Better Offline – "How To Argue With An AI Booster, Part One"

Podcast: Better Offline
Host: Ed Zitron (Cool Zone Media & iHeartPodcasts)
Date: September 10, 2025
Summary prepared for listeners who haven’t heard the episode.

Episode Overview

In this first part of his three-part series on “AI boosters,” host Ed Zitron dives deep into the people fervently promoting generative AI, despite mounting evidence that the technology is not delivering on its promises. Zitron lays out the arguments and rhetorical tricks used by AI boosters, dissects industry data and media narratives, and arms listeners with responses and rebuttals to typical booster claims. The tone is sharp, skeptical, and often bitingly humorous, with Zitron positioning himself as both tech industry insider and professional critic.

Key Discussion Points & Insights

1. Setting the Stage: The AI Booster Phenomenon

• Defining "AI Boosters":

  • Zitron explains that AI boosters are not necessarily developers or daily users of AI technology but function more as fans, akin to diehard sports team supporters (14:12).
  • Their allegiance to AI is symbolic and tribal, making them more likely to proselytize and defend AI than the actual practitioners who build and deploy it.

• AI Optimism vs. Skepticism:

  • Zitron observes a vast double standard: skeptics are expected to rigorously defend their doubts, while boosters receive a pass for making optimistic, often unsubstantiated claims (03:42).
  • “To be skeptical of AI is to commit yourself to a near constant amount of demands to prove yourself…Conversely, being an optimist allows you to take things like ‘AI 2027’ seriously, to the point that you can write an entire feature length fan fiction piece in The New York Times and nobody will bat an eyelid.” (03:42)

2. Industry Reality Check

• Worrying Signs Behind the Scenes:

  • There’s mention of Meta restructuring (and downsizing) its AI department for the fourth time in a row—“which doesn’t seem like something you’d do if you thought AI was the future.” (04:29)
  • Markets are reacting negatively to new reports (MIT, Fortune) showing that “95% of generative AI pilots at companies are failing and providing no ROI.” (04:56)

• Debunking Myths About Generative AI:
  Zitron reads directly from the MIT study’s “Five Myths” section (06:09):

  • “AI will replace most jobs in the next few years.” (No, layoffs are limited and only in industries already affected.)
  • “Generative AI is transforming business.” (Adoption is high, but transformation is very rare.)
  • “Enterprises are slow at adopting new tech.” (Actually, 90% have seriously explored buying an AI solution.)
  • “The biggest thing holding back AI is model quality/legal/data and risk.” (Really, it's that most AI tools don’t learn or integrate well.)
  • “The best enterprises are building their own tools.” (Internal builds actually fail twice as often.)

• Zitron’s Core Point:
  Enterprises are “sticking their fingers in all the bits of the SaaS and it isn’t working. And the enterprise loves money. The enterprise will do, even if it’s a genuinely evil product, they’ll push it…[AI] doesn’t fucking work.” (08:25)

• User Resistance Is Not the Issue:

  • The problem is not that users are incompetent or resistant, but that AI tools “don’t do what they’re meant to do and people are really realizing it when they try and use them.” (09:27)

3. Tactics & Psychology of AI Boosters

• Boosters Thrive on Victimization:

  • They present themselves as the oppressed, “sneer and jeer and cry constantly” when others aren’t amazed by AI’s progress. (16:02)

• Symbolic Proof Over Reality:

  • The goal is not practical, demonstrable utility—it’s symbolic proof that the booster is on the “winning team.”

• Condescension & Gaslighting:

  • Boosters often frame skeptics as ignorant, stubborn Luddites, rather than address their concerns with evidence or clear argument.

4. Debate Tactics & How to Respond

Ed begins a recurring theme: defeating "booster quips"—the standard lines and tricks AI boosters use in argument.

a. “You’re just being a hater for attention / clicks.”

• Zitron: “Being a critic requires you to constantly have to explain yourself in a way that boosters never have to.” (20:40)
• Suggested response: Ask them to define what “attention” is, how critics supposedly monetize it, and how that's different than the attention boosters get by repeating AI hype in the media.

b. “You just don’t get it.”

• Response: Make it their job to explain what you’re missing—in concrete, personal terms, not vague anecdotes. (24:19)
• “If I don’t get it, it’s the booster’s job to tell me why. Make them justify their attitude.” (25:09)

c. “AI is powerful and getting exponentially more powerful.”

• Demand specifics: “What does powerful mean? How do these supposed benchmarks relate to reality?” (26:51)
• If they mention models passing coding or math tests, ask: Where’s the product? Where’s the new, transformative capability?

d. “AI will…” (Make revolutionary changes, replace jobs, etc.)

• Response: “Anytime an AI booster says ‘AI will,’ tell them to stop. Tell them to stop and explain what AI can do now.” (32:15)
• Push them for actual timelines and hold them to their claims.

e. “Agents will automate large parts of the economy.”

• Force specifics: Demand real working examples of these mythical “agents.”
• Cite Salesforce research: “Agents only have a 58% success rate on single step tasks…35% on multi-step tasks." (34:57)

f. “This is just like the early days of the Internet/smartphones.”

• Zitron calls this analogy false: “The iPhone was an immediate success…People paid for the iPhone immediately.” (37:55)
• The early Internet had low investment and obscurity, where AI is already massively funded and hyped—if AI was truly revolutionary, we’d be seeing obvious use cases by now.

g. “We’re in the early days of AI.”

• Counter: As of 2025, nearly 80% of Americans have heard of ChatGPT, over 34% have used it, and AI startups absorb the vast majority of VC money. These are not “early days.” (41:57)
• “The early days argument hinges on obscurity and limited resources, something that generative AI does not get to whine about.” (44:06)

5. Why the AI Booster Narrative Persists

• Massive funding and media attention keep the hype alive, even as practical results lag far behind investment.
• AI boosters have every institutional advantage—greater attention, more lucrative opportunities—yet cling to a narrative of being embattled outsiders.
• Zitron suggests Silicon Valley is caught in a “powerful follow-up culture that only one or two unique ideas can exist at one time…and those ideas are currently OpenAI and Anthropic.” (44:21)

Notable Quotes & Memorable Moments

• On booster mentality:
  “AI symbolizes something to the AI booster…a way that they’re better than other people.” (15:43)

• On the stubborn optimism of boosters:
  “No matter how blindly obvious evidence is to the contrary, they will find ways to ignore it.” (10:57)

• On the stats presented by boosters:
  “AI isn’t replacing anyone. Enterprises are trying to adopt generative AI, but it doesn’t fuck. And the thing holding back AI is the fact it doesn’t fucking work.” (08:50)

• On demanding specifics:
  “They will drag you toward what’s just on the horizon, but never quite define what the thing that dazzles you so much will be or when it will arrive.” (22:13)

• On ad hominem:
  “I do insult people. I do demean them. I call them babies and I do funny voices. And I do that because I don’t respect them.” (29:21)

• On AI’s real-world value:
  “Any product, especially software designed to make you feel stupid for not getting it, is poorly designed. ChatGPT is the ultimate form of Silicon Valley sociopathy. You must do the work to find the use cases and thank them for giving you the chance to do so.” (29:06)

Timestamps for Key Segments

• 03:09–10:00 – Framing the episode; defining boosters; new industry data on AI ROI; five myths about generative AI.
• 13:20–15:43 – What makes a real AI booster; symbolic vs. practical allegiance to AI.
• 16:00–20:40 – “Booster quips” defined; booster psychology; tactics of condescension and victimization.
• 20:40–29:21 – Concrete strategies to debate boosters: breaking down their favorite lines and how to respond.
• 32:15–44:21 – Refuting “AI will…” and “early days” claims; comparing AI and the early Internet; massive funding and exposure counter the obscurity argument.
• 44:21–End – Summing up; why the AI era may have “speedrun” straight to a bubble; preview of future episodes.

Conclusion

This episode is a methodical and deeply sardonic takedown of the rhetoric, psychology, and economics surrounding generative AI and its most zealous promoters. Ed Zitron provides listeners with both ammunition and a playbook for engaging with AI boosters—insisting on specificity, rejecting gaslighting, and remembering that any transformative technology ought to prove its worth without requiring faith or deference.

Listeners can expect more of this pointed, data-backed irreverence in the next two parts.