It's revealing that the author thinks that a podcast is the ideal venue to reason through complex technical issues.<p>The "like" phenomenon is less of a verbal fluency issue and more of a cultural one. You can listen to someone smart like Donald Knuth speak and he will definitely stammer and stutter a lot, but he doesn't use filler words. "Like" is more of a West Coast or California thing and I also find it annoying and distracting.
Just a little more effort and STEM people will discover the social sciences. Cute.
>The people who know the most often sound the least certain<p>As was beautifully demonstrated in this article.
Not sure I agree with this. It's often true in SF, but that is largely an affectation, people imitating people like Peter Thiel etc. But not as true elsewhere
In medicine you want the doctor who's willing to admit "we don't understand the exact mechanism here" + also who wants more details from you before making a decision, vs confidently brushing you off and writing a prescription as fast as possible.<p>Lawyers will usually give much less-certain answers to questions like "is it legal to do X" than lay people as well because they're aware of much more nuance in the law. (Not referring to the wishy-washy corporate-law answers given to avoid liability here, but in outside convo about issues.)
<p><pre><code> The best lack all conviction, while the worst
Are full of passionate intensity.
</code></pre>
- W.B. Yeats
"The fundamental cause of the trouble is that in the modern world the stupid are cocksure while the intelligent are full of doubt."<p>Bertrand Russell
> while the worst
> Are full of passionate intensity.<p>sounds like the ideal entrepreneur to give funding to
Dude is using AI for a slop-post that complains that AI pundits are not persuasive enough and should take acting classes.<p>Really, the one thing missing in 2026 is more and better AI propaganda!
"As a rule, strong feelings about issues do not emerge from deep understanding." -Sloman and Fernbach<p>Also, the Dunning-Kruger effect still applies to smart people. You don't stop when you are estimating your ability correctly; as you learn more, you gain more awareness of your ignorance and continue being conservative with your self-estimates.