AI Tools & Frameworks Directory

A Beginner's Guide to Working with Claude Design • 5 Best AI Tools for Data Analysis You Should Try in 2026 • 5 Books That Will Deepen Your Understanding of Large Language Models • Is KimiClaw a Useful Tool?

A hybrid LLM application pattern that combines a predefined workflow with adaptive agent behavior The post Put the Agent Inside the Workflow appeared first on Towards Data Science.

How a seemingly harmless move to a multi-agent architecture quietly tripled our LLM costs and what actually fixed it. The post The 3× Token Bill We Didn’t See Coming appeared first on Towards Data Science.

This chapter is divided into four parts; they are: • Autoregressive Generation • Prefill and Decode • A Simple KV Cache • Memory Usage of the KV Cache A decoder-only transformer model predicts the next token from the tokens that came before it.

Building a voice-controlled AI agents isn't hard, this article breaks the pipeline into its real components: streaming speech recognition, turn detection, streaming generation, interruption handling, and tool calling under voice constraints and shows what each one is responsible for.

Check out these five books on building, fine-tuning, and deploying large language models.

July 2026 was the busiest month for frontier model releases the field has seen. Four major labs shipped flagship or near-flagship models, two well funded newcomers shipped their first, and the largest open weight model ever published went up for download, all inside thirty one days. Read as a list, ...

I used Claude Code daily for months before realizing that claude --help hides many of its most useful capabilities. I kept restarting fresh sessions, repeatedly explaining the same project structure, simply because I did not know a better workflow existed. While debugging an unrelated issue, I disco...

In this article, you will learn the seven architectural components that separate a production-grade agentic AI system from a demo script, and how each one...

Discover 7 essential machine learning algorithms that every data scientist should know before reaching for LLMs and generative AI, with simple explanations and practical Python code.

Prompt engineering helps you write better prompts—but it doesn’t help you change them safely. This article explores a common production failure where a simple variable rename breaks every live call, and introduces a lightweight static analysis tool that treats prompts like contracts, catching breaki...

Learn why clear business goals, data quality, simple models, careful validation, realistic costs, and human judgment matter more than chasing the latest technology.

Building an ALNS heuristic in Python for vehicle routing, time windows, capacity constraints, and mandatory driver breaks. The post Los Movimientos, Part II: Solving Large Pickup-and-Delivery Problems with Adaptive Large Neighborhood Search appeared first on Towards Data Science.

Five resources covering SLM architecture, fine-tuning, agentic workflows, and local deployment for data professionals.

This is the opening piece of a four-part deep dive series, on building a high-frequency streaming pipeline against a live public API. The data source is openSenseMap, a citizen-science IoT network used for climate research, mostly in Germany. A live public API is what makes it useful: it produces da...

Five models, sustained generation, real wall-socket energy at $0.31/kWh — and the surprise the RTX-3090 numbers predicted, only bigger. The post How Much Does a Local LLM Actually Cost to Run? I Measured Every Watt on Apple Silicon appeared first on Towards Data Science.

from custom integrations to a universal standard for tool access The post MCP Explained: How Modern AI Agents Connect to the Real World appeared first on Towards Data Science.

AI-agent development has progressed through overlapping phases: prompt engineering, context engineering, tool use, autonomous loops, memory systems, and multi-agent coordination. A newer focus is graph engineering, which treats AI applications as explicitly designed workflows rather than a single au...

Compare KimiClaw's cloud-hosted AI agent platform against self-hosted OpenClaw across setup, privacy, and automation capabilities.

Anthropic has released Claude Opus 5. The fourth model in two months, if you are keeping count. Most people are not. This one matters more than the count suggests. Opus is the workhorse tier, the model that does the actual paid work, and it just got a step change rather than a bump. Anthropic’s own ...

Memory & State For AI Agents Building an AI agent can be tricky. Keeping it on track over a six-month deployment is incredibly hard. LLMs...

This article shows you up all the steps in building and deploying your first autonomous AI agents from start to finish.

Top 5 MCP Servers for High Performance Agentic Development • 10 Newsletters Keeping You Ahead in AI • Kaggle + Google’s Free 5-Day Agentic AI Course • Language Model Hallucination Evaluation with GraphEval

I generated a Kármán vortex street without solving a single fluid equation. Here's how the Lattice Boltzmann Method gets there instead, derived from first principles, implemented in C++, and run on a supercomputer. The post The Fluid Simulator That Doesn’t Solve the Fluid Equations appeared first on...