I'm Aditya Nandlal, an AI Agent Developer and multi-product engineer with approximately 10 years in the industry. I turn LLMs into useful systems with tools, MCP, RAG, approvals, automation, confidential product work, and production-grade software.
Five years of independent delivery. Five years in confidential product engineering.
Client ambiguity, product architecture, production constraints, and now agentic execution—the work has always been end to end.
Delivered 40+ private and personal projects across web products, admin systems, API integrations, automation, and business tooling. Owned discovery, architecture, implementation, deployment, and support.
Built and maintained multiple private production systems across React, Next.js, Node.js, Python, data platforms, self-hosted infrastructure, APIs, automation, and AI-assisted workflows. Employer, product, and customer identities are intentionally withheld.
Publishes real, inspectable products spanning coding agents, MCP automation, rendering engines, backend platforms, secure self-hosted applications, and developer infrastructure.
Many employer and client products are protected by confidentiality. Names, links, customer details, and implementation specifics are intentionally omitted; only broad responsibility areas are shared.
Contributed to multiple production products through admin experiences, backend services, APIs, data workflows, integrations, automation, security controls, deployment, and ongoing operations. Product and company identities remain confidential.
Designed and delivered substantial private products across web applications, service layers, and operational tooling.
Built secure admin panels, internal tools, role-aware workflows, dashboards, and day-to-day operational controls.
Implemented APIs, data models, background jobs, third-party integrations, automation, and reliability-focused services.
Worked from discovery and architecture through testing, deployment, maintenance, and continuous product iteration.
No employer or client names, product identities, private source, credentials, customer data, or internal architecture are disclosed.
Seven original public product builds from the GitHub profile—not tutorial clones, but opinionated tools with architecture, security, documentation, and delivery concerns.
A private-beta coding-agent foundation with a React workspace, Tauri/Rust safety layer, local Codex runtime, private LLM gateway, patch previews, and approval-gated actions. Some execution and installer paths remain in beta development.
A Python bridge and MCP server that lets coding agents control Blender through structured tools for scenes, assets, transforms, rendering, and export.
A low-level TypeScript 2D engine with explicit Canvas/WebGL pipelines and raw2d-mcp tooling for scene validation, generation, and agent automation.
A TypeScript headless CMS and API platform with multi-tenant isolation, workflow APIs, route permissions, automation tokens, and documented MCP contracts.
A self-hosted database access manager for PostgreSQL and MySQL with isolated adapters, restricted accounts, live catalog inspection, and a guarded SQL workspace.
White-label webmail built with strict TypeScript and provider adapters for JMAP and IMAP/SMTP, including protected setup, 2FA, hardened sessions, and Docker delivery.
An open-source Payload and Next.js server control plane for audited port operations over SSH.
The agent is only one layer. Reliable outcomes need contracts, state, permissions, observability, data, interfaces, and deployment.
AN / BESTMAA“Understand the system. Design the foundation. Ship the product. Verify the reality.”
Modular architecture, readable internals, practical automation, and products that can survive outside a demo.
Build · Play · Ship · RepeatLet's talk about agent workflows, MCP integrations, RAG systems, developer tools, or product infrastructure.