LinkGen
Autonomous LinkedIn AI auto-poster
In short: LinkGen (AI / Automation) is a case study from Daniyal Alam’s portfolio: Autonomous LinkedIn AI auto-poster. Core stack: Next.js, React 19, TypeScript.
A LinkedIn automation platform that aggregates trending tech news, generates personalised posts with Google Gemini, finds matching images and auto-posts on a schedule via Vercel cron — engineered to run on free tiers.
- Industry
- AI / Automation
- Scope
- Polished, shipped applications
- Core stack
- Next.js · React 19 · TypeScript · Tailwind
The problem
Creators spend hours finding topics and writing consistent, engaging LinkedIn posts.
The solution
An automated pipeline: discover trending news across 5 sources, generate posts via Gemini, attach images, and schedule via cron with full history and manual revert.
Technical challenges
The engineering problems this build had to get right.
- Rate-limit juggling across 5+ APIs
- Reliable async image upload to LinkedIn
- Cross-source news deduplication
Architecture
Implementation — what shipped
Engineering notes
Lesson for similar AI builds: design for rate-limit juggling across 5+ APIs and reliable async image upload to LinkedIn up front — these are the parts that are expensive to retrofit once the feature list grows.
Technologies
- Next.js
- React 19
- TypeScript
- Tailwind
- Gemini
- Supabase
- LinkedIn API
- Vercel Cron
- NextAuth
Building something similar?
A 30-minute discovery call is enough to scope the approach and a realistic budget. Related at DanixSoft: AI & Machine Learning, Automation Systems.