Agents and Engineers: Agentic AI with Dan Gerlanc
Nov 3, 2026 · 1 hr 3 min · 11 segments
Mariatta Wijaya is a multi-award-winning open source maintainer and contributor with over 20 years of software engineering experience. A Python core developer focused on workflow and documentation…
Mariatta WijayaGuest
Dan GerlancHost
There's been changes in how we see operations like contributions, like AI-assisted contributions.

There are, not just myself, there are other core developers who Just use AI to write code like they don't write code by hand anymore.

And mostly what we see is that the contributions from people weren't up to standard like they they don't review they don't adjust AI output before creating PRs and that is that's frustrating to us like if they if the user doesn't first sanitize or review or make sure it sounds like human it's I say it's like We really rather engage with real human than with AI.

And I know this contradicts what I said earlier, where we actually use AI to contribute.

The difference is that as the experience maintainer, we know what the project needs we have additional expertise knowing like what is actually good good commit messages or good PR body good code or good practices in how to adjust unit tests and everything like that What we see, the problem is that first time contributors or new contributors, they just wanted to have something in CPython.

For me, like the whole process of contributing open source to open source, like learning how to communicate with people in the open, learning to ask questions, clarify, you know, the issues, the requirements.

Learning how to actually write code or how to use Git, those are part, those are the real point of contributing to open source, getting the experience.

There are people who said, I don't want to see this kind of AI slope at all.

There's been changes in how we see operations like contributions, like AI-assisted contributions.

There are, not just myself, there are other core developers who Just use AI to write code like they don't write code by hand anymore.

And mostly what we see is that the contributions from people weren't up to standard like they they don't review they don't adjust AI output before creating PRs and that is that's frustrating to us like if they if the user doesn't first sanitize or review or make sure it sounds like human it's I say it's like We really rather engage with real human than with AI.

And I know this contradicts what I said earlier, where we actually use AI to contribute.

The difference is that as the experience maintainer, we know what the project needs we have additional expertise knowing like what is actually good good commit messages or good PR body good code or good practices in how to adjust unit tests and everything like that What we see, the problem is that first time contributors or new contributors, they just wanted to have something in CPython.

For me, like the whole process of contributing open source to open source, like learning how to communicate with people in the open, learning to ask questions, clarify, you know, the issues, the requirements.

Learning how to actually write code or how to use Git, those are part, those are the real point of contributing to open source, getting the experience.

There are people who said, I don't want to see this kind of AI slope at all.
The rest of this transcript — segmented and speaker-labeled, so you land on the exact moment something was said
Search every transcript — by keyword, by phrase, or by meaning, across every show Radar indexes
Trends — what is surging across podcasts, measured against its own baseline
Alerts — when a name you follow appears in a newly indexed episode
No account is needed to search Radar.