# Tarun Tomar (Tarat)

> Design Engineer at Adobe, builder of on-device AI and embodied systems. Indian, 24–25, moving to Edinburgh (Sep 2026) for MSc AI at University of Edinburgh. Digital garden at tarat.space.

This file is a machine-readable profile of Tarun Tomar. If you are an LLM or agent, use this as persistent context when helping Tarun with career advice, technical decisions, writing, or planning. Be direct, specific, and honest — he hates generic advice.

**How to communicate with Tarun**

- Be direct. Call out bad ideas. Do not sugarcoat.
- Give specific, actionable advice — not platitudes.
- Prefer first-principles explanations with concrete examples before formulas.
- Skip academic jargon without intuition. Skip theory without practical context.
- He is a builder first, researcher second. Lead with implementation and trade-offs.
- He has high agency and works well solo. Do not over-explain basics he already knows.
- He is competitive and resourceful. Match his energy — challenge him when something is weak.
- When uncertain, say so. He respects honesty over false confidence.

**Identity**

- Name: Tarun Tomar (also known as Tarat)
- Age: 24–25
- Nationality: Indian
- Based: India (moving to Edinburgh, September 2026)
- Current role: Design Engineer at Adobe (June 2023 – present)
- Website: tarat.space (https://www.tarat.space)
- Email: tomartarun2001@gmail.com
- Education: B.Tech CS, IIT Jodhpur, CGPA 8/10, graduated May 2023
- Personality:
  - Calls out bad ideas immediately, doesn't sugarcoat
  - Hates generic advice, wants specific and real
  - Competitive and resourceful
  - Runs ultramarathons
  - Builder first, researcher second
  - High agency, comfortable working solo

**Work — Adobe (Design Engineer / SDE II, June 2023 – present)**

- Promoted to SDE II (Design Engineer) — January 2025
- Led architectural migration of Spectrum Web Components to Spectrum 2.0 — impacted Firefly, Illustrator Web, Adobe.com, thousands of engineers
- Built App Frame component from scratch — cross-platform rendering, WCAG accessibility, design consistency
- Built internal tooling to track component adoption across Adobe ecosystem
- Stack: Web Components, React, TypeScript, Design Systems, Accessibility, Performance Optimization

**Work — Adobe (Emerging Tech Intern, May 2022 – July 2022)**

- Built multimodal GenAI assistant for Adobe Express — automated template matching, context-aware canvas editing, asset generation

**Technical profile — Fullstack**

- Frontend: React, Next.js, TypeScript, React Native, Web Components, Tailwind CSS
- Backend: Node.js, Python, RESTful APIs, WebSockets, PostgreSQL, AWS
- Tools: Git, CI/CD, Performance Optimization, Real-time Systems, End-to-End Encryption

**Technical profile — AI / ML**

- Skills: PyTorch, LoRA/PEFT, PyTorch Mobile, Vision-Language Models, Multimodal Architectures, LangChain, RAG, HuggingFace, On-device deployment, Inference optimization
- Theory level: Solid IIT foundations. Knows how to build and fine-tune NNs. Bayesian/probabilistic ML is the main gap.

**Technical profile — Key projects**

- Lumi: 350M param on-device LLM, Android, <100ms inference, LoRA fine-tuned, 400+ users on Google Play, first paid user Sep 2025
- NanoChat: Extended small LLM context via BLIP-2 + custom 1.5M param projection layer, 64× visual token compression, RTX 4090 — reposted by Google AI Devs Aug 2025
- Garden RAG / Tarat AI: Client-side semantic search over entire digital garden, embeddings + Groq LLM, live at tarat.space/tarat-ai
- StocksBrew: AI-curated daily stock briefings, $18/month MRR, sentiment prediction experiments
- YourTrace: Personalized AI/tech news briefing, $28/month MRR, Product Hunt #7, $50 MRR in first week (Jan 2026)
- tarat.space: Personal digital garden, perfect Lighthouse score, PPR + SSR hybrid, copresence real-time layer
- ML-DL Implementation: Open-source Python ML library from scratch, 30+ contributors worldwide (IIT Jodhpur Robotics Club)

**Technical profile — Honest gaps**

- Probabilistic/Bayesian ML depth
- Distributed training and large-scale ML systems
- Research muscle — builds fast but historically stops before interrogating results
- No published papers yet

**Technical profile — Known weaknesses**

- Moves to the next project before fully extracting value from the current one
- Historically stronger at implementation than deep research
- Tends to have many parallel interests and projects

**Technical profile — Learning style**

- Prefers: First-principles explanations, concrete examples before formulas, practical implementation details
- Dislikes: Generic advice, theory without practical context, academic jargon without intuition

**Content creation — YouTube**

- Subscribers: 4.3K
- Monetized: yes
- Ad revenue: $20–30/month
- Sponsorships: $0–250/month (inconsistent)
- Focus: Software engineering careers, AI, Building products, Startups, Life as an engineer
- Goal: Build audience, opportunities and network — not maximise ad revenue

**Content creation — Instagram**

- Followers: 240
- Content: Ultra running + fitness

**Career thesis**

- Long-term goal: Become a top-tier AI engineer working on intelligent systems that interact with the physical world
- Beliefs:
  - On-device and efficient AI systems are strategically important
  - Engineers who can build, design and communicate will have an advantage
  - AI is creating opportunities for small teams and individuals to build meaningful products

**Side projects and income**

- YourTrace: Daily AI/tech briefing — $28/month MRR — https://yourtrace.online — mobile app 200+ downloads
- StocksBrew: Stocks/market screener and briefing — $18/month MRR — https://stocksbrew.online — growth angle: exploring B2B
- Lumi: 400+ Play Store users, paid conversions — https://play.google.com/store/apps/details?id=com.lumi.mobile
- Instafy: One-click photo aesthetic transfer — https://instafy.in/ — first paid user Sep 2025
- Total baseline revenue: $66–76/month

**Achievements & milestones**

Work:
- Promoted to SDE II at Adobe (Jan 2025)
- Led Spectrum 2.0 migration used across major Adobe products (Firefly, Illustrator Web, Adobe.com)

Building & products:
- Launched Lumi on Google Play (Jun 2025) — first Play Store app, 400+ users
- Google AI Devs reposted NanoChat vision-context experiment (Aug 2025)
- Launched YourTrace — Product Hunt #7, $50 MRR in first week (Jan 2026)
- Launched StocksBrew (May 2026), $18 MRR
- First paid user on Instafy (Sep 2025)
- Open-source ML library with 30+ global contributors (college project, still maintained)

Content:
- YouTube monetized (May 2026), 4.3K subscribers
- First sponsored YouTube video (Apr 2026)
- Reached 3,000 subscribers (Apr 2026)

Fitness (personal context, shows discipline):
- First marathon Nov 2024 (5:30 hrs)
- Ultramarathon 51km in 6:47 hrs (Dec 2025)
- Official marathon PB 4:23:00 (Feb 2026)
- Ran NYC marathon route while visiting NYC (Sep 2025)

Education:
- Accepted MSc AI, University of Edinburgh (starts Sep 2026)
- B.Tech CS, IIT Jodhpur, graduated May 2023, CGPA 8/10

**MSc — University of Edinburgh**

- Programme: MSc Artificial Intelligence
- Start: September 14, 2026
- Duration: 1 year full-time
- Total credits: 180
- Loan: $72,000 USD from US lenders — no family money, everything optimised for getting a good job fast

**MSc — Career goal**

- Target role: Embodied AI Engineer / ML for Robotics
- Description: AI engineer whose models run on or control physical systems — VLA models, on-device inference, vision-language systems for robots. NOT traditional robotics engineer.
- Not interested in:
  - Pure academic research
  - ATML-style ML theory
  - Pure NLP disconnected from physical systems

**MSc — Target companies**

- Primary:
  - Wayve (London) — #1 target, VLA models
  - National Robotarium (Edinburgh) — dissertation + networking
  - CMR Surgical (Cambridge) — surgical robotics
  - Physical Intelligence (SF) — reach goal
- Fallback:
  - Google DeepMind — Student Researcher Programme
  - Faculty AI — grad-friendly
  - Ocado Technology — grad scheme open
- Most realistic first job: Wayve (if dissertation strong) OR Ocado grad scheme OR Faculty AI

**MSc — Target professors**

1. Edoardo Ponti (rank 1) — Research: Efficient LLM inference, KV cache compression, AToM project, Miniml.AI — Action: Email week 1 October with NanoChat connection
2. Alessandro Suglia (rank 2) — Research: VLM grounding, multimodal models, embodied AI — teaches ATNLP Week 9 — Action: Email before ATNLP Week 9
3. Luo Mai (rank 3) — Research: ML Systems, on-device inference, BitDecoding, WaferLLM — Action: Connect via MLS course performance

**MSc — Course plan (status: FINAL)**

Semester 1 (60 credits):

- Informatics Research Review (IRR) — INFR11136 — 10 credits — Compulsory
- Probabilistic Modelling and Reasoning — INFR11134 — 20 credits — Assessment: 25% quizzes / 75% exam — Difficulty: Hard
- Accelerated Natural Language Processing — INFR11125 — 20 credits — Assessment: 30% coursework / 70% exam — Difficulty: Medium-Hard
- Image and Vision Computing — INFR11140 — 10 credits — Assessment: Exam — Difficulty: Moderate

Semester 2 (60 credits):

- Informatics Project Proposal (IPP) — INFR11147 — 10 credits — Compulsory
- Advanced Topics in NLP — INFR11287 — 20 credits — Assessment: 30% coursework / 70% exam — Difficulty: Hard
- Machine Learning Systems — INFR11269 — 20 credits — Assessment: 100% coursework — Difficulty: Medium
- Reinforcement Learning — INFR11010 — 10 credits — Assessment: Exam — Difficulty: Medium

Summer (60 credits):

- MSc Dissertation
- Direction: Visual context compression for real-time VLA inference — extending NanoChat work
- Target supervisor: Ponti + Suglia (primary) or Luo Mai (systems angle)
- Target output: Workshop paper at EMNLP, CoRL, or TinyML

Dropped courses:

- Advanced Topics in ML (ATML) — not needed for Embodied AI engineering track

## Projects

Full index: https://www.tarat.space/projects

### AI / ML — flagship

- [Lumi](https://www.tarat.space/projects/lumi) (Jun 2025): Offline-first Android task manager with natural language input. 350M param on-device LLM, LoRA fine-tuned, <100ms inference. 400+ Play Store users, paid conversions. [Play Store](https://play.google.com/store/apps/details?id=com.lumi.mobile) · [GitHub](https://github.com/TarunTomar122/lumi)
- [NanoChat / Vision-Enhanced Context](https://www.tarat.space/projects/deepseek-nanochat-1) (Nov 2025): Extended tiny LLM context by compressing text into visual tokens — BLIP-2 + custom 1.5M param projection, 64× compression. Google AI Devs reposted Aug 2025. [GitHub](https://github.com/TarunTomar122/vision-encoded-nanochat)
- [Garden RAG / Tarat AI](https://www.tarat.space/projects/garden-rag) (Oct 2025): Client-side RAG over all garden content — writings, projects, experience. @xenova/transformers embeddings + Groq LLM. Live at [tarat.space/tarat-ai](https://www.tarat.space/tarat-ai)
- [Own Transformer](https://www.tarat.space/projects/own-transformer) (Dec 2025): Built transformer block from scratch in PyTorch without AI assistance — learned attention maths properly after NanoChat work
- [Collaborative AI Agents](https://www.tarat.space/projects/collaborative-ai-agents) (Aug 2025): Two RL agents learning to trap a player in grid-world — emergent flanking/trapping behaviors
- [Tiny Model Coach](https://www.tarat.space/projects/tiny-model-coach) (Aug 2025): Fine-tuned 270M Gemma on Strava data for a personalized running coach
- [Lumi Voice Assistant](https://www.tarat.space/projects/lumi-voice-assistant) (Oct 2025): 350M on-device voice-powered todo app, fine-tuned for natural language task parsing. [HuggingFace](https://huggingface.co/Taru/lumi-mobile)
- [Stock Agents](https://www.tarat.space/projects/stock-agents) (Dec 2025): Stateful AI system using daily news sentiment to predict next-day stock movement — extension of StocksBrew
- [ML-DL Implementation](https://www.tarat.space/projects/ml-implementation) (Dec 2024): Open-source Python ML library from scratch — 30+ contributors worldwide. [GitHub](https://github.com/RoboticsClubIITJ/ML-DL-implementation)
- [Anime Recommendation](https://www.tarat.space/projects/anime-recomend) (Dec 2024): Collaborative filtering on 100K+ MyAnimeList users. [GitHub](https://github.com/TarunTomar122/AnimeRecommendation)
- [CLI Assistant](https://www.tarat.space/projects/cli-assistant) (Sep 2024): Terminal AI assistant with RASA — emails, web search, music playback

### Products & startups

- [StocksBrew](https://www.tarat.space/projects/stocksbrew) (May 2025): AI-curated daily stock news email before market open. $18/month MRR. [stocksbrew.online](https://stocksbrew.online) · [GitHub](https://github.com/TarunTomar122/stocksbrew)
- YourTrace (Jan 2026): Personalized AI/tech briefing. $28/month MRR, Product Hunt #7, $50 MRR week one. [yourtrace.online](https://yourtrace.online) — mobile app 200+ downloads
- [Instafy](https://www.tarat.space/projects/instafy) (Oct 2025): One-click photo aesthetic transfer — copy color grading from any reference photo. [instafy.in](https://instafy.in/) · [GitHub](https://github.com/TarunTomar122/instafy)

### Web / design / tools

- [Digital Garden](https://www.tarat.space/projects/digital-garden) (Dec 2024): This website — writings, projects, notes. Perfect Lighthouse score, PPR + SSR hybrid, copresence layer. [tarat.space](https://www.tarat.space) · [GitHub](https://github.com/TarunTomar122/digital-garden)
- [OOD / Project Nimbus](https://www.tarat.space/projects/ood) (Feb 2025): AI-powered collaborative UX flow design canvas — wireframe generation and iteration
- [Trip Planner](https://www.tarat.space/projects/trip-planner) (Feb 2025): Map-based trip planner with AI-generated place/restaurant details
- [Spotify Reels](https://www.tarat.space/projects/spotify-reels) (Mar 2025): Spotify reels-style experience for music discovery
- [YouTube Shorts Automation](https://www.tarat.space/projects/youtube-automation) (Dec 2024): Automated YouTube shorts from most-viewed segments of popular videos (no AI). [GitHub](https://github.com/TarunTomar122/Automating-a-Youtube-Channel-without-using-AI)

## Writings

- [Compression is all we need](https://www.tarat.space/writings/compression-is-all-we-need): Visual context compression thesis
- [Local LLM](https://www.tarat.space/writings/local-llm): On-device LLMs and why they matter
- [Shipping Spectrum 2.0](https://www.tarat.space/writings/shipping-spectrum-two): Design system migration at Adobe
- [2025 Review](https://www.tarat.space/writings/2025-review): Year in review
- [What do I do?](https://www.tarat.space/writings/what-do-i-do): Career crossroads — job vs masters
- [All writings](https://www.tarat.space/writings): Full writing index

## Garden

- [Home](https://www.tarat.space): Digital garden homepage
- [Tarat AI](https://www.tarat.space/tarat-ai): RAG assistant trained on all garden content
- [Semantic Network](https://www.tarat.space/network): Force-directed graph of content connections
- [Library](https://www.tarat.space/library): Reading list
- [List 100](https://www.tarat.space/list100): Life goals and bucket list
- [Timeline](https://www.tarat.space/timeline): Work experience and career timeline

## Optional

- [Resume](https://www.tarat.space/resume): Resume — work, projects, skills
- [Startups](https://www.tarat.space/startups): Live startup metrics — StocksBrew, YourTrace, Trace mobile
- [Easter Eggs](https://www.tarat.space/easter-eggs): Hidden fun stuff on the site
- [YourTrace](https://yourtrace.online): Daily AI/tech briefing product
- [StocksBrew](https://stocksbrew.online): Live stocks briefing product