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DEV270201/README.md

→ what I'm building right now

Blogging Agent: an AI agent that turns a topic into a fully-cited article, built like a product instead of a demo.

queries → research (Tavily) → plan + coverage score → [pause if evidence is weak] → parallel write → synthesize
  • Doesn't hallucinate confidence. The planner scores evidence as sufficient | partial | insufficient and pauses the graph for a human decision, proceed or re-research, before a single word gets drafted. Bounded at 2 rounds, so it can't loop forever.
  • Doesn't lose work on crash. Every node checkpoints to Postgres. A heartbeat thread renews a lease per running job; a sweeper reclaims anything whose owner died, safe across multiple instances.
  • Doesn't ship untested. 162 tests gating merges via GitHub Actions + branch protection. Deploys to ECR through GitHub OIDC, no long-lived AWS keys anywhere in the pipeline.

Expense Tracker Agent: a local LLM agent, built from scratch, no framework scaffolding.

  • Function-calling loop on a local model. Runs on Ollama, with system prompts designed to drive the model to select and invoke tools for logging and summarizing expenses, no cloud API in the loop.
  • Remembers you across sessions. A secondary LLM extracts user preferences at session end and persists them, so the next session's system prompt already knows how you like things done.
  • Structured output over regex. Replaced regex-based response parsing with prompt-enforced JSON schemas, eliminating an entire class of parsing failures caused by the model phrasing things slightly differently each time.

→ previously worked upon

RBAC at scale Designed cohort-based access control serving 1,000+ users: schema, backend logic, admin controls, from scratch
Zero-downtime auth fix Root-caused a distributed auth bug leaving users with half-created accounts; related support tickets went to zero
RAG under load Built a concurrent ingestion pipeline (Node.js, Bedrock) with retries and structured logging, designed to fail loud, not silent
Serverless on a budget Lambda + DynamoDB with 3 GSIs purpose-built to kill full table scans
File infra end-to-end EasyFiles: full-stack app on EC2 behind NGINX, S3 for storage, async deletes via Lambda routed to an SQS dead-letter queue after 3 retries; cut download TTFB 18% by fronting S3 with CloudFront

→ sharing-knowledge

Docker, from first principles — 5-part series
1 · Why Docker The dependency-hell problem it actually solves: pulling pre-built images instead of installing and configuring every dependency on every machine
2 · Containers vs. VMs Why containers share the host kernel instead of shipping a full OS, and why that makes them lighter and faster than VMs
3 · Images, networks, volumes Image vs. container, bridge vs. host networking, and why anonymous volumes silently lose data on container recreation
4 · The commands you actually use ps / pull / push / run / exec / build, including pulling from a private registry like AWS ECR, not just Docker Hub
5 · Docker Compose Replacing "start 10 containers by hand" with one YAML file and docker compose up
Jenkins + Docker: building and breaking a real pipeline
1 · Why Docker agents over plugin sprawl Letting Jenkins orchestrate through plugins while Docker handles build execution in disposable containers: no more Node/Python/Go version conflicts on the controller
2 · Four errors deep in the Jenkins–Docker handshake docker: not found (missing CLI in the Jenkins image), permission denied on docker.sock (group membership), API version mismatch (host/CLI version skew), files "disappearing" (fixed with reuseNode true for workspace mounting)
3 · Full CI/CD pipeline, GitHub push to running container Webhook triggers a build in a disposable AWS CLI container, pushes to ECR, then SSHs into EC2 to swap the container. Multi-stage builds to shrink image size, an NGINX try_files fix for React routing 404s, heredocs to fix commands silently running on the wrong host. Manual 3-5 min deploy cut to under 1 minute, automated
Bash scripting for automation
Learning Bash by writing real scripts Wrote scripts from scratch: a Postgres container lifecycle manager, a CloudFront TTFB benchmarking tool, a disk/memory monitor, and a safe file-migration script, while working through stdout/stderr redirection and multi-line file handling

→ stack I actually use

languages / core

backend / frontend

AI / agents

databases

cloud / infra

day-to-day tools

currently deepening: distributed job orchestration, LLM-as-judge evaluation loops, infra-as-code


→ education

M.S. Computer Science Stevens Institute of Technology, United States Aug 2023 - May 2025
B.Tech. Computer Science KJ Somaiya College of Engineering, Mumbai University Aug 2019 - May 2023

→ let's talk

LinkedIn · Mail · Blogging Agent

if it's in a repo, it has tests. if it's in prod, it has a rollback plan

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