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# Ridges’ Linting Winner Reaches 90% Score at 86% Lower Cost
- URL: https://www.tao.media/ridges-linting-winner-reaches-90-score-at-86-lower-cost/
- Published: 2026-11-03T01:39:37.000Z
- Updated: 2026-11-03T01:39:38.000Z
- Description: The Bittensor coding-agent competition rewarded improvements in both task performance and inference efficiency.
- Author: Bart Hillerich
- Tags: Ridges, Subnets, AI, News

Ridges AI, the software-engineering agent network on Bittensor Subnet 62, has completed its Linting competition with a winning agent that scored 90% at an average cost of $0.03 per run. The starting baseline scored 38% and cost $0.21, putting the winner 52 percentage points higher at roughly 86% lower cost.

The winning submission, wingsuit v3, emerged from 821 submissions reported in [Ridges' final results](https://x.com/ridges%5Fai/status/2117339666886369486?ref=tao.media). Fifteen agents were approved for emissions, the subnet's token rewards.

Linting involves checking code against rules intended to catch errors and enforce coding conventions. Ridges organizes coding-agent development into specialized competitions called Niches, where participants, known as miners, compete to improve performance and reduce the expense of running agents.

The [Competition 27 leaderboard](https://www.ridges.ai/agents/27?ref=tao.media) shows how those two objectives shaped the contest. Early in the competition, smCat v1 reached 68%. Its successor, cowrie v0, raised the score to 70% while cutting average cost from about $0.12 to $0.01\. The leaderboard records an 88.7% cost reduction for that improvement.

Later entrants pushed scores higher: butterfly v1 reached 82%, grouse v1 reached 86%, and IAMHERE v5 reached 90%. Wingsuit v3 matched IAMHERE's score but took the lead by using 19.7% less inference spending, the cost of the model calls used to perform the task. Its average runtime was 3 minutes and 43 seconds.

The results follow Ridges' earlier [introduction of cost controls in Competition 22](https://tao.media/ridges-shares-competition-22-results-after-introducing-cost-controls/?ref=tao.media), when it imposed a maximum cost of $0.29 per problem solved. That competition produced nine emissions-approved agents from 419 created.

For its next competition, Ridges is introducing [miner-set baselines through a benchmark phase](https://tao.media/ridges-introduces-miner-set-baselines-with-new-benchmark-phases/?ref=tao.media). Qualifying agents will compete to establish the initial leader before emissions begin. Subsequent entrants will then need to improve on that leader, with the default rules allowing qualification through either a relative score increase of at least 3% or a cost reduction of at least 6% while matching or exceeding its score.