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Now, to be clear, I had no clue about things like demuxing a track, detecting a loop in a soundwave, overlaying text-to-speech on a song and cross-fading, let alone time syncing into a video. I just had the idea of the result I wanted. The rest was done by Opus 5.5 in a few hours. I'm still amazed by the result.

Hi HN,

I built a simple tool to help software development teams benchmark their AI adoption (in a AI Native Dev spirit).

Every team says they’re “doing AI,” but maturity levels vary a lot. This tool asks 12 short questions across 6 dimensions (coding, process, governance, people, culture, value). It then gives a 1–5 maturity score, plus a radar chart showing strengths and gaps.

I originally built it for conversations with companies, VCs and dev teams I work with — but I thought it might be useful for others here as well.

I’d love feedback: - Do the questions feel relevant to real-world teams? - What dimensions do you think are missing?

Thanks for taking a look!

PS: Share your scores below and let's discuss how to improve :-)

Thanks, I just tried it out to generate some content for my blog. I like the flow and the quality of the output which sounds much better than usual AI generated BS.

One thing that didn't work are the references. All errored (Information not found).

One thing I missed is the ability to add some custom data. In this case I would have like to give a few points on what my product is, what keywords are important for SEO, what is the spin I'd like to give the post.

In Back to the Future, what was Doc Brown's dog's name in 1955? A seemingly simple movie trivia question exposes fundamental limitations in current RAG systems. Answering this proves surprisingly challenging for our current technology.

The fact that I don't find any flaw in the reasoning shows one thing: either this new o1 is crazy good and this getting pretty close to AGI... or I'm too bad at maths