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Most coding agents treat prompt construction like retrieval: gather more files, add more context, hope the model figures it out. But that approach breaks down f

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 T

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 C

In five to ten years, the sharpest manager in your company might not be human, might not sleep, and might exist entirely in shared GPU memory. This is the syste

A practical tutorial for recording model tool requests, real function results, patches, checks, screenshots, and a saved run log. The post How to Debug AI Codin

A friendly introduction to one of the most powerfull optimization techniques using the uncapacitated facility location problem The post How Benders Decompositio

How one open-source ecosystem made state-of-the-art AI accessible The post The Python Ecosystem That Changed AI Development appeared first on Towards Data Scien

Optimise how you interact with your coding agents The post How to Organize All of Your Coding Agent Tasks appeared first on Towards Data Science .

What it actually takes to turn a company's scattered knowledge into something an LLM can reliably use — and why the demo is 5% of the work. The post How to Buil

The full conjecture is stated over abstract fields, but the counterexample is a concrete 3D function that we can explain and visualize using familiar geometric

How statistical physics explains the transition from deterministic predictions to generative AI. The post How to Decode the Temperature Parameter in LLMs appear

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 v

Why prediction-driven variable selection misses confounders and how Bayesian Adjustment for Confounding attempts to fix it. The post Why Your Best Predictive Mo

Building an ALNS heuristic in Python for vehicle routing, time windows, capacity constraints, and mandatory driver breaks. The post Los Movimientos, Part II: So

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 openSen

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

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 Toward

You "vibe coded" the import. Understand Adam's optimization dynamics, why it fails spectacularly, and how to fix it. The post Don’t Just “Throw Adam at It”: Mis

The idea that makes backpropagation possible. The post Backpropagation Explained for Beginners (Part 2): There Has to Be a Better Way appeared first on Towards

Using mathematical optimization to solve a pickup-and-delivery problem with time windows. The post “Los Movimientos”: The Routing Problem That Nearly Broke My S

In a world where human time is expensive, learn how to use it only when really necessary The post Reducing Human Annotation with ML Active Learning appeared fir

The mean keeps making its usefulness felt in all sorts of situations, often in truly non-obvious ways The post The Most Beautiful Statistic: The History and the

A practical reproduction of three retrieval baselines, including the crashes, fixes, and score checks that matter for RAG systems. The post How I Reproduced BM2

Maximize your efficiency with Claude Code The post How to Efficiently Prompt Claude Code appeared first on Towards Data Science .