Comment by larsfaye | Hacker News Reader

Comment by larsfaye | Hacker News Reader

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This is EXACTLY how I am working with these tools, you summarized everything about why I use this approach perfectly. Zed + OpenCode + Mimo/GLM/Kimi models are incredible. I haven't touched a "frontier model" for months.

I really treat them as "delegation layer". They're systems that sit right alongside your stack, and at this point, at every level in it, like a connective tissue that intersects at all points. I can delegate a spec, a function, a file, a whole feature set, an app, a debugging loop, etc.. My day-to-day isn't all that different, it's just like having the "Ship's Computer" that I can ping anytime I need something. I'm enjoying the benefits that a smart data processing pattern interpolator provides, but I'm not giving up any personal control or agency. My goal isn't to go faster, nor is it to avoid coding, because coding isn't drudgery or below us just because we have new code generation tools.

I had a job interview at Canva where they had an "AI coding round". They wanted to see how I used AI in my workflow.

Because I was using DeepSeek flash, the interviewer was confused at how fast I was getting edits - he'd only used Claude and was used to it thinking for 40 minutes to update a function.

We were building a frontend application and I was able to do that whole guided prompt/review loop. I finished the task with no defects (high quality code) and way ahead of time.

I could tell the questions he asked were prepped for vibe coding with slow frontier models, like "how do you review the code to ensure it is safe to commit" - "make small/reviewable edits and read the code the LLM emits?".

Despite meeting the criteria of a principal engineer in the other rounds, the feedback on the AI round was that "I didn't delegate enough to the AI and was too hands on" lol.

> the feedback on the AI round was that "I didn't delegate enough to the AI and was too hands on" lol.

the real feedback they couldn't say is that you were a threat to his position.

So frustrating. Too many hiring teams seeking the "perfect" candidate instead of hiring for completely valid and amazing potential.

I'd wager you're far better than whatever candidate they landed on, because the person who apparently qualified for that role probably isn't thinking while they prompt away.

Why are engineering teams looking for brainless monkeys? It's to their detriment all around if they aren't hiring capable people.

Did that AI round feedback scuttle a potential offer?

Unfortunately they decided not to proceed despite glowing feedback in the other rounds

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