SAFEDOOMED
Rithvik Shetty

Rithvik Shetty

0

SWEATING

Building an open-source file converter in a world where ChatGPT can already write your FFmpeg scripts for you, Rithvik.

79%

More doomed than 79% of people

Your doom score of 73/100 puts you here on the AI apocalypse curve.

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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

high

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.

high

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.

medium

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.

medium

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

~3years until significant automation of this role

🛟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'

Fun

Nobody 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

Fun

When 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

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