# God is hungry for Context: First thoughts on o3 pro

<https://www.latent.space/p/o3-pro>

- Host: [latent.space](https://links.thingelstad.xyz/hosts/latent.space/)
- Saved: June 12, 2025 (2025-06-13T02:01:34Z)
- Record: https://links.thingelstad.xyz/links/bdb51fa1a05c/
- JSON: https://links.thingelstad.xyz/links/bdb51fa1a05c.json

## What Jamie wrote

I haven't done any serious work with the newest reasoning models, and frankly have found them a bit cumbersome to engage with. This post highlights how you really do need to engage with them very differently, and what they are really good at.

> But then I took a different approach. My co-founder Alexis and I took the the time to assemble a history of all of our past planning meetings at **[Raindrop](http://raindrop.ai/)**, all of our goals, even record voice memos: and then asked o3-pro to come up with a plan.
> 
> We were blown away; it spit out the exact kind of concrete plan and analysis I've always wanted an LLM to create -- complete with target metrics, timelines, what to prioritize, and strict instructions on what to absolutely cut.

Definitely deep research capabilities.

## Facts

- Kind: [Page](https://links.thingelstad.xyz/kinds/page/)

## Appears in

- [WT323: Weekly Thing 323 / Context, Dithering, Liquid Glass](https://weekly.thingelstad.com/archive/323/), Notable

## Same host

- [$2 H100s: How the GPU Bubble Burst - by Eugene Cheah](https://links.thingelstad.xyz/links/7ed10c99c861/) (latent.space, October 14, 2024)

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## Elsewhere

- Wayback Machine: https://web.archive.org/web/*/https://www.latent.space/p/o3-pro
