AI adoption and IntelliSense
Complete off the top of my head thing, no source/research, just anecdotes and pontificating.
As i've been doing some heavy editing today of a 300+ line SQL query, one thing I'm wondering about with these AI usage stats are how much of the "adoption" falls into things like intellisense suggestions.
There's two parts to this, with the first being just bad suggestions.
I've found them to be "okay" for something like F#, but for SQL, which has always required me to knife fight for an alias to begin with, they're just utter garbage.
I normally don't blow through my free github copilot suggestions in my month (I'm not in the code mines as much anyways), but I blew through it in a day of shitty SQL suggestions (and then just turned it off). This was last month, so not even while dealing with the current monster, and I'm left wondering how many people just have it vomit out useless stuff they change anyways.
The second part, is just the usual "you don't really know your tools".
While doing this query I considered turning it back on or using it. I have several CTE's for readability as this is a prototype but it necessitates an annoying pattern of taking the names of your columns, uplifting them to the next query select, and then summing and renaming them AGAIN such as SUM(COALESCE(a.example,0)) AS [example]
When you have 84 columns to do this with, it can be tempting to let AI notice the pattern and just do it. However it's not actually necessary, and now that they're clocking the tokens as we knew they would, I'm back to just using my multi line editor skills. Middle click select, some home/end to get a starting point, then ctrl+shift+arrows mixed with Alt+arrows and some copy paste and I'm mostly done. Few Ctrl + D's or straight up find and replaces and I'd edited 80 lines in maybe 30 seconds?
AI would've been a bit easier, and from what i've seen of MANY coders, something I suspect they only think is doable through AI. However much like how AI is getting people to use features they never even knew existed in their business tools, I wonder how much adoption on the coder side is the same. All these text editor helper tools many coders don't use (please keep all VIM manifestos under 400 pages) suddenly being automated out by the VASTLY more expensive AI.
And like some of the other AI solutions, as the money starts to hit the budgets, I think we'll see a lot more "Look you need to learn how to do this normally" (or "hey guess what we're removing from VS code!").
Not sure I have an overall point to this, but I'd be curious to hear what other people are seeing in their environments.
I know this is off topic, but I would sooner cut my wrists than to manually work with so MANY columns like that lol. Edit: just reread my comment and sorry in advance if this part feels like I'm poking fun at you. That wasn't my intention, sorry!
I had a few situations kinda similar to yours. What I did was to list the columns I needed once in a Google Sheet, then make some formulas that automatically generated the SQL code I needed for the following CTEs. That way it was easier for me to keep track of the columns and I could also easily add or remove them in one place.
But back to AI, I find intellisense to be most useful is in small things, like changing a variable’s name. It usually spots that variable in other places and offers to fix them. Sometimes it also helps with small adjustments - like for example, just today I was swapping a few prints for logger functions, and once I changed one, it offered to swap the other 3 below. (This was python, to be clear)
But on the other hand, or I guess, 90% of the other time, it’s useless. It makes random suggestions and often nonsensical. And it struggles with lines of code that get a bit too complex, or are too long. I think behind the scenes, the AI only checks a handful of text near where your cursor is. That’s why it probably couldn’t deal with your 84 columns.
When it works, it saves time and it’s convenient, but that’s when it works… Which is only a few times in my experience… I can live without it.
Noooo worries. It's never fun. I mind this a little less than I used to, but SQL is just one of those languages where I feel like the tooling stopped making progress 20 years ago. There's sooo many obvious and repeatable patterns and issues and yet you're still fighting uphill most times when you start diving into a query.
Not sure which language/ide you use, but this is traditionally done with F2 in VS Code (or i think Ctrl +R R or something weird in VS proper?). Finds and replaces all instances of the highlighted variable (across the project if it's at that scope). Unless its sql...
Note: I'm budget-bound so I'm using Deepseek v4 Flash, not any frontier model.
First off, even for coding, I've been back on Leetcode recently and the chatbot can really just fail on an Easy implementation of a linked list.
For macro text editing, AI agents can leverage python or grep/sed to do them but they won't use them unless you suggest it explicitly. If you know vim I think it's just better, but I am not used to them yet. On the other hand, agents are quite nice at automatically scanning stray deprecated references when I'm in the midst of renaming.
I'm only a junior, but I do think at a certain level you have to be pretty comfortable with your means of input to a computer, no matter how much you have to customize one to fit. I use a very funky layout that nobody could use, which caps my ability on other people's computers.
AI agents was good for me with respect to doing workspace configs, as I can add or remove neovim plugins or change my terminal settings at will, because I couldn't sustain the attention to read plugin docs - A weakness on my part. With AI agents + web search I pretty much settled a neovim/wezterm setup in a day from zero. However I do think it takes some observation of which part of the tools are good, for example I see that I always like the Outline view to understand file structures in Zed for example, so I try to get one in Neovim.
With regards to coding, I pretty much have to have a system prompt written out that mimics my thinking flow, and have the agents ask me questions about intended behaviours first. I do think code generated from the corpus, rather than from my instructions, has a tendency to be overly defensive with checks, while not knowing how to encode invariants into types and all. Otherwise, it's pretty nice to create one-off tools (e.g python conversion of documents/slides) or quick demos (HTML page for me to compare design palettes)