I suspect, since this is HN, you're looking for something more open and hackable. But you might want to check out SIG Connect if you just want something that works out of the box.
Sorry I can't get into "how it works". Feel free to DM me for any questions.
I've been trying to use the latest versions of LLMs to analyze a target for scoring, but it's completely outside their current capabilities and hasn't worked.
Additionally, the app doesn't seem to be available in Germany.
One thing I see missing from some other replies to your comment is a discussion of determinism. That is given the same input, always produce the same output.
Determinism is often valued in safety critical systems. The system can't work _sometimes_. The system can't even work correctly _eventually_. It must produce the desired result in the time allotted. Actuating the thing 20ms too late could be as bad doing it incorrectly depending on the application.
I'm no ML expert, but that seems to be a problem for those types of solutions in some spaces.
We’ve had some success with similar methods. In addition to the simplicity(it just “plugs into” the existing board), it’s nice to get metrics on the bottlenecks happening on the product side of things. If we can show that it historically takes 2 weeks to refine requirements, we can tighten up our estimates and shine a light on potential problems occurring there. If you only have metrics on the dev work, the more business-minded folks tend to focus improvements only on what they can measure.
I’ve also found that folding product workflows into the Kanban board gives the team more visibility and ownership over that end of the pipeline. We can observe how those items age before it ever gets to the dev team and swarm to fix things as a team earlier in the process.
I would love to have an AWS expert handy at all times, so I tried to upload all AWS documentation using this: https://docs.aws.amazon.com/sitemap_index.xml. I can no longer use the site, so I suspect that busted something.
In hindsight, that was not cool and I'm sorry about it.
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