In other words, moving money/spend from non-AI projects to AI projects/cost. This includes trimming the bottom X% of performers to reallocate that money too.
In most cases, it is not about current productivity or AI doing people's jobs.
Could the limited MCP support be due to security concerns?
I've seen a number of stories about LLMs going rogue and messing things up (dropping databases, making unwanted changes, etc). Also, apparently there are security concerns with the MCP protocol itself.
Having dabbled a bit in astrophotography, I would suggest that color is best used to bring out the structure (and beauty) of the object. Trying to faithfully match the human eye would, unfortunately, cause a lot of that data to be harder to see/understand. This is especially true in narrowband.
The article below claims that milder store-bought peppers are the result of growers using different varieties, which is driven by larger (factory) consumers of the peppers.
I found it helpful in understanding the underlying causes of my own feelings of burnout. Also, don't be put off that the book says it's for women. The core lessons seem to apply to everyone.
I used to work at a CMMI Level 5 (certified) shop. The process was inevitably tailored to the lowest common denominator. It was meh.
We used to say that the process will never turn a mediocre engineer into a good one but it will absolutely turn a good engineer into a mediocre one.
In general, I've observed that a lot of these heavyweight processes are used as a substitute for high quality engineering leadership. They are not a good substitute.
When I've seen this happen it usually boils down to communication problems. The solution is often to talk to the reviewers _before_ writing the PR.
For example,
1. Disagreement about the problem/solution - hash out the design first, then write the code
2. Disagreement about priorities - align expectations before investing too much time in design or code
3. (etc)
Yes, communication is hard. Unfortunately, it's really the only way to get things done with other people. Building decent communication skills is a worthwhile investment for all SWEs
Mark Twain is often quoted as saying, "I apologize for such a long letter - I didn't have time to write a short one."
In my experience, simple solutions are not the lazy minimal-effort ones. It takes a lot of work to distill complex problems down into simple solutions.
There is earlier research[1] from the same authors showing the opposite effect. It's unclear to me what changed.
One thing I noticed is that the earlier research took into account productivity increase of the employees due to less commuting time. This certainly benefits the employee and probably the overall economy, but maybe not the employer.
I found it helpful in understanding the underlying causes of my own feelings of burnout. Also, don't be put off that the book says it's for women. The core lessons seem to apply to everyone.
In other words, moving money/spend from non-AI projects to AI projects/cost. This includes trimming the bottom X% of performers to reallocate that money too.
In most cases, it is not about current productivity or AI doing people's jobs.