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An Empirical Study of Harness Design for Coding Agents

Coding harnesses shape how autonomous coding agents translate model capabilities into long-horizon software-engineering performance, yet existing…

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Why am I seeing this Ranked on source trust — arXiv

It ranks mainly on source trust: arXiv is the most reliable outlet we track on this subject, and is the only one on the story so far.

The classifier could not identify the subject from the text, so the section was inherited from the source feed. We do not summarise what we cannot identify — this one links straight out.

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Blended score 0.519 — every figure below is computed, none of it is editorial.
FactorWeightScore ContributionWhere it came from
Corroboration 0.35 0.39 +0.135 26% 1 independent org on the story. Tier-3 aggregators never corroborate — they can show something is circulating, never that it is true.
Source trustleads 0.25 0.85 +0.212 41% arXiv is the highest-trust source on this story and is first-party — the organisation announcing its own news. Trust is taken from the best source, not averaged.
Pickup rate 0.20 0.00 +0.000 0% One counted organisation, so there is no spread to measure — nothing has picked this up to set a rate.
Freshness 0.20 0.85 +0.171 33% Halves every 10 hours from the newest item on the story. This is the only factor that rewards a story for nothing more than being recent.

Corroboration counts distinct organisations, once each, and only from tiers 1 and 2. Freshness halves every 10 hours, so this ranking is a snapshot and will differ at the next build.

Read the full article at Arxiv →

What happened

Coding harnesses shape how autonomous coding agents translate model capabilities into long-horizon software-engineering performance, yet existing work typically evaluates harnesses as monolithic systems, leaving the effectiveness of individual components unclear. To enable component-level comparisons, we study this question with a lightweight coding harness whose execution loop is fixed while three components are varied: planning, action space, and context management. Across four models evaluated on SWE-Bench Verified and Terminal-Bench 2.1, we evaluate 176 matched settings spanning five context-management strategies, four context-window budgets, and targeted ablations of planning and action space.

1independent orgs
52story score
0velocity
85source trust
1passes seen

How this story arrived

Ordered by when each source was first observed, which is what the velocity figure is computed from. Publishers backdate; observed order does not.

  1. 01 Arxivfirst-party first seen An Empirical Study of Harness Design for Coding Agents

Overclock clusters coverage from independent sources and grades it automatically. The figures above are computed, not editorial. This page summarises and links to reporting by the outlets named — follow the links for the original work.