What do you think about this project? Has something like this being tried before?
What do you think about this project? Has something like this being tried before?
> O'Hara said the man was a “lawful gun owner” with a permit. Records show that Pretti attended the University of Minnesota. State records show Pretti was issued a nursing license in 2021, and it remains active through March 2026.
Minnesota permit-to-carry requirements: https://dps.mn.gov/divisions/bca/public-services-bca/firearm...
> Q: Do I have to disclose to a peace officer that I am a permit holder and carrying a firearm?
> A: Yes, upon request of a peace officer, a permit holder must disclose to the officer whether or not the permit holder is currently carrying a firearm.
So a U.S. citizen who is a legal, permitted gun owner with no outstanding criminal charges, legally carrying in public, who complies with the law and informs a DHS officer that they are legally carrying, is effectively subject to summary execution without due process. (The penalty for permitted carrying without possessing the physical permit card is $25 for a first offense and forfeiture of the weapon; it would've been his first offense per Minneapolis police.)
If ever there was a 2A violation, it's a federal officer shooting and killing a legal gun owner solely for possessing a gun in their presence.
1. Created in 2013
2. Have between 7 and 10 subs
3. Have between 2 and 3 video playlist
4. Account bio extremely generic
After a few minutes spent manually checking I decided to build a tool that: • Downloads all YouTube comments + replies
• Runs sentiment analysis on each
• Detects bot-like behavior using heuristics + LLMs
On this video, over 40% of comments look like bots, and they overwhelmingly argue the video wasn’t AI-generated.I didn't went as far as trying to understand where these accounts are coming from, but my main goal was to confirm whether this was real coordination.
I'm not expert in data nor in python (I've mostly vibe-coded it). I’d love to get some help from folks how might be interested on these topic.
As I will need to fully handover the task and let the agent(s) essentially one-shot the implementation I need to be way for specific and clear in giving it context and goals, otherwise I’m afraid it will start build code purely by accumulation creating a pile of unmanageable garbage.
Also changes which requires new UI components tend to require more manual adjustments and detailed testing on the UX and general level of polishing of the experience our users expect at this stage.
I’m starting to develop a feeling of tasks that can be done this way and I think those more or less represent 20 to 30% of the tasks in a normal sprint. The other 70% will have diminishing returns if not actually a negative return as I will need to familiarise with the code before being able to instruct AI to improve/fix it.
From your experience building this, what’s your take on:
1. How do your product helps in reducing the project management/requirements gathering for each individual tasks to be completed with a sufficient level of accuracy?
2. Your strong point seems to be in parallelisation, but considering my previous analysis I don’t see how this is a real pain for a small teams. Is this intended to be more of a tool for scale up with a stable product mostly in maintenance/enhancement mode?
3. Are you imagining a way for this tool to implement some kind of automated way of actually e2e test the code of each task?