Shashank ShekharAI-Augmented
Product Engineer
I build AI-assisted products, search-heavy interfaces, and full-stack systems that move from prototype to production without losing engineering discipline.
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How I Help Teams
Practical engineering support for teams building AI-assisted products, search-heavy interfaces, and maintainable full-stack platforms.
AI-Augmented Product Engineering
I help teams design and ship AI-assisted product workflows with clear architecture, approval boundaries, validation, and production safeguards.
- Agent workflow design with human review gates
- Structured LLM outputs and validation paths
- Prototype-to-production implementation plan
Frontend Architecture
Scalable Angular, React and Next.js interfaces for complex products, with reusable components, schema-driven screens, and maintainable state boundaries.
- Component and design-system architecture
- Performance and maintainability review
- Frontend delivery plan for product teams
Search & Catalogue Systems
Product discovery and data-heavy interfaces built around faceted search, taxonomies, schema-driven UI and low-latency user experience.
- Typesense-backed faceted search UI
- Catalogue taxonomy and schema modelling
- Search UX and relevance improvement plan
MVP to Production Delivery
End-to-end product delivery across frontend, API, database, deployment and handover, focused on working systems rather than throwaway prototypes.
- Next.js / FastAPI implementation
- Dockerized deployment and handover docs
- Testing, observability and operational checklist
Currently Building
Evolving local tooling into a cohesive cloud environment.
AI engineering workspace for repository planning, parsing, and multi-agent coordination.
Agentless SSH fleet management dashboard for Docker deployments and zero-downtime migrations.
AST tree-sitter based schema parser compiling directories into structured repository memory maps.
Open-source cross-framework design tokens and core accessible web components.
Featured Products
Full-scale platforms demonstrating visual and engineering depth.
BuildOS Agent
AI-native development workspace for project planning, knowledge management, architecture generation, AI-assisted coding, documentation, and execution.
The Problem
Modern AI coding tools lose project context, duplicate decisions, and struggle with long-running multi-repository software projects.
The Solution
Designed a persistent engineering workspace where project architecture, decisions, docs, implementation status, prompts, and AI conversations become reusable project memory.
Highlights
- ✔ High-relevance, AST-based dynamic prompts
- ✔ Stateful multi-agent planning queues
- ✔ Reusable, file-integrated project context
Tech Stack
BuildOS Full Platform
Full agentic AI platform tying together a Next.js dashboard, FastAPI backend, vector-search knowledge layer, and a Node.js runtime for orchestrating agent-driven infrastructure tasks.
The Problem
Running AI agents against real infrastructure needs more than a chat window — it needs a real backend, persistent state, vector search over knowledge, and a runtime that can safely execute and report back on agent actions.
The Solution
Built a production platform: a Next.js dashboard, a FastAPI + SQLAlchemy2 API layer backed by Postgres with pgvector for semantic search, Redis for queuing/caching, and a dedicated Node.js runtime service that executes agent-issued operations over WebSockets.
Highlights
- ✔ FastAPI + SQLAlchemy2 API layer with async Postgres/pgvector
- ✔ Dedicated Node.js runtime service for executing agent operations
- ✔ Redis-backed queuing and caching between services
- ✔ Full Docker Compose deployment, self-hosted
Tech Stack
BuildOS Knowledge Hub
Knowledge management layer that indexes repositories, docs, architecture notes, prompts, and API specs into structured OKF engineering knowledge for AI agents.
The Problem
Engineering knowledge is scattered across repositories, READMEs, docs, prompts, API specs, and architecture notes, forcing developers to repeatedly rebuild context.
The Solution
Created a structured project memory layer that extracts applications, modules, APIs, services, schemas, dependencies, decisions, and deployment workflows for AI retrieval.
Highlights
- ✔ Tree-sitter code layout parsing
- ✔ Unified repository dependency graph
- ✔ Semantic and relationship hybrid search
Tech Stack
BuildOS Node Commander
AI-powered infrastructure management platform for self-hosted servers and cloud machines with fleet visibility, Docker operations, remote execution, and migration workflows.
The Problem
Managing multiple Linux servers requires switching between SSH, Docker CLI, Portainer, terminal sessions, and monitoring tools.
The Solution
Built a unified infrastructure workspace for server discovery, Docker inspection, deployments, health monitoring, remote commands, and near-zero downtime Docker migrations.
Highlights
- ✔ 100% agentless server command streaming
- ✔ Safe volume migrations across remote nodes
- ✔ Browser-integrated terminal shell access
Tech Stack
Engineering Philosophy
Core ideas that drive my building process.
Architecture First
Every product starts with clear system boundaries. I define data streams, API contracts, and constraints before touching the keyboard.
AI is a Tool
AI generates functional boilerplate code quickly. Humans must own the architectural decisions, verification, and code quality controls.
Automation by Default
Anything repetitive should eventually disappear. I write automation scripts, templates, and triggers to clear away operational overhead.
Production > Prototype
A prototype that doesn't ship holds zero value. Shipping reliably, early, and observing telemetry in production defines real success.
Self-Hosted Infrastructure
Centralized control and container routing across my private network.
AI Processing Stack
Visualizing the orchestration pipelines that power my AI tools.
Engineering Case Studies
Additional project breakdowns detailing deep system integration.
AI-Integrated Automation Services
Automation services for PDF/text extraction into structured JSON with validation, deterministic post-processing, and fallback paths.
AI-Powered Workflow Builder Platform
Visual workflow builder with NL-to-graph generation, versioning, and separation between definition and execution layers.
Data Transformation Adapter
In-progress adapter to transform CSV/JSON into structured templates with export to JSON or CSV.
High-Scale Product Discovery Platform
Enterprise-scale product discovery platform for 7.7M+ SKUs with schema-driven UI, faceted search, and bulk editorial workflows.
Technical Expertise
Structured stacks representing my core competencies.
Frontend
- Angular
- React / Next.js
- TypeScript
- Tailwind CSS
- Design Tokens
Backend
- FastAPI (Python)
- Node.js (TypeScript)
- PostgreSQL
- Redis
- Typesense Search
Infrastructure
- Docker / Docker Compose
- Proxmox VE
- Cloudflare Tunnels
- Linux Node Ops
- CI/CD Workflows
AI Stack
- Agentic Development (build → run → diagnose → fix)
- AI Agents (LangChain, Custom)
- Tool Calling Architectures
- Structured Outputs
- Context Engineering (AST RAG)
Latest Articles
Technical deep-dives published on my engineering blog.
How I Built a Self-Hosted AI Operations Dashboard on a $16 VPS
A practical blueprint for turning a small Hetzner box into a reliable operations dashboard with health checks, auth, history, and alerting — the exact stack I would ship again.
From Git Commit to LinkedIn Post: A Repeatable Content Workflow for Engineers
A simple system for turning shipped work into SEO-friendly blog posts, LinkedIn-ready summaries, and portfolio updates without sounding generic.
Why BuildOS Uses Agent Loops Instead of One-Off Prompts
The engineering case for persistent agent execution: planning, verification, recovery, and human approval gates inside a real product workflow.
Building BuildOS: Reimagining the AI Agent Execution Loop
How we implemented event-driven microservice orchestration and Paramiko SSH streaming to execute code safely across private fleets.
Why AST-Parsing Trumps Raw Vector Embeddings for Code RAG
An in-depth look at using Tree-sitter AST queries to build deterministic model context maps rather than relying purely on semantic vector chunking.
Zero-Downtime Docker Compose Migrations via Secure Relays
Solving remote volume migration issues without direct host-to-host SSH trust configurations.
Experience Timeline
Chronological record of system ownership and delivery.
Designed and released BuildOS Node Commander agentless infrastructure tool. Integrated Tree-sitter code indexes and multi-agent systems to orchestrate container configurations.
Authored visual workflow editor platforms utilizing NL-to-graph translation pipelines. Built automated microservices backed by FastAPI and PostgreSQL.
Scaled enterprise catalog systems for CrowdAnalytix indexing over 7.7M+ SKUs. Tuned search results, relevance boosting, and facets with Typesense clusters.
Constructed category classification trees and governed attribute dashboards. Interfaced layout boundaries using reusable component layers.
Ready for the right engineering challenge?
I am strongest in remote teams building AI-assisted products, internal tools, search-heavy platforms, or workflow automation systems.