Github Repo: github.com/rasbt/LLMs-from-s…
→ View original post on X — @sumanth_077, 2026-04-01 13:21 UTC
@sumanth_077
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Build Large Language Models from Scratch: Complete Book Repository
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Build a Large Language Model from scratch! This repository contains the code examples for developing, pretraining, and finetuning a LLM from scratch. It is the official codebase for the book Build a Large Language Model (From Scratch). Notebook examples are included for each chapter: Chapter 1: Understanding Large Language Models Chapter 2: Working with Text Data Chapter 3: Coding Attention Mechanisms Chapter 4: Implementing a GPT Model from Scratch Chapter 5: Pretraining on Unlabeled Data Chapter 6: Finetuning for Text Classification Chapter 7: Finetuning to Follow Instructions Link to the repo in the comments!
→ View original post on X — @sumanth_077, 2026-04-01 13:21 UTC
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Unified Agent Definition Across Claude Code CrewAI OpenAI
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Absolutely, same agent definition across Claude Code, CrewAI, and OpenAI is what makes it useful
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GitAgent: Framework-Agnostic Standard for Portable AI Agents
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If you found it useful, reshare it with your network Follow me → @Sumanth_077 for more insights and tutorials on AI Engineering! nitter.net/Sumanth_077/status/203… Sumanth (@Sumanth_077) Turn any git repo into an AI agent! GitAgent is a framework-agnostic standard that lets you define agents as git repositories. Every AI framework has its own structure. Claude Code, OpenAI, LangGraph, CrewAI, AutoGen all use different formats. You build an agent in one framework and it's locked there. No portability. No reuse. GitAgent fixes this. Your repository becomes your agent. Drop two files into a git repo (agent.yaml for the manifest, SOUL. md for identity) and it becomes a portable agent definition. Export it to any framework with adapters. You get git's workflow for free. Version control your prompts. Roll back broken changes with git revert. Fork public agents, customize them, and PR improvements back. Run gitagent validate in GitHub Actions to catch issues before deployment. The structure is flexible. Start with just agent.yaml and SOUL. md. Add skills, tools, workflows, memory, and compliance rules as you need them. Everything is optional except those two core files. It works across frameworks. Export to Claude Code, OpenAI Agents SDK, CrewAI, or as a raw system prompt. Same agent definition, different runtimes. Built for compliance. First-class support for FINRA, Federal Reserve, and SEC requirements. Segregation of duties built into the spec. Define roles, conflict matrices, and handoff workflows in agent.yaml. Link to the Github Repo in comments! — https://nitter.net/Sumanth_077/status/2038981420664959188#m
→ View original post on X — @sumanth_077, 2026-03-31 14:07 UTC
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GitAgent Open Source Repository on GitHub
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Github Repo: github.com/open-gitagent/git…
→ View original post on X — @sumanth_077, 2026-03-31 14:07 UTC
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GitAgent: Framework-Agnostic AI Agent Definition Standard
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Turn any git repo into an AI agent! GitAgent is a framework-agnostic standard that lets you define agents as git repositories. Every AI framework has its own structure. Claude Code, OpenAI, LangGraph, CrewAI, AutoGen all use different formats. You build an agent in one framework and it's locked there. No portability. No reuse. GitAgent fixes this. Your repository becomes your agent. Drop two files into a git repo (agent.yaml for the manifest, SOUL. md for identity) and it becomes a portable agent definition. Export it to any framework with adapters. You get git's workflow for free. Version control your prompts. Roll back broken changes with git revert. Fork public agents, customize them, and PR improvements back. Run gitagent validate in GitHub Actions to catch issues before deployment. The structure is flexible. Start with just agent.yaml and SOUL. md. Add skills, tools, workflows, memory, and compliance rules as you need them. Everything is optional except those two core files. It works across frameworks. Export to Claude Code, OpenAI Agents SDK, CrewAI, or as a raw system prompt. Same agent definition, different runtimes. Built for compliance. First-class support for FINRA, Federal Reserve, and SEC requirements. Segregation of duties built into the spec. Define roles, conflict matrices, and handoff workflows in agent.yaml. Link to the Github Repo in comments!
→ View original post on X — @sumanth_077, 2026-03-31 14:07 UTC
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Tracking costs and performance metrics in production AI systems
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Yeah that's true, tracking cost alongside performance is critical for production.
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RAGFlow: Open-Source RAG Engine for Production-Ready PDF Processing
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Turn messy PDFs into production-ready RAG systems! RAGFlow is an open-source RAG engine that handles the parts most frameworks skip. Most RAG tools treat document parsing as solved. Upload a PDF, chunk it, done. But real documents are messy – scanned copies, complex layouts,
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Verification Layer Critical for Building Reliable AI Skills
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Yeah the verification layer is key, otherwise you're just accumulating broken skills
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Learning Mechanisms Differentiate AI From Static Tool Libraries
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Yeah the learning mechanism is what separates this from static tool libraries