The climate constraints are currently not compatible with the ongoing arm race on large neural networks models. The training seems kinda OK, but the inferences... and it's currently just rolled out as shiny gadgets. This really need to be rethought.

This browser is really an horrible data harvesting platform for Microsoft's benefit. They never learn...

It's been a while since I dived into reading a Ph.D thesis... I bumped into that one through an article which was trying to summarize it but I wasn't super happy with it. That's why I decided to go to the source.

It's an interesting read, it has the benefit of making a clear difference between complicated and complex from the get go, which is welcome (generally a good sign for me).
If you want the tl;dr it's at the end of page 16:
"we found that differences in architectural complexity accounted for differences in developer productivity of 50%, three-fold differences in defect density, and order-of-magnitude differences in staff turnover".

Note the last point about the staff turnover should be taken with a grain of salt though. It is well explained in the limitations of the study, being a lot in the high complexity areas of the code can also be a sign of higher skills and thus more job opportunities.

Anyway, I think we all suspected some link between complexity and productivity but I always wondered how much. Seeing how the study was done it's definitely not an absolute answer (very thorough and precise, even historical data taken into account over several releases... but in a single company). Still the value is in at last giving us some rough numbers on how far the impacts can go. Thus, the scale of those impacts are potentially huge.

Maybe it's time to stop trying to find rockstar developers or mythical 10x developers (common "leprechauns" of our industry)... Let's focus on tackling undue or uncontrolled architectural and code complexity instead, shall we? Even better if that's done through the use of documented patterns when applicable.

Interestingly, the literature review part gives a few clues about why there is under-investment in architecture in general, or reworking the architecture on long term project. It's unclear to organizations the costs of the undue complexity will carry. It's exactly what this thesis tries to shed light on (see tl;dr above).

Also, it's interesting to see confirmed that the perception of the architectural complexity we have is often wrong when looking at parts in isolation. The relationships need to be transitively mapped to start to grasp the presence of architectural complexity. That's why only coordinated efforts can tackle it, it's almost impossible to tackle for a single developer.

Of course I'd advise reading it in full, that requires investing some time into it though.

Very stimulating, I'd like to apply some of those tools on projects in the wild but I'm not sure there are ready made tools available. Also I'm wondering what we would find if I'd reuse some of those in ComDaAn to work on temporality of changes rather than dependencies. I think this could give interesting insights.

Interesting way to frame the potential problems around organizational culture. This indeed influence behaviors quite a bit so should be in check. It also shows it's a complicated problem you don't want to overdo it, freeze the culture in place, and see it used mainly for blaming... it'd effectively turn into a cult.

This is a good summary of the most important points in the PMI body of knowledge. If you dabble in project management it's worth looking at it.

Now, this is interesting research. With all that complexity, emergence is bound to happen. There's a chance to explain how and why. The links with the training data quality and the prompts themselves are interesting. It also explains a lot of the uncertainty.

Interesting japanese term. "Complete what was originally intended". A few more proposed at this end of this short post.

This is a huge! DreamWorks Animation releasing its rendering pipeline as free software.

The lack of transparency is staggering... this is purely about hype and at that point they're not making any effort to push science forward anymore.

Nice exploration of Django + HTMX + web components for a CRUD use case. Interesting insights and highlights some of the limitations with HTMX.

Definitely this. Having "heroes" brings obscurity and hide the problems, this prevents management from knowing and handling the issues. This also create lots of missed opportunities for collective learning and improvements.

Excellent post about getting too invested in a single tool. We can loose flexibility in the process. Also in the case of React, I didn't realize until now that half of the web developers have never known a time when React didn't exist!

Well, people asking relevant questions slow you down obviously... since the goal about the latest set of generative models is to "move them into customers hands at a very high speed" this creates tension. Instead of slowing down they seem hell bent at throwing ethics out of the window.

Looks like it completes Comby nicely for the search only case.

Definitely this. If it's too fancy and fashionable you're likely to pay it in later with the undue complexity it introduced.

Une histoire édifiante sur le sexisme ordinaire... et tout le monde regarde ailleurs.

Interesting advises for higher management roles. The information gathering and the distorsion fields are key factors to have in mind to not loose perspective. Otherwise it's when you'll start doing more harm than good.

Indeed, it's important for architects to get their "hands dirty". Organizations where it's not the case prevent their architects to challenge their assumptions pushing them to stay in their ivory tower. It's a good way for bad decisions to pile up over time.

Interesting, this seems to empirically confirm the Peter Principle, at least in sales. Also shows that companies are trying to workaround it. Dual career ladders seem to be an interesting path for this.

Very import milestone for brain mapping. Far from more complex animals of course and an insane amount of work each time. Still the common fruit fly is already revealing interesting new facts about neurology.