> I expected to see measures of the economic productivity generated as a result of artificial intelligence use.
>Instead, what I'm seeing is measures of artificial intelligence use.
Fun fact: this is also how most large companies are measuring their productivity increases from AI usage ;), alongside asking employees to tell them how much faster AI is making them while simultaneously telling them they're expected to go faster with AI.
productivity is such a nebulous concept in knowledge work - an amalgamation of mostly-qualitative measures that get baked into quantitative measures that are mostly just bad data
And in a business you can easily measure total profit and divide by total hours worked.
When you try and break it down to various products and cost centers is where it comes unstuck. It’s hard to impossible to measure the productivity of various teams contributing to one product, let alone a range of different products.
On the contrary. I like agile for when you don’t know exactly what you’re building but you can react quickly to change and try to capture it.
Moving fast and breaking things, agile.
On the other hand. When you know what you want to build but it’s a very large endeavor that takes careful planning and coordination across departments, traditional waterfall method still works best.
You can break that down into an agile-fall process with SAFe and Scrum of Scrums and all that PM mumbo jumbo if you need to. Or just kanban it.
Knowing exactly what you want to build is pretty rare and is pretty much limited to "rewriting existing system" or some pretty narrow set of projects
In general, delaying infrastructure decisions as much as possible in process usually yields better infrastructure because the farther you are the more knowledge you have about the problem.
...that being said I do dislike how agile gets used as excuse for not doing any planning where you really should and have enough information to at least pick direction.
If someone comes to you and says: "I want to build a platform that does WhizzyWhatsIt for my customers, it has to be on AWS so it's mingled with my existing infrastructure. It needs to provide an admin portal so that I can set WhizzyWhatsIt prices and watch user acquisition make my bank account go brrrrrtt. It needs the ability for my quazi-illegal affiliate marketing ring to be able to whitelabel and brand it as their own for a cut of the profits."
This is obviously satire but there's a clear ask, some features, from there you know what you need to have to even achieve those features, what project management process would you employ? Agile? Waterfall? Agile-fall? Kanban? Call me in 6 months?
Probably waterfall stuff that have actual clear functions and integrations (if you can extract all that system gets and what it does with it there is no reason to agile it) then slowly get thru the current mess, documenting it at each step while trying to replace it with something better.
Replacing existing system (and especially one you didn't write) is pretty much always the hardest case.
Nice way to make all that data meaningless. I already know some people who’s jobs have pushed adoption of AI tools and it’s clear that whether or not it meaningfully impacts their speed it is not going to do them any favors to say it doesn’t even when it does not
>Instead, what I'm seeing is measures of artificial intelligence use.
Fun fact: this is also how most large companies are measuring their productivity increases from AI usage ;), alongside asking employees to tell them how much faster AI is making them while simultaneously telling them they're expected to go faster with AI.