Software engineer · AI agent tooling (trace, eval, gate outputs) · Building WinSentinel for Windows security
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Microsoft
iOS Developer
June 22, 2026 – Present
agentic-recipes
June 7, 2026 – Present
Canonical agentic pipeline examples built on prompt-lib — linear chains, fan-out/fan-in, middleware pipelines
View Projectagent-eval
June 5, 2026 – Present
Lightweight TypeScript framework for testing and evaluating AI agent outputs — prompt chain testing, hallucination detection, drift monitoring, and pass/fail assertions for agentic workflows
View Projectmetacognition
April 26, 2026 – Present
mBFT: Metacognitive Byzantine Fault Tolerance — reference implementation for Consensus-Driven Metacognition in Multi-Agent Systems
View ProjectWinSentinel
February 16, 2026 – Present
Always-on Windows security agent with real-time monitoring, AI-powered threat detection, auto-remediation, and 13 audit modules
View Projectagentlens
February 14, 2026 – Present
AgentLens — Observability and Explainability for AI Agents
View Projectagenticchat
July 24, 2025 – Present
Turn natural language into executable code — right in your browser. Lightweight AI chat powered by GPT-4o with sandboxed JavaScript execution.
View Projectsauravcode
November 10, 2024 – Present
Frustrated by syntax-heavy languages, I designed *sauravcode* for simplicity and clarity. It removes unnecessary punctuation and rigid conventions, focusing purely on logic. With minimal syntax, it allows ideas to flow naturally without distraction. *Sauravcode* is my tool for coding as a seamless, intuitive process, free from constraints.
View ProjectVoronoiMap
September 19, 2016 – Present
Voronoi partitioning of a geometric 2 dimensional space.
View ProjectFeedReader
September 16, 2016 – Present
Intelligent RSS reader for iOS — AI-powered feed analysis, knowledge graphs, sentiment radar, trend forecasting, narrative tracking, and autonomous reading with 330+ Swift modules
View ProjectOcaml-sample-code
January 23, 2015 – Present
214 OCaml implementations: data structures, algorithms, interpreters, theorem provers, neural networks, distributed systems, cryptography, formal methods, and more
View ProjectCultural Fit Analysis
The candidate's project portfolio is highly diverse, showcasing a broad range of interests from low-level systems (C++, OCaml) to AI and web technologies. While this demonstrates versatility, the sheer breadth and lack of focus on a specific domain might indicate a preference for exploration over deep specialization, which could impact cultural fit depending on the team's needs for focused iOS expertise. The 'FeedReader' project is a strong indicator of interest in iOS development.
Soft Skills & Operational Fit
The provided data does not contain sufficient information to assess soft skills or operational fit. Project descriptions suggest a strong independent drive and technical curiosity.