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Motorola Solutions Engineer Discusses Agentic SDLC Pipelines and LLM Evaluation
Key points
- Building agentic SDLC pipelines with MCPs.
- Evaluating LLMs as judges using Cohen's kappa.
- Improving requirements by shifting QA left.
- Specification enrichment stage after design phase.
Agentic SDLC Pipelines
Suneet Malhotra, Senior Manager of Test Engineering at Motorola Solutions, discussed the implementation of end-to-end agentic SDLC pipelines. These pipelines utilize MCPs (Multi-Agent Communication Protocols) to automate and integrate various stages of the software development lifecycle.
LLM Evaluation with Cohen's Kappa
A key aspect of the discussion involved the evaluation of multiple Large Language Models (LLMs) acting as judges. Malhotra detailed the use of Cohen's kappa, a statistical measure, to assess the agreement between these LLMs, ensuring reliability in automated judgment processes.
Shifting QA Left for Improved Requirements
The conversation also focused on strategies to enhance software requirements by integrating quality assurance earlier in the development process. This 'shifting QA left' approach involves a specification enrichment stage immediately following the design phase.
Companion Code Available
Further details on Malhotra's five-agent SDLC and accompanying code are available on his GitHub, providing practical examples and resources for those interested in implementing similar agentic systems.
✨ This summary was generated by AI from the outlets' reporting listed below. It is not independently verified and may contain errors — check the original sources. How BrevFeed works →
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Reporting from
Suneet Malhotra of Motorola Solutions discussed building end-to-end agentic SDLC pipelines using MCPs and evaluating multiple LLMs as judges with Cohen's kappa. The discussion also covered improving requirements by shifting QA left through a specification enrichment stage after the design phase.