To be fair, it's our own damn fault. "Poor stewardship over professional standards" is a succinct way of putting it.
The reasoning comes down to poor training, lack of standard competency tests (which is a stable goal to train for), and probably heavy disagreements about what a candidate should be capable of as a junior/mid/senior/principal, or at year 1, 2, 3, 5, etc. of their career.
Communication of these standards over blog posts and what you can find via search engines just won't - and hasn't - cut it for raising the competency of the industry as a whole. If you are competent, you can publish a book which becomes popular, but there would still be disagreement about what books are important.
As an example, Designing Data Intensive Applications is probably one of the more well-known books, but it's not a requirement to read that. The reason it's not a requirement is that you can meander through most jobs by just googling stuff and no one denies you a job if you can't talk about its content.
This problem has gone on long enough that most of us can't give a comprehensive list of what the "basic knowledge" is that we need. Most of us could try to make our own lists, but we'd be much less confident that that list should be the standard because it hasn't received any critical review and approval by a large sample of people.
We need to get out of this free-for-all thunderdome. We do that by getting the companies aligned on what they expect. Then they simply don't hire people that don't meet those expectations. Then we can start writing competency tests towards meeting those expectations and simultaneously develop training material to pass those tests. Most importantly, those standards cannot change too quickly otherwise we end up with the same moving target situation we have now.
You give me the training material, I pass a test, then I get a junior job and continue training for the expectations at various job title levels. It should be that simple.
To be fair, it's our own damn fault. "Poor stewardship over professional standards" is a succinct way of putting it.
The reasoning comes down to poor training, lack of standard competency tests (which is a stable goal to train for), and probably heavy disagreements about what a candidate should be capable of as a junior/mid/senior/principal, or at year 1, 2, 3, 5, etc. of their career.
Communication of these standards over blog posts and what you can find via search engines just won't - and hasn't - cut it for raising the competency of the industry as a whole. If you are competent, you can publish a book which becomes popular, but there would still be disagreement about what books are important.
As an example, Designing Data Intensive Applications is probably one of the more well-known books, but it's not a requirement to read that. The reason it's not a requirement is that you can meander through most jobs by just googling stuff and no one denies you a job if you can't talk about its content.
This problem has gone on long enough that most of us can't give a comprehensive list of what the "basic knowledge" is that we need. Most of us could try to make our own lists, but we'd be much less confident that that list should be the standard because it hasn't received any critical review and approval by a large sample of people.
We need to get out of this free-for-all thunderdome. We do that by getting the companies aligned on what they expect. Then they simply don't hire people that don't meet those expectations. Then we can start writing competency tests towards meeting those expectations and simultaneously develop training material to pass those tests. Most importantly, those standards cannot change too quickly otherwise we end up with the same moving target situation we have now.
You give me the training material, I pass a test, then I get a junior job and continue training for the expectations at various job title levels. It should be that simple.