Great article. What LLMs mean for education is a big question.

My personal analogy is that Christopher Nolan studied English: learning how to think about a script is as important as the skills a director needs to make a movie (if even someone/something else does the work). Same for CS vs coding.

So true. Thinking first in terms of the tasks you want performed, before thinking about the agents you want to build, is a good order to go in.

Designing Data-Intensive Applications was an instant classic - nice to know 2nd ed. is coming!

My (limited!) experience is

- Forgive yourself your first recordings. You’ll get better, but first you must ship.

- You do get used to yourself. Enough so you’re focused on what you’re trying to achieve.

- The only criticism that really hurts is of your ideas. Same risk as writing them down!

The performance and editing are skills for sure.

“Artifice” implies dishonesty but it’s like learning an instrument: authentic performance takes lots of practice.

Without practice, the audience pays more attention to the quality of the performance than anything you actually say.

Good policy. LLMs are useful, but have also provided plenty of examples of how knowing when to say “no” is important!

Scenarios where including a viz guru is better/faster: cheaper:

- data needs wrangling
- viz work is 10x faster with data tools
- most data does not “speak” w/o normalisation, or variance, or cohorting, or …
- viz gurus make *interactive* tools
- can export viz to vector formats for design collab.

I’m in the camp that data vis is a great skill, have spent lots of time with d3.

But can’t think of any full time, long term, inhouse data viz specialists. Except maybe outsourced labour churning out dashboards.

Isn’t good viz work better paid as design, analysis, engineering, strategy, etc?

Great premise!