Is the majority of research vibecoded these days?

I recently got to the final round for a research engineer position at Google. They rejected me in the end and the feedback I received that I've been out of touch with research for too long. I finished my PhD almost ten years ago and since then did various data science / software engineering / AI engineering stuff.

So the past few months I've been reaching out to old colleagues and people I've met at conferences to see if we can collaborate on a few research papers. I joined three projects with different people, and I'm quite shocked at that everyone is offloading everything to AI with barely any human intervention. All three projects followed basically this premise:

1. Ask AI to do deep research, and come back with ten ideas for a research paper, with the disclaimer that it should focus on easy gaps to fill.

2. Ask AI create a detailed spec with hypothesis, stages and gates. Use AI to refine and validate.

3. Ask AI to implement each stage. Ask AI to review the code and if it matches the requirements in the specs.

4. Ask AI to run experiments (our experiments are just training/finetuning/optimizing agents on expensive GPUs).

5. Ask AI to review the results and create pretty graphs.

6. Ask AI to draft a paper.

Then you notice that a lot of shit in the paper don't make sense and you end up spending a week asking Claude to fix bugs, rerun experiments, redo analysis,... etc.

The whole process from ideation to submitting takes 1-2 weeks. I asked my co authors if this is normal and they all said that everyone is doing this these days.

Is that the status in academia now, or was I just unlucky with the people that I got involved with.