Announcing MCP Toolbox Java SDK v1.0: Agentic data access for the enterprise
cloud.google.com·6d ago
Cloud & Infrastructure
The New Stack·Jul 22·5 min read
Agents keep changing their answers. Harness just built delivery pipelines that don’t care.
TL;DR
Harness has launched its AI Agent Development Lifecycle (DLC) service, enabling developers to deploy AI agents with the same governance and security as traditional application code. This innovation aims to streamline the deployment process for AI agents, which currently face significant adoption barriers.
✦ Why It Matters
Evaluate your current deployment processes to incorporate AI agents using Harness's new DLC service.
Key Takeaways
- Implement Harness's AI Agent DLC for better governance.
- Use AI Evals to measure agent quality effectively.
- Leverage AgentTrace for detailed tracking of agent performance.
- Adopt predictable pipelines to manage non-deterministic AI outputs.
How It Works
Harness's AI Agent DLC service integrates traditional software delivery practices with AI agent management. It establishes quality gates that evaluate agent responses based on predefined criteria, ensuring that only agents meeting safety and performance standards are deployed.
Tools like AI Evals allow teams to define datasets and scoring functions, while AgentTrace records every action taken by an agent, providing insights for continuous improvement.