Comment by dr_dshiv
6 days ago
“I wanted to see if I can get in on this 10x magic. I decided to put my money where my mouth was and I bought $10 worth of DeepSeek credits to use with a project I was working on.“
Wow. I guess that’s the punchline!
6 days ago
“I wanted to see if I can get in on this 10x magic. I decided to put my money where my mouth was and I bought $10 worth of DeepSeek credits to use with a project I was working on.“
Wow. I guess that’s the punchline!
I'm sure DeepSeek isn't the point here. You can change the name to whatever you prefer and the article still holds.
Actually, I think the author put DeepSeek on purpose to avoid the obvious ChatGPT/Claude comparison — because whatever he chose, there would be a question of why model A and not B, while the point of the article isn't about models comparison at all.
It is the point. Also open source model enthusiast tell you otherwise, there is a coding quality gap between these models. If I use DeepSeek, I do so knowing that I have to limit to simpler tasks on smaller, well specified prompts. What the author did, letting the model do the planning, is not something DeepSeek will excel at. I'm using GPT (Terra, Sol, Luna), Claude (Opus 5, Fable), Qwen 3.8 and GLM 5.3 Flash daily and have to vary which model I use where because there's a huge intelligence step function difference here. That's why this article is so useless:
Imagine someone trying to make the case that riding bicycles is a terrible experience and their whole argument is that they took a random cheapo bike with flat tires and rode it for 3min and that wasn't fun. Sure, but if you buy a 25k carbon bike you will have a different experience. I'd not trust that person. If someone told me they have 10 bikes they ride daily and can explain the differences, in detail, between their bikes, and what they excel at. I'd trust that person's opinion.
There’s a night-and-day difference between frontier and budget models, no question. But the issue isn't the tooling at all : if you put someone who doesn't know the rules of the road on a $15k carbon road bike, they're just gonna slam into a telephone pole at 30 mph instead of 6 mph
Excellent analogy. This paragraph invalidates the entire post and honestly just looks lazy. The author may be right anyway, but with that level of experience with these tools, he is really just guessing.
Maybe the failure is in trying only one model / one prompt.
Right. Better throw money at 5 different ones and then people come and tell you that you just need MORE agents and throw MORE money at it or you're not doing it right.
4 replies →
I think the point is that $10 isn’t exactly a lot of money to put where your mouth is, nor a serious effort to see if it works.
I got here and... I agreed with everything up to this point.
The author makes a good point. If you don't know what you're doing, AI accelerates that. No question.
But they put a whopping... ten bucks into using DeepSeek and weren't impressed with the initial results.
I know they try to cover this with "you just aren't prompting correctly!" but if, in 2026, you aren't able to have an LLM generate decent quality code... IDK what to tell you. Good luck I guess?
> in 2026, you aren't able to have an LLM generate decent quality code
Nobody is. The only difference is that some of us are willing to say the emperor has no clothes.
The workflow isnt a single prompt then you have working code from the LLM, its 30 prompts of discussion and then reading each proposed edit and having tangent discussions until you're somewhat ok with it. Then reviewing the changeset as a whole and refactoring a few times
I am.
> but if, in 2026, you aren't able to have an LLM generate decent quality code... IDK what to tell you.
I think the author's point still stands. At some point you need to determine whether the output is of decent quality. A lot of people don't have the ability and experience to do that.