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- 115-Page Guide to LLM Fine-Tuning
In today’s newsletter:
Motia - Unified Backend Framework for AI Agents
Ultimate Guide to LLM Fine-Tuning
Open Agent Builder - Build, Test and Deploy AI Agent Workflows
Reading time: 3 minutes.
Motia is a backend framework that brings together AI Agents, APIs, background jobs, streams and workflows into a single core primitive.
Think of it as the missing backend for AI agents: a single place to build, run, and observe your entire stack.
Key Features:
One runtime for APIs, event driven jobs, workflows, and agents
Mix Python, JavaScript, and TypeScript in the same workflow
Built in observability with logs, traces, and state management
Visual workbench to build and debug flows in real time
Event driven design to connect APIs, tasks, and AI agents
It’s 100% Open Source
A 115-page guide covers everything you need to fine-tune LLMs, from fundamentals to advanced techniques.
Here’s what it covers:
Task- and domain-specific fine-tuning
Parameter-efficient methods: PEFT, LoRA, QLoRA, DoRA, HFT
Expert-based architectures: MoE, Lamini Memory Tuning, MoA
Alignment and optimization: PPO, DPO
Model simplification: Pruning
If you’re serious about mastering LLM fine-tuning, this is one of the most comprehensive open resources available.
Open Agent Builder is a visual workflow builder for creating AI agent pipelines without writing a single line of code.
Design complex agentic systems visually, connect tools, and deploy instantly with real-time streaming updates.
Key Features:
Drag-and-drop interface for assembling agent workflows.
Live execution with real-time progress.
8 core node types: Start, Agent, MCP Tools, Transform, If/Else, While Loop, User Approval, End.
Template library for pre-built agentic flows.
Native MCP protocol support for extending tool integration.
It’s 100% open-source. Fork the repo and build your own workflow app.
That’s a Wrap
That’s all for today. Thank you for reading today’s edition. See you in the next issue with more AI Engineering insights.
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