[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]  dTAO For Dummies [@dTAOfordummies](/creator/twitter/dTAOfordummies) on x 1155 followers Created: 2025-07-13 14:01:00 UTC Poor software quality costs the global economy over $XXX trillion annually. A decentralized network deploying competing AI agents could autonomously generate, test, and refine code, transforming development into a scalable, efficient process. #Bittensor Subnet XX @ridges_ai --------------------------------------- What is it? SN62, Ridges AI (formerly AgenTao), is a marketplace for autonomous AI agents specializing in software engineering. Users delegate coding tasks—bug fixes, feature additions, or test generation—to competing AI agents, with rewards based on performance and token holdings. Miners build and deploy agents, while validators ensure quality through benchmarks. --------------------------------------- How It Works Validators create problems from real repositories, like code patches for issues. Miners use tools like SWE-Agent to submit solutions via AI models (supporting OpenAI, Groq, Ollama, or local setups). Scores are based on test pass rates and round-trip correctness, ensuring code aligns with the problem. Incentives penalize low-quality or duplicate submissions. Users interact via a GitHub extension to tag issues for agent resolution. Holding Ridges tokens increases miners' reward shares, fostering competition and quality. --------------------------------------- Why It’s Important This subnet modularizes software engineering into specialized tasks, potentially outperforming centralized tools through decentralized incentives. In a market where AI coding tools are projected to reach $XX billion by 2028, Ridges AI offers a decentralized alternative, avoiding vendor lock-in and promoting collaborative advancement. --------------------------------------- Notable Milestones / Partnerships Launched as AgenTao in late 2024, the subnet open-sourced its agent code in early 2025, achieving over XXXXX updates in the first week and improving agent performance from X% to XX% on SWE-Bench metrics. It supports models from Groq, Ollama, and DeepSeek, with ties to @omegalabs_bt. The rebrand to Ridges AI emphasized modular agent specialization and partnerships with compute-focused Bittensor subnets. --------------------------------------- Real-World Applications Developers can automate open-source tasks, like fixing regressions or upgrading dependencies. Enterprises can speed up feature development in internal repositories. AI researchers can benchmark custom agents against standards like SWE-Bench, advancing autonomous coding. --------------------------------------- How to Use It Install the Ridges AI GitHub extension, tag an issue with @ridges, and specify the task (e.g., "generate unit tests"). Receive quotes in TAO, Ridges tokens, or USD, select a solution, and integrate the code. Miners register on Bittensor, run scripts with their preferred AI model, and monitor performance via the dashboard. Non-technical users, like product managers, can delegate coding, focusing on oversight while agents handle implementation. --------------------------------------- To Sum Up Ridges AI advances software engineering by enabling collaborative AI agents to democratize high-quality code generation, aligning with scalable, open intelligence for developers and innovators worldwide. #AI #AgenticAI $TAO  XXX engagements  **Related Topics** [marketplace](/topic/marketplace) [coins ai agents](/topic/coins-ai-agents) [decentralized](/topic/decentralized) [coins ai](/topic/coins-ai) [$sn62](/topic/$sn62) [coins bittensor ecosystem](/topic/coins-bittensor-ecosystem) [bittensor](/topic/bittensor) [coins layer 1](/topic/coins-layer-1) [Post Link](https://x.com/dTAOfordummies/status/1944396647863316746)
[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]
dTAO For Dummies @dTAOfordummies on x 1155 followers
Created: 2025-07-13 14:01:00 UTC
Poor software quality costs the global economy over $XXX trillion annually. A decentralized network deploying competing AI agents could autonomously generate, test, and refine code, transforming development into a scalable, efficient process.
#Bittensor Subnet XX @ridges_ai
What is it?
SN62, Ridges AI (formerly AgenTao), is a marketplace for autonomous AI agents specializing in software engineering.
Users delegate coding tasks—bug fixes, feature additions, or test generation—to competing AI agents, with rewards based on performance and token holdings. Miners build and deploy agents, while validators ensure quality through benchmarks.
How It Works
Validators create problems from real repositories, like code patches for issues.
Miners use tools like SWE-Agent to submit solutions via AI models (supporting OpenAI, Groq, Ollama, or local setups).
Scores are based on test pass rates and round-trip correctness, ensuring code aligns with the problem.
Incentives penalize low-quality or duplicate submissions.
Users interact via a GitHub extension to tag issues for agent resolution.
Holding Ridges tokens increases miners' reward shares, fostering competition and quality.
Why It’s Important
This subnet modularizes software engineering into specialized tasks, potentially outperforming centralized tools through decentralized incentives.
In a market where AI coding tools are projected to reach $XX billion by 2028, Ridges AI offers a decentralized alternative, avoiding vendor lock-in and promoting collaborative advancement.
Notable Milestones / Partnerships
Launched as AgenTao in late 2024, the subnet open-sourced its agent code in early 2025, achieving over XXXXX updates in the first week and improving agent performance from X% to XX% on SWE-Bench metrics.
It supports models from Groq, Ollama, and DeepSeek, with ties to @omegalabs_bt.
The rebrand to Ridges AI emphasized modular agent specialization and partnerships with compute-focused Bittensor subnets.
Real-World Applications
Developers can automate open-source tasks, like fixing regressions or upgrading dependencies.
Enterprises can speed up feature development in internal repositories. AI researchers can benchmark custom agents against standards like SWE-Bench, advancing autonomous coding.
How to Use It
Install the Ridges AI GitHub extension, tag an issue with @ridges, and specify the task (e.g., "generate unit tests").
Receive quotes in TAO, Ridges tokens, or USD, select a solution, and integrate the code. Miners register on Bittensor, run scripts with their preferred AI model, and monitor performance via the dashboard.
Non-technical users, like product managers, can delegate coding, focusing on oversight while agents handle implementation.
To Sum Up
Ridges AI advances software engineering by enabling collaborative AI agents to democratize high-quality code generation, aligning with scalable, open intelligence for developers and innovators worldwide.
#AI #AgenticAI $TAO
XXX engagements
Related Topics marketplace coins ai agents decentralized coins ai $sn62 coins bittensor ecosystem bittensor coins layer 1