HN speckx 4/20/2026

The Code-Adjacent Power of AI

Beyond direct code writing, AI assistants provide value in code-adjacent activities like documentation, refactoring, and project planning on long-running projects.

HN jdkee 4/20/2026

RLMs are the new reasoning models

Recursive Language Models (RLMs) combine reasoning and tool use into single inference abstraction, advancing beyond separate reasoning models.

LB bernat.tech by gaborjbernat 4/20/2026

PyTexas 2026 Recap

PyTexas 2026 conference recap covering tutorials and talks with themes on domain sovereignty and AI agents writing code.

HN hardmaru 4/20/2026

Can LLMs Flip Coins in Their Heads?

Research exploring whether LLMs can perform genuine probabilistic reasoning or simulate randomness. Model capability analysis.

HN cloudpresser 4/20/2026

Observability for AI Agents

Deep dive on observability and tracing for AI agent systems. Addresses monitoring failures that appear as valid outputs.

HN Brajeshwar 4/20/2026

RL Scaling Laws for LLMs

Research on reinforcement learning scaling laws for LLMs, extending pretraining scaling law predictability to RL training phases.