Towards Data Science By Emmimal P Alexander

Coding Agents Can Solve the Task — But How Much Work Did They Waste?

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The article "Coding Agents Can Solve the Task — But How Much Work Did They Waste?" examines the performance of coding agents using real repositories and seeded agent decisions. It reports on 50,400 runs, highlighting metrics such as wasted turns, patch churn, and the effectiveness of different harness rules. The study provides insights into how these agents manage code modifications and the efficiency of their decision-making processes.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at Towards Data Science.

Towards Data Science
Oct 9

Where Does the Money Go Across Long-Running Coding Agents?

The article titled "Where Does the Money Go Across Long-Running Coding Agents?" explores the financial aspects of maintaining and operating coding agents over extended periods. It highlights the costs associated with controlling these agents and examines how resources are allocated during their lifecycle.

By Daniel Miller
Towards Data Science
Aug 26

How to Effectively Solve 100+ Tasks with Claude Code

The article "How to Effectively Solve 100+ Tasks with Claude Code" discusses strategies for working more efficiently with coding agents. It focuses on practical approaches to manage and complete a large number of tasks using Claude Code. The post was originally published on Towards Data Science.

By Eivind Kjosbakken
Hugging Face Trending Papers
Jul 15

Early Adoption of Agentic Coding Tools by GitHub Projects

Agentic coding tools are increasingly capable of generating and submitting pull requests (PRs) to software projects, introducing new forms of human-agent collaboration in software development. While prior studies have examined PR-level outcomes of agent-generated contributions, less is known about how agentic coding tools are adopted and managed at the project level.