Master Full-stack AI Engineering In today's newsletter: Fine-tune any LLM directly from Claude! Speculative decoding in LLMs. tSNE Projections can be misleading. TODAY'S ISSUE fine-tuning Fine-tune any LLM directly from Claude! We built a Hugging Face fine-tuning studio that lets you fine-tune any LLM directly from Claude: The app connects to the HF Hub for model and dataset search. It handles chat template formatting for the training data, and lets you configure LoRA rank, quantization,...
4 months ago • 7 min read
Master Full-stack AI Engineering In today's newsletter: Markov decision processes and value functions in RL. How LLM inference works internally. TODAY'S ISSUE AI engineering Markov decision processes and value functions in RL Last week, we launched a hands-on course series on reinforcement learning. Part 2 is now available, and you can read it here → Reinforcement learning nanodegree part 2 Part 1 gave you the RL interaction loop and the exploration-exploitation tradeoff through bandits, and...
4 months ago • 9 min read
Master Full-stack AI Engineering In today's newsletter: Two skills to fix the context gap in Claude Code. Naive RAG vs Blockify, explained visually. DevOps vs. MLOps vs. LLMOps. TODAY'S ISSUE Hands-on Two skills to fix the context gap in Claude Code Claude Code has two context gaps that no amount of CLAUDE.md optimization will fix. The first is web scraping. web_fetch doesn’t return raw page content. It runs the page through a smaller model and returns a summary with a 125-character quote...
4 months ago • 7 min read
Master Full-stack AI Engineering In today's newsletter: Technical LLM interview question! 10 must-use slash commands in Claude Code. [Hands-on] Build a Real-time Federated Data Engine for Agents. TODAY'S ISSUE Agents Technical LLM interview question! You have 80,000 agent trajectories from production. You need to find top 100 worth reviewing to improve your agent. No LLM allowed to evaluate trajectories. How will you do this? Let’s look at some approaches. The simplest solution one could...
4 months ago • 7 min read
Master Full-stack AI Engineering In today's newsletter: The anatomy of diffusion LLMs. Evaluate MCP-powered LLM apps. 20 most common magic methods in Python OOP. TODAY'S ISSUE Deep dive The anatomy of diffusion LLMs This week’s deep dive covers one of the most important architectural shifts happening in language modeling right now: diffusion LLMs. Read the full Part 1 deep dive here → Diffusion LLMs Part 1 It builds a complete understanding from first principles: how autoregressive generation...
5 months ago • 7 min read
Master Full-stack AI Engineering In today's newsletter: Open-source plugin to give coding agents live web data. Build agents that don’t fail in production. Manual RAG pipeline vs unified knowledge bases (with demo). TODAY'S ISSUE together with bright data Open-source plugin to give coding agents live web data A key limitation of coding agents today is that they can’t fetch live web data on their own. And platforms like LinkedIn, X, and Reddit (where a ton of developer discussions happen) are...
5 months ago • 5 min read
Master Full-stack AI Engineering In today's newsletter: An Open-Source Autonomous BI Agent. A Memory-efficient technique to train large models. Types of memory in AI Agents. TODAY'S ISSUE Open-source An Open-Source Autonomous BI Agent MindsDB just open-sourced Anton, an autonomous BI agent that turns plain-language questions into full dashboards. You ask something like “Show me NVIDIA’s profit margins,” and Anton handles everything: figuring out the right data source, writing and executing...
5 months ago • 5 min read
Master Full-stack AI Engineering In today's newsletter: DailyDoseofDS is now on Instagram! Concepts of LLM serving. Build a 100% local MCP server and client. [RECAP] A mini crash course on AI Agents! TODAY'S ISSUE AI engineering DailyDoseofDS is now on Instagram! This newsletter regularly breaks down RAG architectures, AI agents, LLM internals, and everything in between. Now we’re bringing all of that to Instagram too, in a format that’s quick to consume and hard to ignore. We’re already 240...
5 months ago • 6 min read
Master Full-stack AI Engineering In today's newsletter: A disaster-free way to run OpenClaw on real data/apps! Filter Chains at the proxy layer The filter and config in practice Setup OpenClaw <> Plano Stacking filters Output filters The takeaway TODAY'S ISSUE hands-on A disaster-free way to run OpenClaw on real data/apps! Summer Yue from Meta was testing OpenClaw on a small inbox for weeks. It read emails, suggested what to archive, and waited for her approval before doing anything. Every...
5 months ago • 9 min read