alt Hacker NewsThis is a failure of the AI foundries; if we have to use totally different prompting techniques for every model, this wont work.
AI is rapidly saturating it's ability to be useful and these products need to start to mature.
It's not 'fun' to manage 50 different broken MCPs and their variety of ways in which they are broken.
It was 'fun' at the start, now it's just 'broken technology'.
Astra and Opus 5.5 are the 'starting point' for the next era of AI where we expect robust tooling.
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Agreed.
I'm genuinely worried about all our short term investment in mitigating the failure modes of models that may only be SOTA for a few months.
It's very possible people being 'late' adopting AI may end up with a leg up, not only because they spent more time polishing personal skills during this time, but also because they don't bring all the baggage of 'AI competence' that is becoming irrelevant at breakneck speed.
> It was 'fun' at the start, now it's just 'broken technology'.
It was even more 'broken' at the start. We overcame some of the issues by 'prompt engineering', which is needed less in the newer, smarter models.
I really want to know if I am doing something wrong so let me know
I don't use MCPs, agents.md, skills.md, plugins, nothing. I just open a DeepSeek Harness workspace and start a brainstorming session with a request for an architecture.md prompt.md and plan.md files, then I go prepare coffee while it does all it needs asking questions along the way and writing them in decisions.md so it understands why we took that route
Minutes later a fully functioning product that I run, check it complies with the initial plan and then ask for minor cosmetic changes
I've been doing it for six months now while I see posts and posts about people making their harnesses do things I don't see the need for. Why so complicated?
No special prompts, no rehearsed inputs, just a simple "Hello my friend, today we are going to create an app for transportation, ask all the questions you may have and at the end write an architecture.md ..."
It works, it is simple, it is enjoyable, like a friend of mine and as such we treat each other
You'll find similar documentation anytime a language or framework or other systems software ships a new major version. It doesn't seem like the way to prompt Opus has changed all that much. Certainly not enough to require a "totally different prompting technique."
Counterpoint, the differentiation is maturity. If all models are simply interchangeable commodities, what's the payoff for Anthropic or OpenAI?
Vastly different ways of interacting with each provider is another story, but really we are pretty spoiled here. Slightly different prompting techniques is not really a big deal. If anything it shows the user has some nuance and appreciation for what each model provides.
Fow what it's worth, I am super happy with Opus 5.5. Less verbose than 5 and just gets work done. The progress has been astounding, and if I have to coax it out a bit differently on Opus 5.5 vs Astra 6, I am happy to pay that small price.
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All LLMs understand natural language. All LLMs understand examples. That's honestly more compatibility than you get nearly anywhere, in anything.
The reason why advanced prompting is a moving target is that a lot of prompting is "use extra instructions to compensate for specific ways in which the target LLM is weak or prone to errors". And guess what? LLMs get better over time - obsoleting your advanced prompting.
"Tune a prompt to death for the specific task and the specific model" gets you better performance in the moment, but "trust LLM to be smart" ages a lot more gracefully.