Amanpreet Singh (@apsdehal) / X

wow

We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math. It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training. We call this Weight-Space Programming:

Readers added context

LLM was given weights explicitly as text in prompt and used code/forward passes (per authors' logs) to ablate Qwen looping direction, a known thinking-mode issue per model card. Primarily fixed repetition in that mode, not general 'natively' improving weights/math. rikiyat.github.io/blog/weight-sp… github.com/RikiyaT/lm_und… huggingface.co/Qwen/Qwen3.5-0… huggingface.co/RikiyaT/Qwen3.…

A year ago, everybody was pushing chat as a universal interface in their applications. Every system of record, every SaaS application. But, as agents start to do actual work, the reverse is happening and the UI is now showing up embedded in the chat. 1/n

OpenAI

@OpenAI

Oct 7

GPT-6 and Intelligent UI, now rolling out in ChatGPT for everyone. Intelligent UI in ChatGPT delivers fast, interactive answers that make everyday questions more visual, complex topics easier to grasp, and interactive tools for your task available on the spot.

Good article. It gives you a glimpse of how the interaction with agents will look in the future as they start doing more work. Super Agents are emerging as a new interaction layer across the board: projects in Claude Code and Cursor also build on the same idea. As we trust

Exploring Super-agent Design: Towards a More Autonomous Agent System

The original article is in Chinese. This is a machine translation. This article discusses architectural ideas. It is not an introduction to existing features of DeepSeek Harness. 1. Super-agent Over

Eliciting the tribal knowledge in people's heads that was never written down anywhere is an art and the biggest barrier to the diffusion of AI in enterprises.

gabriel

@gabriel1

Oct 21

"company brain" startups that construct information from internal messages and documents when they realize 90% of information only exist in peoples heads: 😭😭😵‍💫😵‍💫

The job is shifting from doing to verifying

Consider this real-world problem: you want to automate receipt generation by aggregating numbers from multiple systems of records into a single receipt for invoicing. But if the agent gets even 1% of

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