1,208 karma · joined January 9, 2022
Also can someone actually understand the logic of joins, indexes, pks, etc enough to create an efficientand scalable db, and not simply have learned sql by proximity?
Reputational I was thinking leaking data, or generating wrong information for users etc
- 2 won't use AI at all and simply be left behind and stagnate (or go bust)
- 2 will partly use AI, and maybe keep up, maybe not
- 1 will go nuts vibe an entire app and explode (see Tea app or whatever)
- 4 will have an inefficient app, suffer reputational damage, lose some money, or similar, but probably survive
- 1 will hit the jackpot and get a 100M ARR company with 4 people.
Stats are of course completely made up, but you get the point.
Azure Copilot can charge whatever it wants because you can't use anything else.
I expect management probably didn't do as well as they could have too.
While tech has definitely enabled this shift, it doesn't seem overly relevant, outside of the current doomer views (albeit, it feels, valid views!)
Personally I'm anticipating agentic coding will be out of my price bracket (a single agent run costing US$20+ is far beyond what I can justify, especially with how often it fails). I'm planning on going back to optimised prompts on one-pass edits.
My sentiment exactly! I have a very similar scaffold to each of my prompts, and feel I provide similar context files, however sometimes I get a truly inspired, complex, and functionally complete response...and sometimes I'd have been better off running lorem ipsum through a python interpreter.
I can't find any rhyme or reason to success. I'm not sure if prompting is significantly more nuanced than I realise, or it's the statistical magic that's having a laugh at me.
>open source models on inference-optimized hardware.
Is this actually a thing? Or are you talking about some hypothetical "opus 4.7 ASIC"?
After a few weeks they'll settle on the documentation for raised garden bed and the implementation of a home defence sprinkler system.
All while leaving you with a $10,000 bill at the end of the month.
Ain't life grand.
I'm sure we built a lot of badly made stuff then too, but my guess is with our tighter manufacturing tolerances, we can push things closer to breaking point, with our increased casting/molding tech, we make stuff smaller and more complex, so it breaks more, we also drive harder to profit margins (unsourced claim!) so cutting corners/quality is more acceptable/planned obsolescence/planned failure.
The only approach I've found that works is no memory, and manually choosing the context that matters for a given agent session/prompt.
I've investigated a few options for non-admin wireguard on Windows and it's all pretty messy.
I'm either genuinely missing some key harness/whatever, or businesses are going to have issues down the line.
From my simple checks - and from Microsoft's own blog - per token pricing isn't going to be realistic for agentic coding either.
I think this is really telling. The cost of AI has really been masked HUGELY to drive adoption. The true cost is likely to be unsustainable for the big complex tasks (agents running for hours+) that companies have been pushing.
I was skeptical, then quietly bullish on AI, but I'm now seeing signs the market is cracking and the availability is going to receded/costs balloon.
I'd be curious what a better/non-legacy solution is! (as I do this stuff haha, and don't see much else other than full cloud options, sf etc)
Working more as a pair, or essentially doing code review as you go, in small chunks, is significantly better.
I personally don't have the setup of tokens to spend to say "go build this entire thing" and then review 15k loc. I also find even opus is poor at coming up with tests to justify the business logic it's meant to be implementing.
This fascination with ignoring that everyone in this disaster is the 'bad guy' (yeah including the US) is very bizarre.