You just need to work on your agent design and prompting skills, modern LLMs are crazy good at all the things you listed with the right context and tools.
Technically yes, but this has nothing to do with LLMs.
You need to be able to write a good spec period, and this has been true as long as programming has existed. The problem is, LLMs cannot write them themselves, and have trouble reasoning out the unstated parts of complex problems if the spec doesn't spell it out.
Developers familiar with the problem space being worked on, however, can reason out the unstated parts, because the unstated parts are usually the bread and butter of the problem space.
Side note: this is often why LLMs trained on synthetic text perform weirdly or badly... the synthetic text is written by people not familiar with the thousands of individual problem spaces that exist out there, and miss important facts or nuance.
LLMs trained on real text, however, is often done without proper license, and are essentially lossy compressed piracy archives. You're damned if you do, you're damned if you don't.
You need to be able to write a good spec period, and this has been true as long as programming has existed. The problem is, LLMs cannot write them themselves, and have trouble reasoning out the unstated parts of complex problems if the spec doesn't spell it out.
Developers familiar with the problem space being worked on, however, can reason out the unstated parts, because the unstated parts are usually the bread and butter of the problem space.
Side note: this is often why LLMs trained on synthetic text perform weirdly or badly... the synthetic text is written by people not familiar with the thousands of individual problem spaces that exist out there, and miss important facts or nuance.
LLMs trained on real text, however, is often done without proper license, and are essentially lossy compressed piracy archives. You're damned if you do, you're damned if you don't.