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?
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.
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.
Oh I think it'll help you successfully quit smoking, but man, quitting vaping is another animal in itself. The problem being that vaping is cheap (especially DIY), and it doesn't smell. So there's less incentive to quit, and if you do try holy hell the irritability is horrible for 2-4 days (nicotine withdrawal).
Java might be old, but it's still a long way from dead. And actually it could be argued that it's done a fantastic job keeping up with the demands of modern development. Kotlin and Scala are great, but there's still tons of need for and value in Java itself.
Swift? Um, okay... Good language, yes, but it's still very iOS-centric. I generally agree with the assessment of Python, but I'll stick with R for everything it can do. I use Python for everything else. If Swift breaks out of the iOS box then maybe I'll think about learning it.
I'm unclear from the website what exactly the pitch is. I really like the idea of a grayscale medium intelligence phone which helps counter the addictive nature of smartphones and is focused around the essentials: maps, camera, calendar, email, slack...
For some time my wife and I have both been wanting a dumber minimal smartphone, to help break our addiction to our phones without depriving us of their usefulness. This might be a good fit, but it's hard to tell from the website.
$0 demand? Are you kidding? If there was no demand then Bitcoin's price would be $0. It's not zero therefore demand is also not zero. This is basic economics. Come on, man.
No intrinsic value? How about how it is truly stored energy? It has a lot in common with gold. Just because it's digital doesn't make it's worthless. Lots of very valuable things are entirely digital these days.
Excel is remarkable, yes, but I'd argue that given its nature pretty much every reasonably complex workbook can be expected to have at least one bug. Having worked with them a lot in many different contexts, I've seen just how easily errors are introduced and I think they should never be used for research or finance where the cost of errors is high. At it's core the issue is that it's really hard to create variations and tests which can tell you if something is wrong... Much harder than it is to do this in a normal programming paradigm. Yes, the barrier to entry is lower, but the trade-off is much increased error rate and ongoing brittleness. Even if it's "right" at one point there's no guarantee it will be right in the future. What if someone copies/pastes data into a crucial worksheet and misses a column? It's so incredibly easy to screw up!
The TLDR; is that roughly 2,000 more people in the 25-34 age group started farming, which is a roughly 2% increase. Doesn't really sound like news to me, not yet at least. I'd like to interpret it as the younger generation getting back to their roots and more connected with real stuff (where food actually comes from, getting hands dirty, that sort of thing), but 2,000 people doesn't make a wave. I hope this number continues to rise and that as a society we become more _real_ in coming years rather than less. I.e., I think our society has lost something important the further we've gotten from our roots.