Trndinn
Create and grow on social without the chaos
What it does
Trndinn is built for creators and teams who are tired of jumping between multiple tools just to manage social media. It brings everything into a simpler workflow — from creating content to planning and publishing — so you can focus on what actually matters. We’re still early, but already seeing strong adoption from users looking for a cleaner, faster way to run their social presence.
Plan, create, and schedule LinkedIn and social posts with AI—you stay in control. Built for creators, marketers, and agencies. Transparent plans; see demo.
Trndinn's agents draft on-brand posts from the examples you provide, schedule them on a visual calendar, and publish to the accounts you connect — then feed your Content Engine to rank, distribute, and newsletter. You stay in control; agents do the work. Trndinn is a member of leading startup and AI programs that back early-stage builders. Program acceptance reflects membership only and does not imply endorsement by NVIDIA, Google, AWS, or ElevenLabs. LinkedIn is live today, with more channels on the roadmap. You connect accounts; we comply with each platform's policies. You grant access, you stay in control, and you can disconnect anytime. You connect the accounts you own as each channel…from trndinn.com
Does the same job
all alternatives →More growth this month
the category →
AstraPixels▲267A pixel-art solar system at its real current positions.
Growth · 29d ago · astrapixels.com

Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com