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  • 09:09 (UTC -07:00)
  • X @zalenix

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Typing SVG

Software Engineer · AI Agent Tooling & Security

LinkedIn Email WinSentinel


I build tooling for AI agents — the layer that makes autonomous systems observable, testable, and reliable — plus an always-on Windows security agent. Two focused areas, no side quests.


🤖 The Agent Stack

A focused toolchain for building and operating AI agents: write patterns → gate outputs → observe runs.

Project What it does Stack
agent-eval Zero-dependency toolkit for evaluating AI agent outputs — an eval framework (hallucination, drift, staleness, contradiction checks), fleet monitoring, and a CI quality gate that blocks on empty/stale/off-task output. (gate the outputs) TypeScript
AgentLens Observability & explainability for AI agents — trace how an agent reached its answer: capture every model + tool step, debug, and understand behavior. SDK + collector + dashboard. (observe the runs) TypeScript
prompt Prompt engineering toolkit — template engine, prompt chaining, injection detection, and bias checks. (write the patterns) C# / .NET
agentic-recipes Canonical agentic pipeline patterns — summarization chains, tool-agent ReAct loops, RAG, plan-and-execute, self-consistency, multi-agent debate, reflexion, tree-of-thoughts. (compose the patterns) C# / .NET

🛡️ WinSentinel

Project What it does Live
WinSentinel Always-on Windows security agent — real-time monitoring, AI-powered correlation, auto-remediation, and audit modules with compliance profiles. winsentinel.ai
WinSentinel Pro Pro tier — license server, fleet management, and advanced modules for organizations. Site

🛠️ Tech

TypeScript Node.js C# .NET Python Azure Docker



Building tools that make intelligent systems observable, accountable, and reliable.

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  1. WinSentinel WinSentinel Public

    Always-on Windows security agent with real-time monitoring, AI-powered threat detection, auto-remediation, and 13 audit modules

    C# 8 2

  2. agentlens agentlens Public

    AgentLens — Observability and Explainability for AI Agents

    JavaScript 2 1

  3. agent-eval agent-eval Public

    Lightweight TypeScript framework for testing and evaluating AI agent outputs — prompt chain testing, hallucination detection, drift monitoring, and pass/fail assertions for agentic workflows

    TypeScript 2

  4. agentic-recipes agentic-recipes Public

    Canonical agentic pipeline examples built on prompt-lib — linear chains, fan-out/fan-in, middleware pipelines

    C# 2