Towards Data Science
Jun 3
What AI Agents Should Never Do on Their Own
How to set the rules that keep agents effective and out of trouble The post What AI Agents Should Never Do on Their Own appeared first on Towards Data Science .
How to Debug AI Coding Agents When They Change the Wrong Thing
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 Coding Agents When They Change the Wrong Thing appeared first on Towards Data Science .
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Towards Data Science
Aug 6
I Built a Tool-Calling Agent in Python. Here’s How I Debugged It
A minimal loop with real API calls, validation, compact outputs, and trace evidence before adding an agent framework The post I Built a Tool-Calling Agent in Python. Here’s How I Debugged It appeared first on Towards Data Science .
Towards Data Science
2d ago
Webwright: Why AI Web Agents Should Write Code, Not Click
For years, web agents have worked one click at a time—and often fallen apart on long tasks. Microsoft Research’s Webwright makes a different bet: give the model a terminal and let it write the program instead.
Towards Data Science
Jul 6
How to Run End-to-End Tests with Claude Code
Increase the effectiveness of your coding agents through end-to-end testing. The post How to Run End-to-End Tests with Claude Code appeared first on Towards Data Science .
OpenAI Blog
Mar 19
How we monitor internal coding agents for misalignment
How OpenAI uses chain-of-thought monitoring to study misalignment in internal coding agents—analyzing real-world deployments to detect risks and strengthen AI safety safeguards.
Towards Data Science
Jun 21
Tool Calling, Explained: How AI Agents Decide What to Do Next
Understanding ow LLMs interact with the world around them, from returning data to taking action The post Tool Calling, Explained: How AI Agents Decide What to Do Next appeared first on Towards Data Science .
Towards Data Science
Jun 10
How to Refactor Code with Claude Code
Improve coding agent productiveness with refactored code The post How to Refactor Code with Claude Code appeared first on Towards Data Science .
arXiv AI
Jul 22
AgentDebugX: An Open-Source Toolkit for Failure Observability, Attribution, and Recovery in LLM Agents
arXiv:2607. 18754v1 Announce Type: new Abstract: LLM agent failures are difficult to debug because the step where an error surfaces is often not the one that caused it.
Towards Data Science
Jul 22
Detecting Vulnerabilities in Agent Skills with SkillSpector: From Green Checkmark to Real Security Judgment
Static analysis nailed the malicious skill and over-flagged the useful one. The gap between those results is where human judgement actually earns its keep.
Towards Data Science
Jul 19
Your AI Agent Passed Every Eval. Finance Still Killed It.
An AI agent passed every metric in the eval harness I published, then the CFO killed it — its successful resolutions cost more than the humans it replaced. The one metric that predicts whether an agent survives production, and how to measure it without a rebuild.
Towards Data Science
Jul 8
Redesign Work Before You Add More AI Agents
Map AI value, design workflows, redefine talent, upgrade the executive team, and measure the business impact. The post Redesign Work Before You Add More AI Agents appeared first on Towards Data Science .
Towards Data Science
Jul 28
MCP Explained: How Modern AI Agents Connect to the Real World
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 .