RAG retrieves. Agents act. I built both separately, connected them explicitly, and ran the same nine tasks through all three systems.

The post RAG Isn't an Agent — I Built the Layer Between Retrieval and Action appeared first on Towards Data Science.

I tested TypeSafe AI’s Jev on 3,080 classification tasks to see how its accuracy, latency, calibration, and confidence compare with LLMs — and whether it works as a practical decision layer for AI systems.

The post Jev vs. LLMs: When AI Moves from Generation to Decision-Making appeared first on Towards Data Science.

Get more out of your coding agent subscriptions

The post How to Maximize Your Coding Agent Subscriptions appeared first on Towards Data Science.

Retrieval is not evidence. How to build AI that proves its own claims.

The post Beyond RAGs: Building Actually Truthful AI Harnesses appeared first on Towards Data Science.

Why a green test suite can mean nothing

The post Towards Spec-Driven Test Automation: Part 1 appeared first on Towards Data Science.

Learn how to effectively code up an internal tool using Claude code or Codex

The post Build a Speaker-Recognition App with Claude Code appeared first on Towards Data Science.

Why this matters less for what Astra can do and more for what every other model hasn't been tested for

The post GPT-6 Astra Just Hit OpenAI's Highest Cybersecurity Risk Level appeared first on Towards Data Science.

Five scikit-learn defaults that deserve a closer look before your next model reaches production

The post Your AI Assistant Wrote the Code. Who Checked the Defaults? appeared first on Towards Data Science.

One near miss, four months of running agents, and the question almost nobody is asking: what are you supposed to do while the AI writes the code?

The post AI Made Me 5x Faster. It Also Made Me 5x Worse at My Job. appeared first on Towards Data Science.

How to verify your app aligns with your intent without ever reading a line of generated code.

The post Coding Agents Keep Shipping Silent Failures — Here Is How to Catch Them appeared first on Towards Data Science.

Multi-agent coding systems don't necessarily fail because agents can't communicate. They can fail because important commitments made in conversation have nowhere to live afterward.

The post Multi-Agent Coding Isn’t Enough — Agents Need a Commitment Layer appeared first on Towards Data Science.

Keep your apps looking professional with Claude Code design skills

The post How to Build Consistent Designs with Claude Code appeared first on Towards Data Science.

I built a system that automatically discovers, verifies, and applies relevant requirements from earlier interactions without asking the user where they came from.

The post Coding Agents Don't Need Longer History — They Need Intent Continuity appeared first on Towards Data Science.

Better understand the intent of your coding agents

The post How to 5x Your Communication Effectiveness with Claude Code appeared first on Towards Data Science.

Moving from static model assignment to intelligent, task-level LLM selection.

The post Optimizing LLM Inference Costs in Multi-Agent Systems with Adaptive Model Routing appeared first on Towards Data Science.

My first impressions of OpenAI's new frontier model

The post How to Maximize GPT-6 Astra appeared first on Towards Data Science.

A context window can be technically complete and still describe a world that no longer exists. I built a deterministic benchmark to measure the cost of acting on stale context.

The post Context Windows Don’t Know What’s Still True — I Built a Validity Layer That Does appeared first on Towards Data Science.

I saved my day with a mere $52 bill. But you don't have to repeat my mistake.

The post I Vibe-Coded an App in Just Two Hours (And Regretted It the Next Day) appeared first on Towards Data Science.

How to catch a payload that looks correct but isn't, using a watchdog pattern with working Python.

The post Why Most Multi-Agent Systems Fail Even When Evaluation Passes appeared first on Towards Data Science.