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Related: I find this self-assessed AI level for contributions [1] to be extremely useful, both professionally and personally, to communicate the level of AI ass

Related: I find this self-assessed AI level for contributions [1] to be extremely useful, both professionally and personally, to communicate the level of AI assistance so that the person on the receiving end can evaluate how much time & effort they want to spend understanding my code. [1]: https://www.visidata.org/blog/2026/ai/#self-assessed-ai-level-for-contributions https://www.visidata.org/blog/2026/ai/#self-assessed-ai-leve...

chrisjj 1mo ago
> this self-assessed AI level for contributions [1] to be extremely useful Why would you trust the bot to self-assess truthfully? That's like trusting a spammer to tag his emails as spam.
- zuzululu 1mo ago
  a spammer is motivated by self-enrichment AI agents are grounded on the user provided direction. If it doesn't work well then it naturally loses trust.
  - chrisjj 1mo ago
    > If it doesn't work well then it naturally loses trust Too late. If it doesn't work well then it has already naturally destroyed trust.
Calazon 1mo ago
This is great. There's a big difference between levels 2-4 (where I generally operate) and levels 7-8 (where I see a lot of others operate), and I like how this level system makes that explicit.
stillpointlab 1mo ago
I think 10 levels here is too much and hints that someone anchored on 10 as a round number and then forced the levels to fit after the fact. I don't really see much value beyond the 3 levels of AI disclosure that have been floating around: - fully human - ai assisted - ai generated
- kccqzy 1mo ago
  There’s a big difference between AI generated code that the human understands completely, the human understands mostly, or the human understands not at all.
  - stillpointlab 1mo ago
    "Human understanding" is not yet an objectively quantifiable metric that can be applied to code change sets. As it would only ever be self-reported (a claim made by a user submitting to a repo), I see little to no value in it.
    - kccqzy 1mo ago
      It is quite quantifiable in fact, but I just worry people won’t take the time to quantify it. I do this exercise myself for code that I really care about: after AI has written the code and I think I have achieved a full understanding, I unapply the entire patch and make sure I can reproduce the patch with the same underlying idea perhaps with less verbosity in the comments. That’s what I call fully understood. If I “mostly understand” some AI code, it means during the reproduction I need to occasionally look back at the AI code to continue.

chrisjj 1mo ago

> this self-assessed AI level for contributions [1] to be extremely useful Why would you trust the bot to self-assess truthfully? That's like trusting a spammer to tag his emails as spam.

zuzululu 1mo ago
a spammer is motivated by self-enrichment AI agents are grounded on the user provided direction. If it doesn't work well then it naturally loses trust.
- chrisjj 1mo ago
  > If it doesn't work well then it naturally loses trust Too late. If it doesn't work well then it has already naturally destroyed trust.

Calazon 1mo ago

This is great. There's a big difference between levels 2-4 (where I generally operate) and levels 7-8 (where I see a lot of others operate), and I like how this level system makes that explicit.

stillpointlab 1mo ago

I think 10 levels here is too much and hints that someone anchored on 10 as a round number and then forced the levels to fit after the fact. I don't really see much value beyond the 3 levels of AI disclosure that have been floating around: - fully human - ai assisted - ai generated

kccqzy 1mo ago
There’s a big difference between AI generated code that the human understands completely, the human understands mostly, or the human understands not at all.
- stillpointlab 1mo ago
  "Human understanding" is not yet an objectively quantifiable metric that can be applied to code change sets. As it would only ever be self-reported (a claim made by a user submitting to a repo), I see little to no value in it.
  - kccqzy 1mo ago
    It is quite quantifiable in fact, but I just worry people won’t take the time to quantify it. I do this exercise myself for code that I really care about: after AI has written the code and I think I have achieved a full understanding, I unapply the entire patch and make sure I can reproduce the patch with the same underlying idea perhaps with less verbosity in the comments. That’s what I call fully understood. If I “mostly understand” some AI code, it means during the reproduction I need to occasionally look back at the AI code to continue.