Professionals have large networks of neurons. They are sturdy and efficient from repeated use. Memory palaces help to start the construction of these large networks of neurons. Afterwards, as another commenter noted, the knowledge is deeply processed. Mnemonics are replaced by networks of meaning. It is no longer “This algorithm rhymes with tomato”, but “This algorithm is faster if the data is stored in faster hardware, but our equipment is old so we better use this other algorithm for now”.

Broadly, the progression of learning is: superficial learning, deep learning, and transfer. Check out Visible Learning: The Sequel by John Hattie for more on this.

Edit: To directly answer your question, experts have so many sturdy neural hooks on which to hang new knowledge that mnemonics become less and less necessary. Mnemonics may be particularly helpful when first learning something challenging, but are less necessary as people learn.

You could also check out a paradox called the expert paradox. We used to think memory is boxes that get filled. This idea was directly challenged by Craik and Lockhart’s Levels of Processing. Levels of processing supports the idea that “the more you know, the faster you learn”. Note that this is domain-specific. In other words, an expert in dog training won’t learn quantum mechanics faster than anyone else.

This reminds me of this video that shows how Italian food is a recent invention https://youtu.be/iZZfwyKa0Lc

I’d say feeling admiration for others. People who are kind, patient, insightful, and critical thinkers. People who look at how political goods (including wealth) are distributed and can think critically about it. Nutomic and Dessalines for sure.

On mobile atm but there’s the Princeton books on Computer Science

I like the novelty/predictability ratio idea. There is also the idea of “create expectations and satisfy them”, which leads to a sense of stability. Our cultures and genres create expectations. Rhymes tied to a certain metric can become part of these expectations. Of course, you can also create expectations and frustrate them, which leads to a sense of instability. Searching for “fakeout rhyme” videos makes this evident. Pat Pattison, an expert in songwriting, could be a good source on this ☺️

There’s also some thinkers who say that thinking only ever happens through language, so talking could be more of a mapping of “thinking words” onto “communication words”.

Yes! Rhetoric, the study of the available means of persuasion! Lots of professions still do that today: speech writers, advertisement creators, academic rhetoricians, some linguists, some anthropologists or sociologists, some historians…

It depends on the author! Authors create symbolic universes and they get to choose the rules of those universes. You can read Robert McKee’s work for more on this.

Thanks for the response. I guess I do see much of human behavior through a contextual behaviorist lens. Sorry if it seems excessive. I am not Hayes or Hoffman. It is just frustrating to see blanket explanations for human behavior, instead of understanding specific processes. I guess I really want to avoid the fundamental attribution error and reductionism, something contextual behaviorism deliberately aims to avoid.

While I recognize Emotion Focused Therapy is helpful to understand and, if possible, change social behavior (which is why I mentioned it previously), I maybe should have brought up Emption Construction Theory or even Sapolsky’s multi-lens framework, considering different timescales of explanation. Would you have suggested something different? When does contextual behaviorism fail?

Thanks for helping me potentially falling into reductionism. I wouldn’t want to fall in that trap.

Anytime we talk about human behavior, it is a good idea to learn and use the lens of behavioral contextualism. If and only if the contextual behaviorist analysis concludes that human connections is the issue, Sue Johnson’s texts will be great to understand your coworker. Otherwise, the contextual behavioral analysis will let you know what’s going on.

Edit: Removed excess text

I don’t get it. Can you give context?

Ultimately, yeah. The article points out that the way they want to do it is with unique designs, carbon neutrality, and transparency in the production chain.

I agree that we shouldn’t jump immediately to AI-enhancing it all. However, this survey is riddled with problems, from selection bias to external validity. Heck, even internal validity is a problem here! How does the survey account for social desirability bias, sunk cost fallacy, and anchoring bias? I’m so sorry if this sounds brutal or unfair, but I just hope to see less validity threats. I think I’d be less frustrated if the title could be something like “TechPowerUp survey shows 84% of 22,000 respondents don’t want AI-enhanced hardware”.

I MISSED THE EQUIVALENT OF PLACE IN LEMMY? Does anyone have context?

Agile is indeed more of a mindset than a rigid system. In my recent experience helping a tabletop game team, we applied Agile principles to great effect. Rather than trying to perfect every aspect of the game at once, we focused on rapidly iterating the core mechanics based on player feedback. This allowed us to validate the fundamental concept quickly before investing time in peripheral elements like the looks of the game.

This approach embodies the Agile value of ‘working product over comprehensive documentation’ - or in our case, ‘playable game over polished components’. By prioritizing what matters most to players right now, we’re able to learn and adapt much more efficiently.

Agile thinking helps us stay flexible and responsive, whether we’re developing software or board games. It’s about delivering value incrementally and being ready to pivot based on real-world feedback.

I appreciate your candor about not wanting to speak on topics outside your expertise. That’s commendable. I wonder if we can still talk with the understanding that we may not know it all. I truly believe curiosity is able to sidestep many of the problems related with ignorance.

You’re right to be cautious about appeals to authority. My intention wasn’t to suggest NASA’s use of Agile validates it universally, but rather to counter the OP comic’s implication that Agile is inherently incapable of achieving significant goals like space exploration.

Regarding Agile-like practices in earlier NASA projects, you’re correct that concrete evidence is limited. However, we can analyze their approaches through the lens of Agile principles. Scrum, for instance, aims to foster characteristics found in high-performing teams: clear goals, information saturation, rapid feedback loops, adaptability to changing requirements, and effective collaboration. These elements aren’t exclusive to Scrum or even to modern Agile methodologies. The key is recognizing that effective project management often naturally gravitates towards these principles, whether formally adopting Agile or not.

It’s an interesting area for further research: have complex engineering projects historically incorporated elements we now associate with Agile? If so, how?

Your skepticism is valuable in pushing for a more nuanced understanding of project management across different domains.

I can see you’re frustrated by the downvotes and pushback you’ve received. It’s understandable to feel defensive when your viewpoint isn’t well-received. I appreciate you sharing your perspective, even if it goes against the majority opinion here.

Your points about the space shuttle program’s challenges are valid and worth discussing. It’s important to note the timeframes involved though. The shuttle was developed in the 1970s, well before agile methodologies emerged in the 1990s and 2000s.

Interestingly, one could argue that NASA may have used agile-like practices in the space shuttle program, even if they weren’t labeled as such at the time. However, I did a quick search and couldn’t find much concrete evidence to support this idea. It’s an intriguing area that might merit further research.

Regarding modern agile approaches, while no method is perfect, many organizations have found them helpful for improving flexibility and delivering value incrementally. NASA’s recent use of agile for certain projects shows they’re open to evolving their methods.

I’m curious to hear more about your thoughts on software development approaches for complex engineering projects. What do you see as the pros and cons of different methodologies? Your insights could add a lot to this discussion.

Edgy meme: agile bad

NASA: “Yep, we use agile” https://ntrs.nasa.gov/api/citations/20160006387/downloads/20160006387.pdf?attachment=true

Your comparison is interesting, but let’s consider some historical facts. The Apollo program, which successfully put humans on the moon, actually employed many principles we now associate with Agile methodologies.

Contrary to popular belief, it wasn’t a straightforward Waterfall process. NASA used frequent feedback (akin to daily Scrums), self-organizing teams, stable interfaces so that teams are an independent path to production, and iterative development cycles - core Agile practices. In fact, Mariana Mazzucato’s book Mission Economy provides fascinating insights into how the moon landing project incorporated elements remarkably similar to modern Agile approaches. Furthermore, here’s a NASA article detailing how Agile practices are used to send a rover to the moon: https://ntrs.nasa.gov/api/citations/20160006387/downloads/20160006387.pdf?attachment=true

While it’s true that building rockets isn’t identical to software development, the underlying principles of flexibility, collaboration, and rapid iteration proved crucial to the missions’ success. Programs like the Apollo program adapted constantly to new challenges, much like Agile teams do today.

Regarding Kanban and Scrum, you’re right that they fall under the Agile umbrella. However, each offers unique tools that can be valuable in different contexts, even outside of software.

Perhaps instead of dismissing Agile outright for hardware projects, we could explore how its principles might be adapted to improve complex engineering endeavors. After all, if it helped us reach the moon and, decades later, send rovers to it, it might have more applications than we initially assume.

If you define methodological validity as surviving the “How can this be wrong?” or the “What alternative explanations are there?” questions, then it is easily dismissable. What alternative explanations are there?