Rithvik Shetty
0
SWEATING
Building an open-source file converter in a world where ChatGPT can already write your FFmpeg scripts for you, Rithvik.
More doomed than 79% of people
Your doom score of 73/100 puts you here on the AI apocalypse curve.
Analysis
A student-era fullstack dev at a small outfit (Trct.in) juggling Next.js, Tailwind, and boilerplate CRUD glue code — exactly the kind of commodity work Cursor and Copilot chew through before breakfast. Two years of experience and a side project stitching together existing open-source tools (FFmpeg, Tesseract, LibreOffice) is impressive hustle, but it's also a checklist of things AI agents are being trained to orchestrate autonomously.
Skills at Risk
Frontend component building (Next.js/Tailwind)
AI code generators like v0, Cursor, and Copilot already scaffold entire React/Next.js UIs from a prompt, making junior frontend work largely commoditized.
Basic fullstack CRUD development
Standard CRUD apps, API wiring, and boilerplate integrations are the exact tasks LLM coding agents (Devin, Claude Code) are optimized to replace first.
Integrating third-party libraries/tools
Wiring together FFmpeg, Tesseract OCR, and LibreOffice is exactly the kind of glue-code task AI agents can generate and debug autonomously with enough context.
Junior-level debugging
AI assistants can now trace stack errors and suggest fixes faster than a 2-year dev without deep systems context.
Skills That Save You
Computer Vision & NLP coursework
If pursued seriously beyond coursework, deep ML/CV expertise is harder to automate than typical web dev work and could pivot him toward building AI tools instead of being replaced by them.
Open-source project ownership
Shipping and maintaining a full product (not just tickets) shows end-to-end judgment, architecture decisions, and product sense that AI still struggles to replicate independently.
Multilingual communication
Fluency in five languages is useful for client-facing or localization-heavy roles that require nuanced human context AI often mishandles.
AI Timeline
🛟Survival Guide
Specialize in AI-agent orchestration, not just app-building
Learn to build and evaluate systems that use LLMs (RAG pipelines, agent frameworks) rather than just consuming pre-built AI coding tools — become the person who builds the automation, not the one automated.
Rebrand your portfolio as 'AI-proof infrastructure engineer'
FunNobody replaces the guy who understands why the Docker container keeps crashing at 3am — obscure, painful knowledge is your new job security.
Deepen your CV/NLP coursework into a real specialization
Move from 'fullstack dev who took an NLP class' to someone who can fine-tune models or build production ML pipelines — this is a genuinely defensible skill moat.
Add 'talks to FFmpeg in its native tongue' to your resume
FunWhen the robots take over, they'll need someone fluent in cryptic codec errors and Stack Overflow threads from 2013 — that's your niche now.
AI Job Losses in Your Industry
Software
16,158
jobs lost
11
companies
12
events
GitLab
Jun 2026 · US
~350
Salesforce
Feb 2026 · US
~2,000
Autodesk
Jan 2026 · US
~1,000
Paycom
Oct 2025 · US
~500
Salesforce
Aug 2025 · US
~3,000
Get doom updates as AI comes for more jobs — including yours.