Fair warning though, you'll lose all hope that companies like Microsoft will ever manage to produce anything that they don't then ruin.
you are implying that we still had any hope left in such endeavors.
I sometimes wonder what would happen if a company hired 100 software engineers, gave them all the same task to program the entire thing independently on their own, and then paid them as a monotonic function of the ranking of their output against their peers. (Obviously, there are limits on what type of product could be developed here, but I think this still encompasses far more company products than you would suspect.)
It’s creative work, like anything else. 1 is not necessarily always the right size, but 100 certainly isn’t. If you look at musical bands usually a sweet spot is between 1-6. You can add more in eg an orchestra or choir but everyone’s not involved in the creative work.
Then it depends on how well you vibe with people. If you have extremely unique ideas and thoughts, you may be better off alone. If you find peers with similar values, preferences and experiences, you might be fine with 5 people.
Most teams I've been on or managed were at their optimal efficiency with three people. Just enough to keep any one person from making too many poor decisions, but not to many to spend half a day in meetings.
On the topic of Microsoft/Linkedin, aren't they the ones who used to or maybe still assign the same task to multiple teams and let the teams compete for who can deliver? That does sound vaguely like what you propose.
So he asked me to write my own queries as well to see who was right. Lo and behold, my numbers didn’t match either of theirs at all.
This video explains everything I've seen in the enterprise IT of a huge government org that was the result of a long series of back-to-back mergers and splits.
It's exactly this!
Conway's law, but over time.
Dysfunction not just because of the large hierarchy, but also because of the built up layers of history. Some elements still limping along, some essentially amputated and mere phantom limbs of the org tree now, some outright dead and spreading miasma and corruption from their decay.
I knew or suspected most of this, but to hear it said out loud so clearly has crystallised my understanding of it.
Even if you know this, there is nothing you can do - you have to organize yourself somehow and how you do that can't be left up to just mirror whatever this piece of software that was brought in happens to be organized - because _that too_ doesn't reflect an actual org chart but is an integration over time of all org charts that have touched it.
I don't even know how to think about the implications this has for the use of open source software and how open source is developed, like... I think there are huge opportunities for research into Conway's law and how it relates to software development practices, software quality, etc.
We humans can’t effectively communicate with groups larger than about 7 people, but AIs have no such limits. We could all simply talk to one manager that can integrate everything and everyone into a unified whole.
It’s like the ship Minds in the Culture series having hundreds or even thousands of conversations at once.
"Not Just Bikes" has a good few videos, including https://www.youtube.com/watch?v=n94-_yE4IeU and a couple more that talk about problems that larger roads effectively cause more traffic ("induced demand", "traffic generation"). Organizational structures are like roads, and like roads they can get overloaded, which in turn means traffic needs to be reduced. There is even communication jam, and to combat that something like enforced communication reduction (lower information throughput), etc. to keep this manageable. That also causes decision making being done with less and less information the more steps are included in a communication chain (like upwards/downwards in a hierarchy), which in turn means the quality of decision making is severely hampered by it.
This whole mess is also the reason why the agile manifesto puts humans before processes and other such things, in fact it implies you change even the organizational setup to fit the project, not the other way around. But in the space of "managerial feudalism" (David Graeber) this is pretty much impossible to pull off.
Once again, seizing the term AI to mean LLMs and other current generative techniques has poisoned clear thinking. When we think "AI", we are thinking about HAL and Cortana and C3PO, which is not what we actually have.
Casey's example is focused on a (frankly, ridiculously) large organisation but I've seen the same thing in numerous small companies with just 20-30 developers, and it's hard not to imagine that this is universal, which is a pretty depressing thought.
Recently I've been involved in a new project where teams were set up to be 'domain-specific' with the idea that this somehow avoided the issues of Conway's Law, but this just feels like exactly the same problem because team structures and the software that they end up producing is siloed in exactly the same way as the organisation structures that existed at the time.
Casey's point that the final design is inherently limited by the lack of high-bandwidth communication between the groups of people that need it most is also fairly demotivating, personally.
Tangentially, having been writing more Golang recently this made me think of Golang's mantra (or was it Rob Pike's quote) of "Don't communicate by sharing memory; share memory by communicating.". Go/CSPs concurrency and sharing model is interesting, but I wonder if it's a fair analogue to compare sharing memory by communicating as low-bandwidth communication, and communication by sharing memory as the high-bandwidth communication that seems to be needed for effective designs.
I partially disagree. IIRC their search is broken, and their job alerts are pretty lousy at de-duplicating advertised positions.
And IIRC they hijack the back button, which I find pretty offensive.
Literally the opposite of LinkedIn. I’m approximately user 5000 on linkedin, and since I joined almost nothing useful has been added, despite a huge increase in complexity