I'm mostly using deepseek 4.1 flash via openrouter, the way I'm doing stuff is:
1. write a sketch of a spec by hand
2. have the llm review the document and question me until it can generate a spec
3. review the spec and revise where needed
4. have it write an implementation plan
5. another round or revision/review
6. executing the plan step by step through the plan, plausing between each step to see if we are still on course and if the decisions it made track with my understanding of what we are doing.
I've been working for a couple of hours tonight, the total cost of the session is €0.6.
it's not the build this thing end to end, but also not quite write function x for me. It is still a lot of manual review, but I find I really need it to even discover what I actually want to build. I just cannot imagine building something in a single shot and getting something that actually has value (unless it is basically a clone of an existing thing). To me the whole value of ai right now is that it's now very cheap to build custom software that exactly matches your preferences.
I do the same but with gpt-6-sol (mostly via github copilot cli).
The one-shot capabilities of frontier models are nice for demonstration purposes, but not actually all that useful to me - the result is often an amalgamation of ad-hoc ideas the agent came up with, poor UI and a hodge-podge of a data model, but at least demonstrating clearly where the specs are lacking.
I agree that in practice, iterative design with lots of review and hand-holding are needed to get quality results. Generated code (I mostly program C++) is often bloated and not succinct or "simple" enough to my tastes, so it requires multiple rounds of cleanup.
For core logic, I find having the agent review code is often faster and more valuable than having it implement it in the first place - it can find and fill in the things I missed.
For my own sanity it is very important that I remain in control and understand the generated code when quality and maintainability are goals of the project.
One of the big differences using the better models is that you don’t need to hold their hand anywhere near as much. Fable is crazy expensive, but I’ve seen it just one-shot some remarkably complex projects. The code it produces is much better, too.
yeah i just think that if I gave the initial pitch to Fable it would have successfully built something that wasn't exactly what I wanted. maybe it is because i went to school for design, but how something works is so important to me and it is hard to get to that point without actually thinking about it step by step and visualizing how interactions would work. I just cant imagine a single one-shot prompt containing enough information to for the model to know what to build. I guess if you have Frontier model money like these silicon valley freaks you could just iterate by asking it to tweak what you didn't like until it is right.
1. write a sketch of a spec by hand
2. have the llm review the document and question me until it can generate a spec
3. review the spec and revise where needed
4. have it write an implementation plan
5. another round or revision/review
6. executing the plan step by step through the plan, plausing between each step to see if we are still on course and if the decisions it made track with my understanding of what we are doing.
I've been working for a couple of hours tonight, the total cost of the session is €0.6.
it's not the build this thing end to end, but also not quite write function x for me. It is still a lot of manual review, but I find I really need it to even discover what I actually want to build. I just cannot imagine building something in a single shot and getting something that actually has value (unless it is basically a clone of an existing thing). To me the whole value of ai right now is that it's now very cheap to build custom software that exactly matches your preferences.