Episode 62: Codex 0.136, Stanford's Agent Guidelines, AWS OpenAI, and GPU Efficiency

About this episode

This episode discusses advancements in AI agent guidelines, cloud computing integrations, and GPU resource predictions.

AgentStack Daily EP062 leads with Codex `rust-v0.136.0`: better TUI diagnostics and error context, improved app-server lifecycle handling, named hooks and permission scopes, Python SDK and Node SDK improvements, and non-interactive installation support. Stanford's CS336 course publishes a formal AI agent guidelines document that reaches 1,863 stars in under 24 hours — institutional validation that agent workflow guidelines are becoming a first-class engineering concern. OpenAI puts GPT-4.5, o3, and Codex on AWS Bedrock, completing the pattern where both major labs distribute through the same cloud. Expanse from YC P26 uses cluster-specific fine-tuned models to predict GPU job resource needs and outperforms frontier LLMs by 8x on that task, backed by real HPC telemetry and SLURM/Kubernetes integration. The project radar covers agent OS for hardware, terminal context managers, MCP workflow templates, and physical agent scheduling. Show notes: https://tobyonfitnesstech.com/podcasts/episode-62/

People in this episode

Hosts: Nova, Alloy

Topics covered

• AI agents
• GPU efficiency
• cloud computing
• software development
• technology guidelines

Keywords

• Codex
• AWS
• OpenAI
• GPU
• AI agents
• Stanford
• rust
• telemetry
• Kubernetes

Mentioned in this episode

Organizations: Stanford, OpenAI, AWS, YC P26, SLURM, Kubernetes

Products: GPT-4.5, Codex, rust-v0.136.0

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