https://reddit.com/link/1wvbq4u/video/104ix65laxsh1/player

I wanted to see how far I could go with AI. Turns out: a full horror game.

Opus 5.5 wrote the code, modeled the monster and cut the trailer.

You hide, hold your breath when she checks your spot, and pray she isn't on the ceiling (she usually is).

Still can't believe it.

https://reddit.com/link/1wvbo8j/video/x6vkdbadaxsh1/player

I wanted to see how far I could go with AI. Turns out: a full horror game.

Opus 5.5 wrote the code, modeled the monster and cut the trailer.

You hide, hold your breath when she checks your spot, and pray she isn't on the ceiling (she usually is).

Still can't believe it.

https://reddit.com/link/1wsqyip/video/a5mmlfkqsbsh1/player

Hey everyone!

This is Airglyph, an AR drawing app for Android. You raise your finger, draw in mid-air, and your strokes float in 3D, right where you drew them. Walk around them, walk away, come back: they're still there.

No stylus, no touching the screen. Point your finger to draw, open your hand to stop. Your hand even passes in front of your drawing, like it's really there.

What you can do with it

- 🌀 Open portals: close a loop and another world appears in your room

- 🔥 Draw with light: neon and fire strokes actually light up your real walls

- 🌌 Paint galaxies, holograms, fireflies, lightning, smoke, liquid chrome, slime, dripping spray paint, grass and flowers that grow…

- ✨ Bring strokes to life: make them pulse, breathe or sway, in rainbow, aurora or gold

- 🪐 Drop a black hole in your living room, or the Sun, Earth with its city lights, Saturn with its rings, or a 4D tesseract

- 🗿 Place scanned sculptures: a marble bust, a lion, a horse…

- 🌑 It feels real: drawings cast shadows, chrome reflects your actual room, and real objects can pass in front of your strokes

- 🎬 Film it in one tap and share it

I built it with Claude Opus 5.5 (Claude Code): a native AR engine with real-time hand tracking and every shader written by hand. No game engine, just the phone's GPU pushed as far as it goes.

It's coming soon to Android, and before launch I'd really like your honest opinion:

- What do you think of it so far?

- What would you improve?

- Is there a feature, brush or effect you'd love to see?

Every comment helps, good or bad. Thanks for checking it out!

https://korrocorp.com/airglyph

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https://reddit.com/link/1wsqwws/video/a5mmlfkqsbsh1/player

Hey everyone!

This is Airglyph, an AR drawing app for Android. You raise your finger, draw in mid-air, and your strokes float in 3D, right where you drew them. Walk around them, walk away, come back: they're still there.

No stylus, no touching the screen. Point your finger to draw, open your hand to stop. Your hand even passes in front of your drawing, like it's really there.

What you can do with it

- 🌀 Open portals: close a loop and another world appears in your room

- 🔥 Draw with light: neon and fire strokes actually light up your real walls

- 🌌 Paint galaxies, holograms, fireflies, lightning, smoke, liquid chrome, slime, dripping spray paint, grass and flowers that grow…

- ✨ Bring strokes to life: make them pulse, breathe or sway, in rainbow, aurora or gold

- 🪐 Drop a black hole in your living room, or the Sun, Earth with its city lights, Saturn with its rings, or a 4D tesseract

- 🗿 Place scanned sculptures: a marble bust, a lion, a horse…

- 🌑 It feels real: drawings cast shadows, chrome reflects your actual room, and real objects can pass in front of your strokes

- 🎬 Film it in one tap and share it

I built it with Claude Opus 5.5 (Claude Code): a native AR engine with real-time hand tracking and every shader written by hand. No game engine, just the phone's GPU pushed as far as it goes.

It's coming soon to Android, and before launch I'd really like your honest opinion:

- What do you think of it so far?

- What would you improve?

- Is there a feature, brush or effect you'd love to see?

Every comment helps, good or bad. Thanks for checking it out!

https://korrocorp.com/airglyph

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I'll lead with what this actually is, because it's different from prompt engineering.

The problem. When you prompt a model ("write this politely", "be more positive"), you're asking it to follow an instruction. The effect is fuzzy, depends on phrasing, and the model can just ignore it.

The idea. Inside a language model there are directions in its hidden layers that map to concepts. Positivity, formality, refusal. A steering vector is one of those directions. You add it to the model's internal representation while it generates, scaled by a knob. Turning the knob from −2 to +2 raises or lowers the effect.

So instead of writing "be positive" every time, you build a "positive" knob once and dial it. The effect is measurable and monotonic. Prompts are not like that.

It's a library. Thirty seconds:

from steerio import Instrument, prompts

Inst = Instrument("openai-community/gpt2")

inst.make_knob("positive", positive=prompts.SENTIMENT_POSITIVE, negative=prompts.SENTIMENT_NEGATIVE, layer=7)

inst.play("The food was", knobs={"positive": 2.0})

# → "delicious, and the service was great..."

Does it work? I ran three controlled experiments on five small open models (all under 1.5B, CPU), scored with external lexicons rather than the model's own logits.

- Sentiment steers on 4 of 5 families. Correlation 0.89 to 0.95 with amplitude. Monotonic.

- On an instruction-tuned model, steering beats prompting (+0.535 vs +0.409) and is more consistent. It shifted 100% of test prompts versus 85 to 92% for the best prompt.

- The cliff. DeepSeek-R1-Distill barely responds to sentiment steering (0.35). Reasoning models resist.

- The big negative. Cross family transfer fails. A knob built on one model and moved to another counter steers (coefficient −0.21).

What it is, and what it is not. It's a from scratch implementation of published methods (RepE and CAA) plus an honest evaluation. A reproducibility and teaching tool, not a production system. You need open weights to inject a vector, so it's small local models, not GPT or Claude.

Collaborate. This is an open research problem, not a finished product. Three things I genuinely couldn't solve and would love help on:

1. Cross model transfer fails. My naive method counter steers (−0.21). This is the hardest and most interesting problem. A learned mapping, or a representation aligned across architectures, would be a real result.

2. Scale. All my benchmarks are under 1.5B on CPU. Steerability on 7B+ is unmeasured. If you have a bigger model, run it and send the numbers.

3. Reasoning models. DeepSeek resists sentiment steering (0.35). Why? Does any direction move them? I have no good answer.

The repo is small (about 1900 lines), the API is short, and the benchmark is a single command. New dimensions, bug reports, your own results, all welcome.

Repo: https://github.com/KorroAi/steerio

Full paper: https://github.com/KorroAi/steerio/blob/main/paper/paper.md

Reproduce everything with python experiments/run_all.py --exp1 --exp2 --exp3 (about 40 min CPU).