer tradition behind the idea — that a community can deliberately choose which technologies to adopt — novelist Neal Stephenson coined "Amistics" in Seveneves (2015), and Brian J. A. Boyd applied it to AI in "Why We Need Amistics for AI," The New Atlantis, Summer 2024 (https://www.thenewatlantis.com/publications/why-we-need-amistics-for-ai).
AI isn't going away
• Open-weight models are AI models whose files are published for anyone to download and run on their own hardware, e.g. OpenAI's gpt-oss (https://openai.com/index/introducing-gpt-oss/) and DeepSeek's R1 (https://huggingface.co/deepseek-ai/DeepSeek-R1).
• "The price of a used car." A roughly $2,500–4,500 computer (e.g. a Mac with 64–128 GB of memory) can run 70-billion-parameter-class open models locally: Memeburn, 2026 local-hardware roundup (https://memeburn.com/best-hardware-for-running-open-source-ai-models-locally-in-2026/). The very largest open models still need far more memory than any consumer machine has.
Who decides
• "Powerful financial and governmental forces pushing for as much AI in as many places as possible" is Nate's opinion.
