AI-Augmented Product Engineer
Shashank
Shekhar.
I build AI-assisted workflows that turn product goals into validated implementation steps.
I am a product engineer with 8+ years across Angular, React, FastAPI, search systems, and AI-assisted workflows. Today I build practical systems that connect product delivery, validation, and infrastructure.
01
Understand
Knowledge Hub
Tree-sitter parses every repository into a structural knowledge graph — classes, APIs, schemas, dependencies. Agents navigate architecture, not text chunks.
Read the case study →// Indexing changed sources...
→ Scanned 18 modules (Python, TypeScript)
✓ Exported OKF schema graph map
✓ Synchronized 42 vector embeddings
02
Plan
BuildOS Agent
Feature requests become stateful planning queues. Specialized agents — database, API, UI — execute sequentially with deterministic context and a circuit breaker watching every loop.
Read the case study →// Initiating planner execution...
✓ Loaded repository structure in 12ms
✓ Compiled AST schema (Tree-sitter)
→ Spawning Database Agent for migrations
03
Execute
Node Commander
Agentless SSH control of the whole Docker fleet. Deployments, live metrics, browser terminals, and near-zero-downtime migrations — no daemons installed anywhere.
Read the case study →$ node-commander status --fleet
● node-01 [SSH connected] - 18 containers
● node-02 [SSH connected] - 12 containers
→ Syncing volumes for migration... 72%
The loop
Build. Execute. Diagnose. Modify.
Build
Agents generate real applications against structural context, not guesses.
Execute
Code runs on actual infrastructure over SSH — sandboxed, streamed, observed.
Diagnose
Failures are read, not ignored: logs, states, and exit codes feed back in.
Modify
Fixes ship in a closed loop, with validation gates and human review where it matters.
Your product could feel like this.
This page and the minimal site carry the same information — two experiences, one engineer. Whether your product needs quiet clarity or cinematic polish, I build both.