Benchmarking RAG Architectures Locally on a Real Financial PDF — Part 1: The Text Layer
Author(s): Ali Enver Arslan Originally published on Towards AI. Benchmarking RAG Architectures Locally on a Real Financial PDF — Part 1: The Text Layer Part 1 of a three-part series. Some of the most useful documents in a bank are also the …
Loop Engineering
Author(s): Rick Hightower Originally published on Towards AI. The Bottleneck Is Not the Model. It is you. Stop being the loop. Start designing the system that does the work. Let’s play AI buzzword bingo! After introducing the term “Loop Engineering,” the article …
Claude Agent SDK Custom Tools and MCP: The Built-In Tools Got You Started. These Three Moves Are How the Agent Grows Up.
Author(s): Rick Hightower Originally published on Towards AI. Part 7: Custom tools let your Claude agent call your code. MCP connects it to the outside world. Subagents let it delegate. Here is how all three fit the same agent without bloating it. …
5 Python Frameworks That Put You Ahead of 90% of AI Beginners
Author(s): Divy Yadav Originally published on Towards AI. Not a list to memorize. The 5 real gaps that decide whether your AI project ships, or dies on your laptop. A beginner spent three weekends building an AI app that summarized PDFs. It …
Vector Database for RAG (The Top 10 to Know in 2026)
Author(s): Asad Iqbal Originally published on Towards AI. Qdrant alternatives, including local + open source vector db If you are not a premium Medium member, read the full guide FREE here and consider joining medium to read more such guides. The article …
Building AI Agents in Rust — part 4
Author(s): Enzo Lombardi Originally published on Towards AI. State machines for multi-step tasks The loop in Part 1 handles a class of question that fits in one breath: read this file, list that directory, answer the user. Two turns, three turns, done. …
Building AI Agents in Rust — part 5
Author(s): Enzo Lombardi Originally published on Towards AI. Multi-agent crews The single-agent loop in Part 1 was enough for one question, one tool, one answer. The state machine in Part 4 handled a task with phases. Neither helps when the work itself …
Building my own LLM-Wiki Research Team
Author(s): Dylan Tartarini Originally published on Towards AI. Compounding knowledge using AI Agents Some time ago, Andrej Karpathy released a Github GiST containing a guide, or better, an intuition on how to build one’s own personal knowledge base. The core philosophy behind …
Why ChatGPT Is More Than Autocomplete
Author(s): GSO1 Originally published on Towards AI. Why ChatGPT Is More Than Autocomplete Figure by the author with assistance from Claude (Anthropic) Calling a large language model (LLM) like ChatGPT “autocomplete” is not exactly wrong, but it is deeply misleading. Most of …
Part 13 — Design the Recommender System
Author(s): Utkarsh Mittal Originally published on Towards AI. Part 13 — Design the Recommender System Part 12 — https://medium.com/p/75cf0a345156 The article explains how to design a production recommender system using a real end-to-end scenario and concrete latency, data, and training considerations. It …
The Best Engineers Stopped Writing Prompts: The 4 Layers That Replaced Prompt Engineering
Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. The Best Engineers Stopped Writing Prompts: The 4 Layers That Replaced Prompt Engineering Boris Cherny built Claude Code. In June 2026 he said the quiet part out loud: “I don’t …
Your Language Model Cannot Say Certain Sentences. The Reason Is the Rank of a Matrix. Let Us Prove It With Tiny Numbers, By Hand.
Author(s): Dr Swarneendu AI Originally published on Towards AI. There are next-word predictions your model is mathematically forbidden from making. Not unlikely. Forbidden, the way a piano with too few keys cannot play a note that lies past its keyboard. The proof …
Every Python Concept a Generative AI Developer Actually Needs to Know
Author(s): DhanushKumar Originally published on Towards AI. Every Python Concept a Generative AI Developer Actually Needs to Know From async coroutines that power real-time LLM streaming, to memory tricks that let you process million-document datasets — the complete map, written for engineers …
Build a Hybrid RAG System with FAISS, BM25, LangGraph and Claude Sonnet Model
Author(s): Alpha Iterations Originally published on Towards AI. Build a Hybrid RAG System with FAISS, BM25, LangGraph and Claude Sonnet Model Combine semantic search and keyword search into one powerful document Q&A app using Claude Sonnet 4.6 API, step by step tutorial …
Loop Engineering: The Missing Governance Layer for Reliable AI Agents
Author(s): Mike Oller Originally published on Towards AI. credit Author: generated by GPT Image 2.0 Loop Engineering: The Missing Governance Layer for Reliable AI Agents By Mike Oller | AI Tool insider I’ve spent the last year building AI agents that do …
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