[pembrook]

> Without people who have actually worked with the system, you end up with a loss of tacit knowledge—and eventually, declining productivity.

> You are spot on w.r.t every assertion you've made.

Huh? What happened to the concept of "debate" on HN. It's just a bunch of people agreeing with each other. Yet the data doesn't support any of OP's thesis.

Here's a chart of the rise in productivity per hour worked in the United States since 1947. It's a steady linear increase every single year: https://fred.stlouisfed.org/series/OPHNFB

Yours is the type of story big company workers tell themselves to feel important while refusing to learn anything new and never taking any risks. But the truth is 99.999% of companies are not doing anything that unique or complex. Most companies are not ASML.

If I had a nickel for every time I've heard someone justify their do-nothing position within a giant bureaucracy while saying the phrase "institutional knowledge" I'd be rich. This is just a sign of a poorly run giant company full of engineers building esoteric and overly complex in-house solutions to already-solved problems as job security.

The truth is all of this "institutional knowledge" is worthless in the face of disruption, and it has a half life that's getting shorter every day.

Everybody talks shit about global just-in-time supply chains and specialization...but just because we had a fake toilet paper shortage for a few months during a 100-year global pandemic doesn't mean running things like it's 1947 for the last 70 years would have been better. You enjoy a much higher quality of life today due to these "evil" JIT supply chains which it turns out are far more durable than people want to claim.

[gzread]

Most measurements measured in dollars are just stealth measurements of inflation. Even inflation adjusted measurements, because official inflation metrics are always lowball numbers with shady methodology.

[jdw64]

US aggregate productivity metrics fail to address this nuance. There is a fundamental difference in abstraction layers between a macro-system becoming more efficient and an individual enterprise experiencing operational failure. As a software engineer, distinguishing between these layers is critical. Your argument is akin to claiming that because the Google Play Store sees a higher volume of app releases (increased productivity), the intrinsic quality of individual apps has naturally improved.

In this analogy, the individual app represents a company, and the Play Store represents the broader US market. Silicon Valley’s highly liquid labor market allows talent to flow freely, which opens up and elevates the baseline of the overall market. However, that is entirely distinct from the fact that individual companies are suffering severe drops in internal quality and productivity.

Furthermore, in software architecture, 'productivity' and 'quality' are rarely directly proportional. With AI coding tools, we can ship an app orders of magnitude faster. Historically, it took me three months to write 60,000 lines of code; recently, I am generating that same volume in just two weeks. My productivity has undeniably spiked, but can I confidently claim the code quality is better than when I manually scrutinized every single line?

The real issue is not whether the broader economy has grown more productive since 1947. The core issue is whether a specific organization bleeds capability when the exact people who understand its real-world constraints, failure modes, and operational history walk out the door.

Both realities can co-exist: National productivity can trend upwards, while individual companies simultaneously suffer operational regressions due to botched migrations, failed refactors, or the loss of tacit knowledge.

I agree that 'institutional knowledge' is sometimes weaponized to defend unnecessary complexity. However, the opposite fallacy is treating all localized, domain-specific knowledge as worthless. While some of it is merely job-security folklore, the rest is literally the only surviving documentation of why the system functions in the first place