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Shreeya Dhakal spends her days evaluating Docusign's AI agents, and her nights building NLP tools for Nepali, her native language and a low-resource one she's worked to bring into the computational world since college. In this installment of Meet the Engineer, the Applied Scientist talks about debugging an AI agent that gave different answers to the same question, and what "good enough to ship" actually means in a multi-tool agentic system. She also explains how building tools for her own language taught her to notice when a system is quietly failing, long before the aggregate metrics would show it.

Trust is the central challenge facing government agencies as they adopt agentic AI—and it must be built the same way agencies have always governed people: through clearly delegated authority and verifiable records. Because AI policies describe intent but don't prove what happened, agencies need centralized, structured agreement data.

A contract is a legally enforceable agreement requiring offer, acceptance, consideration, awareness, capacity, and legality, and it may be either unilateral, bilateral, written, or verbal.

Contract breaches build slowly, through unclear terms, missed deadlines, or undocumented changes, not bad faith. Clear drafting, consistent documentation, obligation tracking, and contract management software close those gaps before they become breaches.

The Docusign IAM platform offers financial services organizations tools like multi-factor authentication and identity verification to help comply with New York State's updated Title 23 NYCRR Part 500 cybersecurity regulation requiring enhanced security measures.

AI-powered agreement technology is transforming commercial legal workflows by automating contract reviews, resolving routine inquiries, and streamlining post-signature obligation management. By using AI to handle low-stakes tasks, in-house legal teams can focus on complex strategic decision-making while mitigating operational risks.