We gotta tune the AI hype-fluencers out of the feed. It leads devs to think there's some AI silver bullet for coding. It doesn't exist. If I just use this MCP server, or run 20 subagents across terminals, or get the perfect rule crafted, only *then* will AI suddenly work! Nah. It's not that easy. Building great software takes foundational knowledge and care. There isn't one specific thing you can do to take the quality of AI generated code and make it perfect. Let me give you an example. If you ask "which MCP servers should I use?", have you first thought deeply about *why* that would even make the code generated better? Is it actually going to save you time? If the MCP is just speeding up copy/paste for you, sure that might help some, but it's not going to fix the poor instructions you gave the model. The model might connect and integrate data from 20 MCP servers only to build the wrong thing. Same thing with rules files. You know what makes great rules? Thinking deeply about your business requirements, system design, and personal preferences. It's kind of hard to outsource that. You can get inspiration from others and pick up some tips or suggestions, but this is a personal question for how *you* want to steer the model. A great rules file for an agent *can* make the quality better. And certain MCP servers *can* make pulling in the right context much easier, hooking into bigger firehoses of data where you're looking for the needle in a haystack. But you only figure this out using AI to build real things and finding real edge cases. Stay optimistic with a healthy dose of skepticism, my friends. These models and tools are *amazing*... and also software engineering is hard.