I personally think context and prompt engineering are not useful things to learn. If you’re having trouble improving the reliability and maintainability of your systems, the solution is to learn how to design better systems. And that’s great news for you, because there’s a ton of resources out there to learn about systems design! That’s normal engineering, and it doesn’t change as quickly as AI engineering… which, full disclosure as someone who uses a lot of token every day, is overhyped anyway.
AI can help tremendously but there’s so much you as a human understand about product direction and real-world use that the AI simply can’t. Everywhere you look, companies are popping up that are desperate to ingest data from every possible source in order to fix this context and intuition gap. But it’s just not possible. As long as you’re the one who ultimately decides what features you’ll implement, the model will be bad at guessing what to build for in the future. And anyway, you can spend all your energy learning how to squeeze the last 10% of work out of your model and harness and workflow but at the end of the day that’s time you’re not learning about designing resilient systems and actually doing the hard work of implementing them.
Bias: I’m a software engineer, and not super ai-pilled, so. There’s that.
I personally think context and prompt engineering are not useful things to learn. If you’re having trouble improving the reliability and maintainability of your systems, the solution is to learn how to design better systems. And that’s great news for you, because there’s a ton of resources out there to learn about systems design! That’s normal engineering, and it doesn’t change as quickly as AI engineering… which, full disclosure as someone who uses a lot of token every day, is overhyped anyway.
AI can help tremendously but there’s so much you as a human understand about product direction and real-world use that the AI simply can’t. Everywhere you look, companies are popping up that are desperate to ingest data from every possible source in order to fix this context and intuition gap. But it’s just not possible. As long as you’re the one who ultimately decides what features you’ll implement, the model will be bad at guessing what to build for in the future. And anyway, you can spend all your energy learning how to squeeze the last 10% of work out of your model and harness and workflow but at the end of the day that’s time you’re not learning about designing resilient systems and actually doing the hard work of implementing them.
Bias: I’m a software engineer, and not super ai-pilled, so. There’s that.