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Akaash Thawani
Mid-Level Full-Stack Engineer specializing in web apps and LLM integrations
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About
Built a production AI-powered sales automation system that reads inbound product enquiry emails, extracts structured data, and routes decisions via a rules-based workflow integrated with a product database. Leverages Gemini structured outputs/schema plus option-based prompting and validation to keep responses reliable, and optimizes latency by breaking agent reasoning into smaller LLM calls; evaluates workflows with LangSmith and metrics like completion rate and accuracy.
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Key Strengths
- Built and deployed AI-powered sales email automation workflow (extracts info, applies rules, checks products in DB)
- Uses schema/structured outputs plus prompt constraints to improve validity of LLM responses
- Designs modular agent workflows with step-level validation to prevent downstream failures
- Optimizes agent latency by decomposing work into smaller LLM calls instead of one large call
- Reliability-focused testing approach (unit + integration) with measurable metrics (latency, accuracy, completion rate)
- Uses LangSmith metadata to evaluate and debug agent/API/function-call behavior
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