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points by rbehrends 3 days ago | 0 comments
A couple of points.

First, it does not really reflect my experience. I find modern models to be largely interchangeable when it comes to common software engineering tasks, including some of the more recent open weight ones. The strongest models become interesting for Ph.D. level of work for me, which is not something I deal with regularly anymore.

None of them are perfect; they all have their strengths and shortcomings, but I can reasonably work with all of them and it honestly doesn't matter much anymore. I do sometimes wonder what exactly people are doing to see such a difference; at a minimum, their workflows must be very different from mine.

Second, you're arguing based on subscription pricing. But Anthropic makes the bulk of its revenue (and has its biggest margins) from enterprise/API pricing, where they are the most expensive provider by far. Anthropic isn't going to make a lot of money off your $20 subscription. With a subscription, you currently get more usage per dollar out of Anthropic's than OpenAI's plans, which approximately offsets the difference in API pricing.

[–] redox99 3 days ago
> I find modern models to be largely interchangeable when it comes to common software engineering tasks

If you think that, it means you're not demanding enough from your models.

Opus 5.5 still makes a lot of mistakes. Even if it can technically do all tasks you throw at it, there's no way it can do it at 100% reliability.

To be clear, AI writes 100% of my code since last year. But it still produces bugs, needs multiple prompts, and has less intuition than a human.

[–] rbehrends 3 days ago
If I'm not "demanding enough" from models, it's precisely because they are imperfect. Having them do long, complex tasks autonomously usually comes with more cleanup work afterwards IME.

My usual workflow (not counting throwaway code) is to use agents as virtual pair programmers, which gives me a good balance of quality and velocity.

Each interaction with the agent remains individually comprehensible and makes progress towards one of the following goals:

- Understanding the problem/solution space.

- Implementing a solution.

- Understanding the solution, especially any agent-written parts and interaction with existing code.

- Evaluating the solution (tests, code analysis, what-if scenarios, consider edge cases).

This does not just involve the model generating code, but also explaining or analyzing it as needed.

This process allows me to retain a mental model in lockstep with developing the written code and have some assurance both of its functionality and non-functional requirements. It also fits in nicely with most existing team-level workflows.

But it's also something that I can do with pretty much any of the modern models.

[–] redox99 3 days ago
Well that's kind of my point. Models still have a lot to improve. They are still imperfect enough that you don't trust them and have to use them as pair programmers.
[–] rbehrends 3 days ago
Yeah, but that's also a large part of why they remain interchangeable, I would say. I feel like we may be talking past each other?
[–] redox99 3 days ago
They are interchangeable maybe in your case. In my case for my tasks and for my product, Opus and GPT are at a level where I can vibe code with them and trust them, whereas the others aren't really there. When models get better they'll reach whatever point you need to be able to trust them.
[–] rbehrends 3 days ago
You said above that "Opus 5.5 still makes a lot of mistakes". This seems to contradict what you are saying here?
[–] redox99 3 days ago
Sorry just woke up, I wasn't being clear.

There's two thresholds.

1. Tasks models can do. 2. Tasks models can do with enough reliability that you can YOLO merge without looking at the code.

Most models can do most of 1. That's no longer the interesting part.

2. is quickly expand. I can trust opus 5.5 enough with easy to medium tasks that I can YOLO merge them. For open models, I can only trust them with easy tasks if I want to YOLO merge.

I'd love to have a stronger model that I can trust to YOLO merge hard tasks.

[–] agile-gift0262 3 days ago
But sounds like Opus and GPT are interchangeble for your case.
[–] redox99 3 days ago
Both have good models. My workflow these days is usually Opus plans and codes, then Opus and Sol review, finally Opus verifies the review and applies fixes.
[–] NoDodgeQuestion 3 days ago
Do you have example, open source you make using non-interchangeable model, that you can not make using other model?
[–] redox99 3 days ago
That wasn't my point, my point was that open models can technically do everything but they make mistakes more often. As an example imagine Opus makes a mistake every 5 prompts and Deepseek every 20. Because you still have a human in the loop, you tell it to fix that mistake and it does, but it's time wasted or bugs sneaking up on you.

Having said that, I was working on an AI for a certain video game, and I had Astra 6 and Sol 6/6.1 work for 30 hours straight, with some human steering to get it unstuck every now and then. It could not get it to work right, and the code it created was a mess.

When Opus 5.5 came out in like 4 hours it cracked it.

I didn't try but I'm very confident if Astra failed, the open models would've failed too.

[–] NoDodgeQuestion 3 days ago
Less time wasted or bugs sneaking are also good example, can you share video game AI example?
[–] redox99 3 days ago
Sorry it's proprietary but imagine a bot for a multiplayer videogame that can replace real players who disconnect mid game.
[–] cloverich 3 days ago
To clarify, i use both subscription pricing (personal use) and api pricing (at work). My spend going down was referring to api pricing, while using it more (for "everything").

Personal efficiency is noted as never hitting my limit despite it doing huge amounts of work at a time (ex: rewrite my notes app in swift for ios and install on my phone, 2 hours later its opened on my phone, looks nice, is working (base set of features). No follow up prompts, around 2 hours of work. 45% of my 5-hour limit.

Work efficiency is spend, task complexity, code quality (how often i have to steer - rare now), and wiring it up to more stuff (ex having it setup metrics and dashboards etc etc).

[–] bigwheels 3 days ago
I used to sing the same tune as you are now- "models are interchangeable". For today, all other models seems significantly dumber and waste more of my time than Opus 5.5.

tl;dr: You should try Opus 5.5 and report back.

[–] rbehrends 3 days ago
I have been using Opus 5.5 (as well as pretty much all frontier models). I am not sure why you think I haven't.
[–] bigwheels 3 days ago
It hinges on what you consider "common engineering tasks", this definition may not be shared amongst the audience.