PERSONAL ARCHIVE ONLINE

INITIALIZING SIGNAL

Thinking,Building & Engineering..HARSH BHARDWAJ

Architecting intelligent systems across the stack. From foundational models to deployed applications, building artifacts that prove capability.

03 / Worklog

Mission log, latest first.

Apr 2026 - Jul 2026

Contract Software Engineer

ClipHawk

Built ClipHawk as a contract-ready AI/data automation system designed to orchestrate agents, audit metadata, and scale high-volume entity processing.

  • Engineered a distributed orchestration server using Node.js and TypeScript to coordinate AI agents across worker nodes.
  • Scaled an event-driven data pipeline capable of processing 5,000+ complex entities daily without ingestion bottlenecks.
  • Integrated OpenAI and Anthropic APIs into production metadata-auditing layers, reducing manual review time per entity by 73%.
  • Implemented robust message queues for concurrent ingestion, reliability, and worker-level fault tolerance.
Node.jsTypeScriptAI AgentsOpenAIAnthropicMessage Queues

// CODE ARCHIVE

Repository Atlas.

A monochrome proof map of the codebase: learning trails, small tools, ML experiments, archived context, and the projects worth inspecting.

Proof-of-Work Vault3 selected builds / click to inspect
Repository Atlas17 repos indexed
ML Labsmodels / signalsLearning Repospublic trailTiny Buildssmall toolsArchivescontext onlyFull-Stack Systemscurated proof
Contribution Frequencymapping activity
LessMore
Recent commitsactivity timeline
7b9c3f1Created 1 commit in LearnOSlearnOSautomation trail
d4e1f8aCreated 10 commits across 4 reposNameFrame / WarWithin / ML101product + learning
3c9a2b1Created 3 repositoriesWarWithin / ML101 / Personalnew build cycle
f1e7d9cOrganized repo proof bucketsportfolio maparchive work
9b2d6e4Pushed screening and automation artifactsClipHawk-ScreenerML/data proof
07

Written Records

Field Notes

Systems, experiments, and the lessons left behind after the build.

01 / Field Note

How not to make Machine's Learn

A practical map of the places machine-learning systems break: data, sampling, features, evaluation, and assumptions.

May 29, 2026 4 reactions
Read dispatch

02 / Field Note

What the heck is IAM in AWS

A direct introduction to securing an AWS sandbox with identities, permissions, and deliberate access boundaries.

Aug 12, 2025 2 reactions
Read dispatch

03 / Field Note

Keep Your DB Awake with Hibernot

The build story behind a small automation that prevents free-tier databases from quietly hibernating.

May 25, 2025 7 reactions
Read dispatch
See all field notes

08 / Project Hitlist

Things I am trying to bring to life.

Ordered by what I want to attack next. Hover a project sigil to let its world surface without turning the page into another card grid.

10 / About Me

Who am I ?

I'm Harsh Bhardwaj, an engineer from Delhi building full-stack systems, ML experiments, automation workflows, and public proof trails. I learn by turning ideas into visible artifacts: repos, notes, dashboards, notebooks, field records, and working tools that can be inspected.

01Observe02Build03Measure04Archive
Education

Maharaja Agrasen Institute of Technology

B.Tech CSE, 2023 - 2027 / CGPA 8.95 / ML & Data Analytics.

Study track

SIC Course in Data Analysis

Coursework focused on analysis concepts, structured data thinking, and practical interpretation.

Operating style

Useful systems over decorative builds

I prefer projects that leave proof behind: code, notes, metrics, automations, and decisions someone can inspect.