Ishan Singh on Muck Rack

Ishan Singh

Singapore
As seen in: Amazon Web Services, Medium, MSN Singapore, South China Morning Post, Flipboard, DEV Community, Towards Data Science, HubPages, Inc42, Vulcan Post and
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Articles

Evaluate AI agents systematically with Agent-EvalKit

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By Ishan Singh, Haibo Ding, Kang Zhou
| Amazon Web Services
Teams building AI agents typically evaluate them the way they evaluate any other software: by checking whether the output matches expectations. But agents that autonomously choose tools and sequence operations across multiple sources produce behavior that output-level testing cannot fully characterize. An agent might deliver a well-structured, actionable response while hallucinating, fabricating facts because its tools returned empty results.
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Simulate realistic users to evaluate multi-turn AI agents in Strands Evals

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By Ishan Singh, Abhishek Kumar, Jonathan Buck
| Amazon Web Services
Evaluating single-turn agent interactions follows a pattern that most teams understand well. You provide an input, collect the output, and judge the result. Frameworks like Strands Evaluation SDK make this process systematic through evaluators that assess helpfulness, faithfulness, and tool usage. In a previous blog post, we covered how to build comprehensive evaluation suites for AI agents using these capabilities. However, production conversations rarely stop at one turn.
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Lead Generation in Digital Marketing Mastery Guide

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By Ishan Singh
| WriteUp Cafe
In the current digital landscape, visibility alone does not guarantee business growth. While attracting website traffic is important, the real value lies in identifying users who show genuine interest and guiding them toward meaningful engagement. This is precisely where lead generation in digital marketing becomes essential. It enables businesses to transform casual visitors into potential customers through a structured and measurable approach.
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