I think all of us could do with a bit of help increasing our intellectual humility, since “when it comes to our beliefs and opinions, most of us are much more confident than we should be”.

People who are intellectually humble know that their beliefs, opinions, and viewpoints are fallible because they realize that the evidence on which their beliefs are based could be limited or flawed or that they may not have the expertise or ability to understand and evaluate the evidence. Intellectual humility involves understanding that we can’t fully trust our beliefs and opinions because we might be relying on faulty or incomplete information or are incapable of understanding the details.

Read on for some recommendations on how to be more mindful of our own intellectual blind spots—and not just because it’s worth pursuing truth:

Despite our sense that we are usually correct, we must accept that our views may sometimes turn out to be wrong. This kind of humility isn’t simply virtuous—the research suggests that it results in better decisions, relationships, and outcomes.

Matt Rickard reminds us that it’s worth considering the long-term effects that putting public APIs behind paywalls might have on search engines:

Large models are trained on public data scraped via API. Content-heavy sites are most likely to be disrupted by models trained on their own data. Naturally, they want to restrict access and either (1) sell the data or (2) train their own models. This restriction prevents (or complicates) Google’s automatic scraping of the data for Search (and probably for training models, too). Google will lose results, site by site—it will be Google Search’s death by a thousand cuts.

Here’s some great advice from Robin Sloan on how to find good educational content on YouTube:

These days, when I’m investigating a subject, I tend to go straight to Low View Count Scholarly YouTube, which is of course the version of YouTube you get when you append the term “lecture” to your search. When you hit a tranche of videos between forty and ninety minutes long, with between 500 and 5000 views, you know you’re in the right place.

This Google experiment is interesting and kind of related:

To make it easier for people to learn about topics they’re interested in, we’re experimenting with AI-generated quizzes on the YouTube mobile app Home feed.

This is great post by Will Larson on the difference between personal (and organizational) “brand” vs. “prestige”—and why focusing on building the latter is way more important for your career than the former.

First, this reminder:

The majority of successful executives I’ve worked with don’t write online. They won’t post on Twitter or Mastodon. They haven’t written a book. They don’t speak at conferences. In your engineering leadership career, you will at times be immersed in the message that you need to be creating content to be successful, but there’s abundant evidence to the contrary. You absolutely don’t have to do this sort of thing.

And then, this definition of what he means by “prestige”:

Prestige is the passive-awareness counterpart to brand. Rather than being what someone actively knows about you, it’s what someone can easily discover about you if they look for it. Many interviewers won’t know anything about me, but a few minutes of research will find my writing, conference talks, and work history.

I agree with this. Make sure that if someone Googles you, they find your site where you can tell your story and showcase your work.

Why Do Developers (Actually) Hate Marketing? The Heavybit team has some good advice in this post:

• Don’t: Create product-led content that shoves the product into your reader’s face.
• Do: create a transparent guide to what your product can and can’t do. But make sure you don’t over-promise (or even sound like you’re overpromising).
• Don’t: Write thought leadership content that relies on cheesy trend predictions.
• Do: Create thoughtful, technical essays based on experiences from engineers and founders. But make sure your claims are authentic as well as relevant and well-supported as well as novel.
• Don’t: Produce hollow, manicured case studies.
• Do: Create technical case studies that describe, in detail, what a customer’s experience was really like – including the gains, the stresses, and the adoption and integration processes. But make sure the focus remains on the customer’s problem and not on your solution.

Good advice here from Kyle Poyar on how to optimize your pricing page, including a reminder to emphasize benefits, not features:

Did your feature matrix get dumped on your pricing page as-is, leading to confusion and eye-rolls across your target buyers? Don’t do that. Tell a story about what the customer can do with the feature.

The Homework Apocalypse is an interesting post by Ethan Mollick on how educators can prepare for (and, to a degree, embrace) the incoming prevalence of LLMs in schools:

Students will cheat with AI. But they also will begin to integrate AI into everything they do, raising new questions for educators. Students will want to understand why they are doing assignments that seem obsolete thanks to AI. They will want to use AI as a learning companion, a co-author, or a teammate. They will want to accomplish more than they did before, and also want answers about what AI means for their future learning paths. Schools will need to decide how to respond to this flood of questions.