> There is no one answer to agentic engineering. Everyone works differently; every model is good at different things. The key here is reps: do a lot, ask a lot, throw away a lot. You’ll learn what works for you.
That all reads to me like: The key here is: "Burn tokens as money in a bonfire, pray you typed in the right magic spell (prompt) and the ingredients (context) in the potion were right, toss away the failed elixir of life".
Instead of writing code and refactoring yourself and gaining an understanding, you're hoping that a slot machine will get luckily get the statistics right to put up code that you already need to read again.
> It’s the same loop that taught me to code, moved up a level: write, run, fail, fix. I used to iterate on code. Now I iterate on prompts, designs, whole features. A rewrite that used to cost a week costs a conversation.
And also costs you skills atrophy and however much tokens will be. Not to mention the negative externalities of using LLMs (massive increase of fraud, of disinformation, of rocketing prices in memory and in turn all electronics, massive use of energy that consumers have to also then pay extra for, environmental and noise cost of using on-site turbines, local destruction of water resources for the local community).