Agents got good. The hard part now is everything around them.

The post Your Agent Doesn't Need More Freedom appeared first on Towards Data Science.

Real repositories, seeded agent decisions: what 50,400 runs show about wasted turns, patch churn, and which harness rules help

The post Coding Agents Can Solve the Task — But How Much Work Did They Waste? appeared first on Towards Data Science.

Re-reading my own IBM patent on real-time concert feedback as what it actually was: an agentic loop with multimodal perception, memory-grounded inference, and a human in the loop. What it got right, and what a decade of hindsight teaches agent builders today.

The post We Specified an AI Agent in 2016. We Called It Analytics. appeared first on Towards Data Science.

Add architectural guardrails around how agents read untrusted sources and use them in the workflow.

The post How Can AI Agents Read Untrusted Sources Safely? appeared first on Towards Data Science.

AI Agents for Beginners, Part 1

The post Build Your First AI Agent with One Tool Call appeared first on Towards Data Science.

AI agents can now write more code than any of us can read. That changed how I think about AI.

The post Stop Using AI. Start Hiring It. appeared first on Towards Data Science.

Mapping structural variance against execution outputs to estimate coding agent reliability without ground truth.

The post The Consistency Quadrant: A Visual Guide to LLM Reliability appeared first on Towards Data Science.

Towards Spec-Driven Test Automation: Part 3

The post A Google Team Measured Half of My Argument, and Left the Other Half Open appeared first on Towards Data Science.

A controlled test of Gemini, DeepSeek, ChatGPT, and Claude on leakage, reporting delays, promotion effects, and structural breaks.

The post I Hid Four Traps in a Forecasting Task. Here Is What Four AI Assistants Did. appeared first on Towards Data Science.

From guarding one agent to steering a fleet

The post How to Govern AI Agents appeared first on Towards Data Science.

Trying to answer the question of "Can LLM agents discover?" through the lens of creativity

The post Measuring the Creativity Potential of LLM Agents appeared first on Towards Data Science.

Coordinating agent capability development with the application it powers

The post Where the Agent Development Lifecycle Fits appeared first on Towards Data Science.

Giving an LLM permission to act, in 9 steps

The post How to Build a Control Plane for AI Agents appeared first on Towards Data Science.

I traced 2,500 listing checks with Weights & Biases Weave, removed avoidable model work one change at a time, and scored every version against the same answers.

The post Can an Apartment Search Agent Call the Model Fewer Times and Still Find Good Matches? appeared first on Towards Data Science.

One run, and what it actually proves

The post Towards Spec-Driven Test Automation: Part 2 appeared first on Towards Data Science.

Agent design patterns every data engineer must know

The post How to Design Architectural Guardrails Around AI Agents appeared first on Towards Data Science.

Every boundary you draw removes a signal your tooling was relying on. That is a structure problem, not a search problem.

The post Good Architecture Deletes the Signals Your Agent Depends On appeared first on Towards Data Science.

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

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