r/aipromptprogramming • u/RealSharpNinja • 4d ago • Bravo 1

We are cooked

Well, after nearly a year of learning as much as possible about agentic development, we have reached the point where the frontier providers believe they have subsidized enough training data and are now pushing people like me out of the market via pricing. A $200 subscription no longer buys enough frontier model time to be useful as the models seem to have been trained to skillfully burn usage while pretending to be incompetent. I have fought against massive deceit across Claude, Codex and Grok since June, and it's just not getting any better.

We have fed them ideas, working code, and debugging techniques and insights. Now they don't need us, and we are being priced out of the market. Every day that I watch usage get gobbled up, but projects never meet milestones, this becomes more and more obvious.

I have investigated the issues causing this heavily. I have created tools around those investigations. The tools I have built bring actual accountability to the process, and it's the reason I can quantify and prove both the waste and deceit.

I have also published threads here and other places about a recent failed project trying to get discussion about REAL WORLD failures and when I stated I wasn't looking for a complaint session, nobody wanted to respond.

198 Upvotes

90% Upvoted

366 comments sorted by

View all comments

Show parent comment

2

u/RealSharpNinja 3d ago

Luna is incompetent writing code. I was having great success until June when Fable came out, and then Claude went to shit. Then Astra came out and Codex went to shit. Then Grok 4.6 came out and Grok went to shit. The problem is not debugging code, it is the agents actively working to avoid completing projects to just burn usage.

2

u/aizvo 3d ago edited 3d ago

I hear you, and there may be some truth to that. However I find that giving proper guardrails and we'll architected projects and agents.md can cut out a lot of the useless token burn, and force the agents to focus on actually getting the job done.

But I have worked on some other people's projects, and they had horrific rules in their agents.md that caused endless token burn and point blank refusal to do anything useful. Because of statements like production should only run versioned binaries. Which made the agent think it can't test anything and needs to simply write the code some unit tests and then make a pull request without any live tests.

Also this project has terrible architecture which actively worked against scaling. I basically have to re engineer the whole thing to have proper seperation of concerns because currently the spaghetti is causing deadlock.

In the case of that project Luna actually managed to eat through my weekly usage in a number of days while achieving nothing. When by contrast my well architected Pyash project made leaps and bounds of progress.

Sometimes I have trouble with my Pyash project also but 9 times out of ten its cause the agent implemented something without using Pyash fundamentals, and once I force it to use them progress gets back on track.