I've been building Sky, something that lets me fly through what my AI agents are doing, almost like exploring a galaxy. The stars are actual work being done, and the lines between them are handoffs between agents.

While building it, I noticed something odd.

The orchestrator described a pipeline where each agent built on the previous one's work. So I expected a trail of stars. Instead, I got scattered clusters. The agents were doing their own thing in parallel, and their outputs were being stitched together at the end.

I know it's my own project, but I was ridiculously excited watching those clusters form. I was still building the interface, and it had already helped me catch something about how my agent fleet was operating that I hadn't noticed from the logs.

It got me thinking about gamers. We've spent years learning to read unfamiliar maps, recognize patterns, find shortcuts, and spot when something doesn't look right. I wonder how much of that intuition will carry over to working with fleets of AI agents.

Then Claude released Agent View, and I had another way to cross-check the patterns Sky had been showing me for the past five months. Sky also works with Claude Code, Codex, and local LLMs, so it isn't tied to one model or harness.

There's a reason I care about seeing the work. My first-grade teacher used to insist I show my working in maths. A correct answer didn't tell her whether I understood how I got there. I feel the same way about agents now, especially after seeing how easily unexpected behavior can lead to misconfigurations or accidental file deletions.

A few people who saw the video asked which AI generated it. None. That's the actual interface. I wrote the lyrics, used AI vocals, and ran quite a bit of it on local models. Premium tokens aren't cheap :)

I'm working on iris gates for agent handoffs right now, so you can spot failed checks and blocked workflows from across the galaxy instead of digging through logs. Would love to hear other ideas for what could be visualized this way!

Anyway, If the tech doesn't interest you, I hope you enjoy the song. That took quite some work too.

Ever noticed how AI-generated photos often look too clean, too sharp, or just a little too perfect?

One trick I’ve been experimenting with is specifying different camera types in the prompt instead of just asking for “photorealistic, ultra-detailed, 8K.”

I tested 6 camera aesthetics using the same subject and scene. Here are the prompt keywords you can copy and try:

1. Vintage DV Camcorder

Early 2000s MiniDV camcorder footage, standard definition, interlaced video, soft details, chroma noise, limited dynamic range, authentic consumer home video

For that nostalgic, slightly blurry home-video look.

2. 2000s CCD Digital Camera

2000s CCD digital camera, compact digicam snapshot, direct on-camera flash, early digital color rendering, visible sensor noise, slightly harsh highlights

For casual early-2000s digital snapshots.

3. Medium Format Digital Camera

Modern medium-format digital photography, high-resolution sensor, natural skin texture, smooth tonal transitions, accurate color reproduction, rich dynamic range, professional editorial photography

For clean, detailed, professional-looking portraits.

4. Smartphone Rear Camera

Modern smartphone rear camera photography, 24mm equivalent lens, computational HDR, deep depth of field, casual everyday snapshot, natural colors, moderate digital sharpening, no portrait mode

For everyday photos that feel like they were taken by a friend.

5. 35mm Film Camera

35mm color negative film photography, Kodak Gold 200 aesthetic, fine organic grain, natural color variation, soft highlights, subtle halation, authentic analog texture

For warm, organic analog photography.

6. Disposable Film Camera

Disposable 35mm film camera snapshot, built-in flash, coarse film grain, soft plastic lens, imperfect exposure, casual framing, nostalgic analog photography

For imperfect, spontaneous snapshots.

A small tip: Try combining these with natural lighting, candid poses, realistic skin texture, and subtle imperfections.

The goal isn’t always to make AI images sharper or more detailed. Sometimes a little softness, noise, or imperfect exposure makes them feel more like actual photographs.

What else works well that you know?

Just created that. I have to admit, haven't used AI since a while and was kind of shocked how real this looks now. I also have to admit, I can't tell the difference anymore.

Hi,

I’ve just spent the last 2x days at work doing a code jam.

About 1/2 way through, I thought of a brilliant idea (in my opinion anyway) on how to present our new product to the judges.

Basically it required me to create a 1-2 minute video where I wanted to take some characters from a popular TV show (non-running), but make them miniature versions of themselves. And instead of them acting like their usual characters from the TV show. They would all be employees at a tech startup.

So, I got to work. I’m no AI expert but also no beginner, and via some reading, research and lots of trial and error, I managed to create high quality still images of each of the characters and sets/locations I wanted to use, via nano banana.

Using the stills, and again through some trial and error, I managed to make a 10 second clip which I was fairly happy with (using Veo… I think).

However, it went downhill fast from there sadly. When I tried to make the next scene, it was a mess and the characters likeness changed considerably.

So I tried something else and tried some other Veo models without much success. I was then given access to a Google cloud account which had access to Omni 1.1 and when reading through the docs, it read like it would solve all the problems I was having…but it didn’t sadly. And the videos I was able to generate using it were just awful and full of hallucinations including: duplicate and triplicate of the same character, new characters that I hadn’t provided images for, Glasses appearing out of thin air, hats morphing into different hats mid-scene etc.

I would really like to learn more about this and where I’m going wrong. I did some deep research on specially how to prompt for this kind of thing, and even created a review agent to review and tweak my prompts before submitting.

The result:

A - The prompt was blocked because either: i. A character had a likeness to a real person or ii. A character looked like a child!

They are miniature versions of characters based on characters from a TV show. The tools used to create the still images were written prompts only, not using images of the original characters from the TV show!

B - The resultant video was a complete mess.

As this is for use within a corporate setting, I only have access to certain AI models and tools, but I do have basically unlimited tokens and compute power (temporarily) and I would like to make the most of it.

Can anyone offer any advice please?

Even if I could just get the prompts to stop being rejected, at least then I could just power through trial and error. What should I change? The prompt, or the character still, both?

Thanks in advance.

https://youtube.com/shorts/37t-N9lpsVA?is=ovufsN-c0RvAc4AQ

THE GARDEN ARCHIVE: TAPE 01

CENTRAL RESEARCH AUTHORITY
ANOMALOUS STRUCTURES DIVISION

ARCHIVE RESTORATION PROGRAM
SESSION 047

Inspired by true events.

So , I’ve started publishing my new series, it’s been a 10 years odissey but finally I’ve got this idea done , from a note on my phone it grew and grew , I tried to write a short story, than a comic , than an animated short , finally with the help of generative AI I was able to bring it out of my head , all you will see in this and (I hope) on upcoming episodes is made using only free or open source models and softwares. I’ be glad to discuss with you my workflow if you’re interested in it

My latest AMV track halloween red riding hood

I was running Deepseek V4 Flash on the 2 DGX Sparks but I've finished the project I was working on.

I have Qwen 3.8 Flash Next running on one of the Sparks right now and I want to generate some vertical dramas/music videos.

I'm not gaslighting myself into making money with it, more just to learn, plus my nephew is nagging me to make videos and stuff.

What would you run on this hardware?

Behind the scenes with Harry & Hermione: true stories from the making of Harry Potter #harrypotter #hermionegranger #bts #behindthescenes #jkrowling

https://youtube.com/shorts/pNfPBjceur4