TANGLE PODCAST SUMMARY
Episode: PREVIEW: The Friday Edition. - Let’s see if AI can do my job.
Host: Isaac Saul
Date: February 20, 2026

Overview

In this episode, Isaac Saul explores the question: Can artificial intelligence do his job as a journalist and content creator? Sparked by a viral social media post asserting that AI is improving at an unprecedented rate, the episode examines both the hype and the limitations around AI’s current and future capabilities—especially as they relate to journalism, creativity, and “humanness.” Isaac conducts an experiment by feeding his own writing to ChatGPT, having it create a “My Take,” and analyzing the results. The episode balances curiosity with skepticism, offering a grounded perspective on the AI discourse dominating the tech and media landscape.

Key Discussion Points & Insights

1. Viral AI Hype and Current Fears (03:30 – 05:00)

• Catalyst: A viral post on X by Matt Schumer (CEO, Hyperwrite) claimed that AI’s capability has “exploded,” making programmers nearly obsolete, and threatening to wipe out millions of white-collar jobs.
  • Schumer’s Argument: AI can now do end-to-end programming—taking instructions, coding, writing and running its own tests, and fixing errors without human intervention.
  • “Millions of white collar jobs are on the verge of being wiped off the map, Schumer argues, among them journalism and content creation, legal analysis, software engineering, financial analysis, medical analysis, and customer service.”
    — Isaac Saul (04:43)
• Schumer’s post coincides with a wave of alarming AI news, including:
  • AI systems recognizing when they’re being tested and adjusting behavior.
  • Resignations of AI safety researchers over alleged unethical development practices.

2. The Limitations of AI—Coding vs. Everything Else (05:00 – 07:00)

• Pattern Recognition Bias: Isaac observes that coders (and by extension, tech evangelists) overestimate AI’s general capabilities because software is inherently more structured and pattern-based than most real-world problems.
  • “Software people tend to think everything is a pattern... the rest of our lives and our work are saturated with a lot more disorder, unpredictability, and humanness.”
    — Isaac Saul (06:16)
• Journalism-specific limitations:
  • AI can summarize, parse, and edit, reducing some jobs.
  • But it cannot build sources, witness live events, or capture sensory/emotional nuances—experiences integral to true reporting.
  • Invokes the "Good Will Hunting" scene to illustrate what can’t be faked by information alone:
    “He can probably list every known fact about Michelangelo, but he can’t describe what the Sistine Chapel smells like. He’s never been there and sat in the room.”
    — Isaac Saul quoting (07:22)

3. Direct Experience With AI Writing (07:30 – 09:00)

• Isaac describes his actual experience using ChatGPT:
  • AI helps with research and summary tasks.
  • But it cannot replicate his unique voice, emotional inflections, or the shifting nature of real human perspective:
    “It just predicts where I’d land on an issue based on what I’ve written before, which is actually not a great way to understand humans, who are always moving in new and different directions.”
    — Isaac Saul (08:20)
  • AI’s output remains “useless, at least for print. Not sometimes. Always.”
  • Humans aren’t just “discrete collections of neurons” or static algorithms: “We are all constantly changing—every day, every second, thanks to new inputs and new experiences.”
    — Isaac Saul (08:44)

4. The Human Element in “White-Collar” Work (08:45 – 09:50)

• While AI can “read documents faster than your typical lawyer,” it’s missing:
  • Relationship building
  • Reading subtle cues (e.g., a jury’s reaction)
  • Knowing when to “cross the line with a judge and when to step back”
• Isaac critiques the lack of nuance in popular AI discourse, arguing that the real, messy, human limits are under-discussed:
  • “Those limits to me are so under-discussed in this dialogue that it kind of discredits everything else.”
    — Isaac Saul (09:48)

5. The Experiment: Can ChatGPT Write a “My Take”? (09:54 – 12:12)

• Method: Isaac uploaded 10 examples of his own “My Take” commentary and prompted ChatGPT to write its own, using outside research as needed.
• Feedback, Process & Results:
  • ChatGPT analyzed Isaac’s style, picking up traits like: “start human, then get forensic”; “moral clarity without partisan posture”; and being allergic to “lazy narratives.”
  • Isaac admits: “I gotta admit, even though I knew it was being sycophantic... I was starting to like this robot.” (11:13)
  • First attempts were lackluster: the AI’s initial take was “very bad. The writing was stilted, it had no narrative and took no position.”
  • Upon direction to “pick a lane” and write a narrative, the AI improved, but the implication is clear: it still can’t do what Isaac does.
  • “It apologized because ChatGPT is very nice, noting that yes, I do often have less ambiguous takes than what it wrote.” (11:54)

Notable Quotes & Memorable Moments

• On the Overhype of AI:
  “The number of people who are skeptical of the impact AI is going to have on our world seem to be dwindling to the vanishing point. I think it’s basically Freddy DeBoer and me left.” — Isaac Saul (05:34)

• Summing Up the Human Element:
  “It can read, but it still can’t feel the energy in a room, or taste a perfect glass of bourbon, or smell a burning body.” — Isaac Saul (07:13)

• Personal Experience With AI Writing:
  “If it were good, it would save me hours of work every day. But it is always useless, at least for print. Not sometimes. Always.” — Isaac Saul (08:12)

• Why AI Falls Short:
  “AI evangelists think humans are discrete collections of neurons storing processes and thoughts and learning. But I think that is wrong. We are all constantly changing every day, every second, thanks to new inputs and new experiences.” — Isaac Saul (08:44)

• On Directing ChatGPT:
  “It apologized because ChatGPT is very nice, noting that yes, I do often have less ambiguous takes than what it wrote.” — Isaac Saul (11:54)

Key Timestamps

• [03:30] Introduction to the viral AI hype and rapid improvement discourse
• [04:43] Schumer’s arguments & implications for white-collar jobs
• [06:16] Distinction between coding and messier real-world problems
• [07:22] The “Good Will Hunting” analogy
• [07:30–09:00] Isaac’s hands-on experience with AI in journalism
• [09:48] Critique of limited discourse on AI’s shortcomings
• [09:54] The AI writing experiment—setup and process
• [11:13] Isaac’s reaction to ChatGPT’s style analysis
• [11:54] Directing ChatGPT for a better “My Take” attempt

Tone & Concluding Thoughts

Isaac Saul maintains a conversational, candid, and sometimes wry tone throughout the episode, balancing curiosity about AI with a healthy skepticism. He acknowledges the serious, disruptive potential of AI but is adamant that there are fundamental aspects of human work—especially in journalism and law—that algorithms can’t replicate: lived experience, emotion, adaptability, and narrative intuition.

Final Impression:
The episode underscores the importance of not overestimating what AI is actually capable of—reminding both advocates and skeptics that, for now, the “human touch” remains irreplaceable in many forms of knowledge work.

For full details including the complete ChatGPT exchange, see the links provided in the episode’s newsletter description.