Frankly, it sounds like you have a lot to learn about agentic coding. It’s hard to define exactly what makes some of us so good at using it, and others so poor, but agentic coding has been life changing for myself and the folks I’ve tutored on its use. We’re all using the same tools, but subtle differences can make a big difference.
I completely and utterly disagree. Simon is no gifter. Intellectually lazy snobs think that any time someone has genuine delight and excitement about something that they’re “grifting.” Also, for anyone who is trying (regardless of whether they are succeeding) the to make money—that isn’t synonymous with “grifting.” God, some of you need a better relationship with a dictionary.
Plus, it seems some of y’all love to hate the very industry which puts a roof over your head. You’re hoping and praying that it all burns down—yet where will that leave you? How do you feel about becoming a plumber—-until the robots take that job?
> Plus, it seems some of y’all love to hate the very industry which puts a roof over your head. You’re hoping and praying that it all burns down—yet where will that leave you? How do you feel about becoming a plumber—-until the robots take that job?
This probably isn't a line of argument you want to go down. I've been unemployed for 7 months, in part due to how difficult it is to get so much as an intro call because so many people have totally automated the process of spamming every open job posting with as many resumes (many of which were likely LLM-generated as well) as possible.
Agreed. As a data scientist myself, I can't imagine Julia getting much "mindshare" among us with the JIT experience it has. Perhaps we're not the real target audience for Julia? But if that's the case then adoption will likely be slow, and limited to only very niche applications and roles. For Julia to really become the next big thing (and solve the damn two language problem), it needs to be an effective solution for data scientists and machine learning engineers--and right now, it just isn't.
I do machine learning and computer vision in python, statistical analysis, plotting, and anything to do with dataframes in R, and computational stuff, network science, and almost everything else in julia. I would like to switch my data analysis stuff to julia but waiting for libraries and functions to load is just too frustrating when I'm doing things interactively. I'm hoping Julia will have a good machine learning, computer vision, and data science environment in the future and it is looking like it will. But for now, it is not an easy environment to work with in these applications and you'd need some fairly specific needs to justifiably use Julia here. But the thing is that when you do have relatively esoteric things to do in these applications, it is much easier to do them in Julia.
Yeah, this has been my experience as well. I really _want_ to like Julia. But so far the JIT experience has been exceptionally miserable--and unfortunately for me, my typical approach to development is quite interactive. I'm on 1.1.1.
Julia's compiled code might be super fast, but developing (or, God forbid, doing any sort of analysis) is painful because of how brutally slow the REPL/interactive environment is. Pretty much every little snippet of code you'll want to test as you write Julia feels like it takes _forever_ to run. I don't know if there's a solution for this while retaining the compiled run-time performance. I'm new to Julia (from R and Python), but I find the slowness/sluggishness of REPL to be nearly a deal breaker for me. It feels like the web back in the 1990s when you'd click a button and wait, and then click another button (or link) and wait, etc.
Ugh. MBAs? No thanks. Usually it's interactions with MBA-holding folks that gives me heartburn. They try to mechanize everything. I agree that an MBA education is probably fairly useful for developers, as long as you can retain your perspective and balance the two worlds--they are very different after all. I'm _very_ business-minded (though I don't have an MBA) and I still run into extensive frustration when I get these kind of queries from the business: why is this taking so long? As this article laid out well, the change or new feature is often conceptually simple but there can be _so_ much required to make conceptually simple things actually happen. Unless you have real development experience before becoming "management", I doubt it's possible for a developer to truly convey that complexity to you. Ultimately it ends up becoming a matter of trust, and frequently competent managers realize over time something along the lines of "well, if every developer I've ever had has taken a long time to deliver conceptually simple things then perhaps that means there's a lot to do to deliver things I think are simple." Sadly, there remain some managers who remain convinced, in the face of all evidence to the contary, that all developers are lazy, slow, and just need to be whipped more and harder.
Yes, this is why it's critical to adopt an output/outcome mentality. When you can't see if or when we're working the only signal of status is whether shit is getting done. This should be the only thing you care about, and it should be super obvious of you're project managing correctly.
Agreed. I would summarize modern society the same way. In some ways life is vastly improved over prior generations, but I think that masks an alarming amount of b societal decay.
Your listed Do's are great, and I'll add the following:
Do:
- Read my profile and make it clear in your email or message why you think the position is a good fit (referencing details from my profile)
- Be personable and real with me. The more I feel like a random number to you, the less I'm likely to respond. I'm simply too busy for low-quality inquiries.
Don't:
- Require salary verification at any point in the process. These days it's offensive.
- Blast out inquiries to anyone who has a keyword in their profile
- Be uniformed about how and why I might be a tremendous fit.
