Generative AI 101

Latest Episodes:

AI Conspiracy Theories: Happy Halloween 🎃 Oct 28, 2026

Show notes

In this episode, host Emily Laird airs her AI conspiracy theories and then does what most conspiracy theorists skip: she checks the footnotes. The evidence points away from secret basements and toward the unglamorous forces deciding who wins, including benchmarks that saturate in months, record lobbying budgets, and data center electricity demand on track to nearly double by 2030. She also argues that the riskiest part of an AI agent may be the permissions we hand it, and asks whether universities are learning to govern these tools as fast as they’re adopting them. No secret meeting required; ordinary incentives are doing the work just fine.

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Improve Your AI Written Emails Oct 27, 2026

Show notes

Polished emails are making managers less believable: when bosses let AI do most of the writing, the share of employees who rate them as sincere falls from 83% to as low as 40. Host Emily Laird explains why light editing costs almost nothing while AI-written feedback, persuasion, and sympathy quietly burn trust. She covers how to brief a chatbot instead of handing it a shrug, the “excess vocabulary” tells that give machine prose away, and practical fixes that keep your own voice in the inbox. Keep the tool, but know exactly where it costs you.

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From Messy Notes to Useful Work Oct 26, 2026

Show notes

Your AI meeting recap looks finished, but some of the owners and deadlines in it may be invented. In this episode, host Emily Laird argues that the real work happens in the forty minutes after the meeting, and that “summarize this” is the wrong request. She lays out a better system: extract the same seven fields every time, make the model write “not stated” instead of guessing, and ground every action item in the exact transcript line that supports it.

🎯 JOIN THE AI WEEKLY MEETUPS

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How to Make AI Actually Read Your Documents Oct 21, 2026

Show notes

A 130-page report lands in your inbox with a buried deadline, a half-million-dollar commitment, and one sentence that quietly rewrites policy, and your AI summary mentions none of it. In this episode, host Emily Laird explains why asking AI to make documents shorter is the wrong assignment, and how to interrogate them instead: commitment tables, version comparisons, skeptical-evaluator prompts, and the hunt for what isn’t there. She also breaks down evidence grounding and why no important claim should leave the chat without a page number attached. Confident, beautifully formatted, and occasionally wrong is not the standard you want to bring into a budget meeting.

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Please Be Kind to Claude Oct 20, 2026

Show notes

Anthropic now lets Claude hang up on abusive users, and Microsoft AI chief Mustafa Suleyman warns that training a model to wonder about its own feelings creates nothing more than an expensive echo. In this episode, host Emily Laird cuts through the headlines to explain what a “moral patient” actually is, why a cartoon sheep selling checking accounts proves Suleyman’s point, and why the off switch was never up for debate. The real fight is about vocabulary, training, and two companies planting brand flags on a question science hasn’t answered. You’ll walk away with practical habits for working with chatbots, from swapping insults for precise feedback to reading every AI self-report as output, not testimony.

🎯 JOIN THE AI WEEKLY MEETUPS

https://www.uwstout.edu/ai-weekly-meetup

📩 EMAIL REMINDERS FOR THE MEETUPS

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💬 CONNECT WITH EMILY LAIRD ON LINKEDIN

http://www.linkedin.com/in/meet-emily-laird

One Workspace to Rule Them All Oct 19, 2026

Show notes

If you are still explaining your job, your project, and your audience to AI every time you open a new chat, host Emily Laird has one question: why? This episode makes the case for AI workspaces (ChatGPT Projects, Claude Projects, Copilot Notebooks) where your files, standards, and past decisions live permanently, so your prompts can describe today’s task instead of rebuilding the entire universe around it. Expect practical advice on curating files, keeping a “Current State” document, and moving important conclusions out of chats, plus a plain-English take on RAG. There is also a catch: persistent context can make AI inherit your assumptions, so knowing when to start fresh matters just as much.

🎯 JOIN THE AI WEEKLY MEETUPS

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📩 EMAIL REMINDERS FOR THE MEETUPS

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💬 CONNECT WITH EMILY LAIRD ON LINKEDIN

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What is an MCP? Oct 13, 2026

Show notes

MCP, the Model Context Protocol, became the universal plug for AI this year, backed by Anthropic, OpenAI, Google, Microsoft, and Amazon and connecting assistants to the apps you actually use. The catch: your AI reads every connector’s tool descriptions, you don’t, and one poisoned line can turn an obedient assistant into a quiet leak. In this episode, host Emily Laird explains how MCP works, why tool poisoning and rug pulls have the NSA and Microsoft paying attention, and seven practical habits for connecting AI without handing out spare keys. Same plug, wildly different behavior, so know who’s holding the keys.

🎯 JOIN THE AI WEEKLY MEETUPS

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What is Meta's Muse? Oct 12, 2026

Show notes

Meta’s Muse is free, works through the night inside your email, calendar, and payment accounts, and makes its money by taking a small cut every time you buy something. In this episode, host Emily Laird reads the fine print on Meta’s new AI agent: the real guardrails (a Sentinel watchdog, one-time card numbers) alongside the catches (model training on by default, and a promised encryption lockbox that hasn’t shipped yet). She makes the case for permission scoping, which means handing over the valet key instead of the whole key ring, with practical rules for read-only access, smarter approvals, and weekly audit checks. If an AI is about to start shopping on your behalf, this is the reality check to hear before you hand over the wallet.

🎯 JOIN THE AI WEEKLY MEETUPS

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📩 EMAIL REMINDERS FOR THE MEETUPS

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💬 CONNECT WITH EMILY LAIRD ON LINKEDIN

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The 4-Part Formula for Better AI Results Oct 08, 2026

Show notes

Thursday, January 8, 2026

9:28 AM

Most people use generative AI like a search bar, type two vague words into the box, and then blame the model when it hands back beige, forgettable text. In this episode, host Emily Laird makes the case for treating AI like a colleague who needs a real assignment: a named deliverable, the right source material, and a clear picture of what finished looks like. She breaks down the Goal, Context, Source, Expectations framework, explains grounding (and how it prevents administrative fan fiction), and looks at 2026 research suggesting generic prompt advice can actually slow people down. The real upgrade isn't prompt wizardry: it's learning to write a clear assignment.

🎯 JOIN THE AI WEEKLY MEETUPS

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The Super Intelligence Accord Oct 07, 2026

Show notes

Six tech giants signed the White House Accord on Super Intelligence, a four-layer oversight pledge the president called "morally binding" (and published with the country's name misspelled under his signature). In this episode, host Emily Laird separates the ceremony from the machinery: what Google, Anthropic, Meta, OpenAI, xAI, and Nvidia actually committed to, why "nonbinding" is the word that matters, and what changed five days later when Washington launched the Super Intelligence Force. The real stakes are no longer about what AI companies promise, but about who is responsible when something goes wrong. Washington has given itself 120 days to figure that out.

🎯 JOIN THE AI WEEKLY MEETUPS

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