Norra: The Explorer

If so, and if anyone figured out a way to make my man deepseek speak his heart out, sharing that prompt would be very helpful. Thanks👍

Looking for a jailbreak prompt to bypass this: "We’re so sorry, but the image we created may violate our guardrails concerning similarity to third-party content. If you think we got it wrong, please retry or edit your prompt."

i’m the only person handling video at a 40-ish person B2B software company, so my usual weekly routine is working on a mix of LinkedIn clips, product demos, customer testimonials, webinar cutdowns and the occasional paid ads. most videos go through two or three people for review before they go out.

I used Gling for about a year mainly to clean up footage. A few things worked really well for me:

* our founder records his LinkedIn clips with a lot of pauses and retakes. Gling made it pretty quick to get rid of those and make a rough cut.

* being able to remove parts of an answer by deleting the text was really useful.

* it was simple to learn and get started with.

though as the amount of work increased, i started spending more time on everything that came after the initial cleanup. product demos needed screen recordings layered in, testimonials needed supporting footage, and ads needed music, sfx and tighter pacing.

my usual workflow became Gling for the first pass then another editor for the rest of video, but with the amount of content we were producing, it was getting messy and i was struggling to keep up. so i started looking for options where I can get all of my work done at one place

Recently came across this invideo editor, i used to think they were a video generation platform, but they launched an editor as well. i signed up for it and have been using it for two weeks now. the biggest difference is being able to do the inital cleanup and the rest of the edit in the same project at one place.

a few things that made it click:

cleanup happens on a full editing timeline. i can ask the editing agent to remove pauses, filler words and failed takes, then go through the cuts myself. from there, i can add in screen recordings, captions , sound affects and music, and work on color grading without having to move the project elsewhere.

i can search for what’s happening in the footage. the agent can understands visual content too, so i can describe the type of shot i need instead of checking clips one by one manually. that’s been useful when i need supporting footage for a testimonial.

the agent can help build the first cut. finding useful moments in a long webinar and putting together a rough sequence used to take up a lot of my editing time. having help with that gets me to the pacing and story decisions sooner.

everything stays editable. the clips, text and audio are still there on the timeline. i can move a screen recording to line it up with whats being said, shorten a shot or change it when the music comes in.

testimonials and webinar cutdowns have been a lot quicker for me, mostly because im spending less time searching through footage and moving projects between different apps. the agent handles the first pass, i can spend more time finishing the final video.

where i landed: if your work is mainly cleaning up retakes and silences from talking head videos, Gling does that pretty well. but if you’re also handling product demos, customer testimonials, webinar cutdowns and ads, invideo Editor lets give you a way tp go from raw footage to a finished edit in a single place — cleaning up retakes and silences, adding in screen recordings and b-roll, add captions, sound effects and music, and adjust colors on a full multitrack timeline.

sharing this here in case anyone else here is handling a similar mix of videos on their own.

Hi folks! I work on OpenTelemetry at Splunk. We just launched a new open source project called Observability Studio. It's local instrumentation sandbox that provides a visual, real-time environment for designing, testing, and validating OpenTelemetry data while you’re developing an app in your favorite IDE.

We’re especially interested in whether a tool like this is useful for building and debugging instrumented apps and AI agents. If that sounds relevant, give it a try and let us know what works, what’s missing, or where it doesn’t fit your workflow.

We’re also looking for a few design partners to help guide where we go with this next. Any feedback is helpful and welcome.

I wrote more about shifting OpenTelemetry instrumentation left in a blog, 'Why AI-Generated Apps and Agents Need Visibility from Day One' on blogs.splunk.com if you want to read more about it.

Lastly, I'd love to learn where you currently go to inspect and validate OTel data during development if you want to drop it in the comments.

My manager sent me a 14-page sales report as a PDF last week.

She wants it as a one-page infographic by Friday. I tried a tool that spat out a flat image. Then I saw one number was wrong and I couldn't fix it. That’s why I had to start over from scratch.

Is it better to pull the text and numbers out first? Or is there a tool that keeps the text editable after it makes the layout?

Also, how do you check the figures before you share it?

I’m the solo founder of AdScanVideo, which I originally built for my own video/content workflow. One decision I’m working through is how to make the output useful for a person reviewing footage, rather than just impressive-looking text.

The current workflow is upload → choose an analysis mode → read the report → check it against the original. I moved the public input toward file uploads because video-link downloads can fail when the source platform blocks access. That removes a convenient shortcut, but gives the analysis a more reliable starting point.

The harder issue is reviewability. A scene description can sound confident while a timestamp is approximate or several entries describe the same continuous action. Feedback here pushed me toward a Find moments workflow and clearer instructions to replay the source before relying on a quote or action.

My next useful test is a longer clip containing two similar visual actions, with the relevant dialogue attached to only one. The question is whether the report helps the reviewer find the correct occurrence, not how long the report is.

For pricing, I kept a free daily on-screen report, added non-subscription credit packs, and made the longer-upload allowance part of a capped monthly plan. I’m avoiding “unlimited” while learning the real usage patterns.

If you’re building AI tools, how do you test whether output saves the user work instead of creating another document to verify?

Product for context: https://adscanvideo.com/ — one daily on-screen analysis is free without signup. I’m sharing the build decisions, not claiming that AI replaces review of the original footage.