Finally! A Standard for AI Coding Agents (Agents.md Explained) @engineerprompt

Uploaded August 2025 | Updated September 2026, 2 weeks ago

Agents.md is a simple, open standard to replace the mess of agent-specific rule files. In this video, I explain how agents.md works, how to add it to your repo (even mono-repos), migration tips, and which tools haven’t adopted it yet.

LINKS
https://agents.md/
github.com/openai/agents.md
https://x.com/romainhuet/status/1957924964105179455
https://x.com/FactoryAI/status/1957926852020039767
docs.anthropic.com/en/docs/claude-code/overview
https://x.com/shadcn/status/1955254151807635602
modelcontextprotocol.io/docs/getting-started/intro
llmstxt.org

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0:00 Why rule files are broken
1:12 What is Agents.md
3:05 Example file & structure
5:02 Mono-repo / nested files
6:30 Migration tips
8:05 Who’s missing?
9:10 Final advice

Finally! A Standard for AI Coding Agents (Agents.md Explained)

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$DeepSeek V4 Flash: The Best Open Model You can Actually Run! DeepSeek V4 Flash (Official) Runs Locally: Benchmarks, Cost, and DGX Spark Setup I test the official DeepSeek V4 Flash (July 31 edition) running entirely locally and break down DeepSeek’s released benchmarks, where it beats the prior V4 Pro/Flash preview and even outperforms larger models like GLM 5.2, while approaching Opus 4.8 for a fraction of the size. I also explain why benchmark harnesses matter (including DeepSeek’s agent harness and an OpenAI harness example) and highlight internal DS Bench results. I cover pricing (about $0.02/M input tokens and ~$0.30/M output tokens), token efficiency on the AI Index cost curve, and agentic coding results like Terminal Bench. Then I demo Open Code harness runs (Pokémon encyclopedia and an International Space Center tracker), show ~20–30 tok/s on two DGX Sparks in FP4, discuss the 1M context window, hardware/VRAM needs for 4-bit and 3-bit, and options like Dwarf Star for SSD offloading and mixed precision. Thanks to @NVIDIADeveloper for DGX Sparks. LINK: https://www.deepseek.com/en/ https://api-docs.deepseek.com/guides/responses_api/ https://github.com/antirez/ds4 https://x.com/UnslothAI/status/2083231049434435596 https://artificialanalysis.ai/#intelligenceDwarfStar https://x.com/stevibe/status/2083120066678464750 Video: https://youtu.be/9gHcmhUDJfw Long Running Agents: https://youtu.be/ju7R6jer6_M My voice to text App: whryte.com Website: https://engineerprompt.ai/ RAG Beyond Basics Course: https://prompt-s-site.thinkific.com/courses/rag Signup for Newsletter, localgpt: https://tally.so/r/3y9bb0 0:00 - Introduction to DeepSeek V4 Flash 0:55 - Shocking Benchmark Results & Performance Efficiency 0:2:42 - The Impact of Optimized Harnesses on Performance 0:4:23 - Pricing & The Pareto Frontier of Cost vs. Intelligence 0:5:04 - Running DeepSeek V4 Flash Locally 0:7:20 - Live Demo: Agentic Coding & Pokemon Encyclopedia Test 0:8:34 - Live Demo: ISS Tracker with Real-time UI 0:9:39 - Limitations: Text-only & Multimodal Alternatives 0:10:51 - Hardware Requirements for Local Setup 0:12:52 - Final Results & Summary$

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