A few, often slightly older, articles on the internet that I have come across and find interesting enough to share.
The Collectible Coins That Celebrate the Dark Side of American Policing
The first military challenge coins, one story goes, were handed out in 1969 by a US Army colonel to build camaraderie in his Special Forces unit. He took the idea from a National Guardsman who had required his troops to always keep a sixpence coin on them in order to buy drinks for their buddies. (Soldiers caught empty-handed during a “coin check” typically must buy a round.) By the 1980s, the silver dollar–size medallions had taken off in the military and beyond. Corporations gave them out to employees. Numismatists collected them. And as cops began equipping themselves and acting more like soldiers, they started minting their own. These law enforcement challenge coins often embrace the unpolished side of the “warrior cop” ethos—the violence, racism, and impunity that have sparked our current reckoning with American police culture.
There’s a widening gap between bold AI ambition and reality. Most organizations aren’t failing at AI because of the technology, but because their foundations can’t support it.
This report is quite uncritical of AI, but it shines the light on a very real problem – the differences in AI ambitions and the reality of a lot of companies. In my opinion, this is to a large part due to AI being oversold to the CEOs and boardmembers of companies, so they expect a lot more from it, than is realistic in most organizations. For example, AI has been promoted as a tool to make programmers up to a magnitude more productive, but we struggle to find any real evidence of this. If you base your strategy around 10x programmers, then it will not work.
Speaking of evidence for AI and system development:
Does AI Really Make Coders More Productive?
The big headline? On average, AI coding assistants give developers a 15-20% productivity boost across industries. That’s solid—imagine finishing your work 15-20% faster! But it’s not the same for everyone. Claims that developers see a ten fold (10x) boost in productivity are not very contextually helpful. Some teams saw huge jumps, while others actually got less productive. Why? It depends on a few key factors.
On top of that, I can add that this article from last year, showed that AI can decrease productivity in some cases:
Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
We conduct a randomized controlled trial (RCT) to understand how early-2025 AI tools affect the productivity of experienced open-source developers working on their own repositories. Surprisingly, we find that when developers use AI tools, they take 19% longer than without—AI makes them slower. We view this result as a snapshot of early-2025 AI capabilities in one relevant setting; as these systems continue to rapidly evolve, we plan on continuing to use this methodology to help estimate AI acceleration from AI R&D automation.
In fairness, I should add that they have found more AI-positive results in later studies, but they find their their own design lacking and states “We are Changing our Developer Productivity Experiment Design“
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