jnPiyush

Rewrite working code into its minimal, elegant form -- lower cyclomatic complexity, fewer lines, no dead code, no needless abstractions -- using a Draft -> Optimize -> Verify loop. Use when asked to compress, minimize, simplify, or make code more elegant WITHOUT sacrificing correctness, boundary validation, or readability.

Scan recent changes for AI-generated slop -- redundant comments, over-abstraction, generic UI defaults, and design tells -- and optionally apply safe automated fixes. Use after a code-generation or refactor pass to remove the visible signs of machine authorship before review.

Produce production-grade Product Requirements Documents (PRDs) that bridge business vision and technical execution. Use when writing, reading, reviewing, or extending a PRD -- by Product Manager agents authoring one, or by Architect/UX/Engineer/Agent-X agents that need to consume or fact-check PRD conventions without loading the full PM agent contract.

Fan out independent work to multiple subagents with context isolation. Covers when to parallelize (independent reads, multi-file searches, parallel analysis), when not to (writes, dependent steps, shared mutable state), bounded concurrency limits, and the anti-patterns that turn parallel dispatch into corruption. Use whenever the active agent is tempted to run more than one subagent at the same time.

Build production-ready AI agents with Microsoft Foundry and Agent Framework. Use when creating AI agents, selecting LLM models, implementing agent orchestration, adding tracing/observability, or evaluating agent quality. Covers agent architecture, model selection, multi-agent workflows, and production deployment.

Implement production applications with Anthropic Claude models -- Messages API, tool use, prompt caching, extended thinking, vision, computer use, and the Claude Agent SDK. Use when coding directly against Anthropic APIs, Claude via AWS Bedrock, or Claude via GCP Vertex AI rather than a higher-level framework.

Use reasoning / thinking models (OpenAI o-series, Anthropic extended thinking, DeepSeek R1, Gemini Thinking) effectively. Covers when to choose reasoning vs fast models, prompt patterns for reasoners, reasoning_effort / thinking budget controls, structured outputs with reasoning, cost/latency trade-offs, and combining reasoners with fast models.

Design robust tool-use and function-calling for LLM agents. Use when defining tool schemas (JSON Schema, OpenAPI), enabling parallel tool calls, structured outputs (JSON mode / response_format), tool error handling, retries, idempotency, and tool selection prompts. Covers OpenAI tools, Anthropic tool_use, Gemini function calling, and MCP tools.

Build production-ready AI agents with Microsoft Foundry and Agent Framework. Covers agent architecture, model selection, orchestration, tracing, and evaluation.

Design robust REST APIs with proper versioning, pagination, error handling, rate limiting, and OpenAPI documentation.

Structure projects for maintainability and scalability with clean architecture, separation of concerns, and consistent project layouts.

Systematic code review and audit practices including automated checks, security audits, compliance verification, and review checklists.

Manage application configuration with environment variables, Azure Key Vault, feature flags, and environment-specific settings.

Fundamental coding principles for production development including SOLID, DRY, KISS, and common design patterns with C# examples.

Efficient database operations with PostgreSQL, Entity Framework Core, migrations, indexing strategies, transactions, and connection pooling.

Manage project dependencies securely with lock files, version pinning, security audits, and update strategies for NuGet, npm, and pip.