Free Tool · BYOK
TL;IN
Turn articles, videos, and notes into LinkedIn posts that sound like you
Drop in what you're reading, watching, or thinking about. Out comes a LinkedIn post in your voice — ready to copy and post.
Launch App →A voice that's actually yours
Say who you are and what you're building toward. The draft picks up your stakes, vocabulary, and angle — instead of the generic “thought leader” smell.
One post instead of five tabs
The article you read, the video you watched, the note you took — woven into one coherent take that finds the through-line.
Drafts that remember you
Paste your best posts once. Every future draft matches your rhythm, hook style, and voice. Stays in your browser, never on our servers.
Nail the hook without starting over
The first two lines decide whether anyone reads the rest. Iterate cheaply on just the opening — the body stays put.
End how you mean to
Spark a conversation, drive clicks, call for collaborators, or let the insight stand. Different posts, different endings.
Your keys, your data
No subscription, no account, nothing stored on our servers. You pay the AI provider directly — pennies per draft.
How it works
- Drop in what you're working with. A URL, a video link, a PDF, or just your notes.
- Say who you are. One line, like “I'm a founder building thought leadership in AI product strategy.” Or pick a hint to start.
- Pick how it reads and how it ends. Story, take, or framework. Spark comments, drive clicks, or let the insight stand.
- Generate, tweak, copy. Two variants in your voice. Into LinkedIn. Done.
Who TL;IN is for
- Founders and operators who want to share what they're learning without spending an hour turning three tabs into one post.
- Builders and engineers who take thorough notes but freeze on the blank LinkedIn compose box.
- Researchers, authors, and creators with a steady reading diet and a small audience they want to feed.
- Anyone rebuilding their LinkedIn presence who already has a voice — from old blog posts, talks, or decks — and wants every draft to sound like them, not a generic “thought leader.”
Not for you if: you're looking for scheduled auto-posting, engagement-pod tactics, or anything that writes on autopilot while you're away. TL;IN is a drafting tool, not a bot.
How TL;IN is different
There are dozens of LinkedIn AI tools. Here's the short version of what makes this one distinct.
Multi-source synthesis, not one-shot rewriting
Most tools take a single prompt or article and regenerate it. TL;IN stitches together multiple sources — an article, a YouTube video, and your own notes — into one coherent post that finds the through-line.
Voice matching from your actual writing
Paste a few of your best posts once. The model learns your rhythm, opener style, and vocabulary. Every future draft inherits that voice profile, stored locally in your browser.
Cheap iteration on just the hook
The first two lines decide whether anyone reads the rest. Regenerate only the opener — the body stays put, your tokens stay small, and you can cycle through 10 hooks in the time other tools take to write one full post.
BYOK, not a subscription
No monthly fee, no seat license, no account. Bring your own Anthropic API key, pay pennies per draft directly to the provider, and keep your prompts and output off anyone else's server.
Want real coaching on LinkedIn?
TL;IN drafts your posts. Jay Alic teaches you how to think about them — ranked the #1 LinkedIn coach in the world three years running, with 1,000+ founders coached one-on-one.
- Read my interview with Jay
- Watch our podcast on YouTube
- Join Link Up, Jay's community
Frequently asked questions
What is TL;IN?
TL;IN is a free web app that turns articles, YouTube videos, PDFs, and your personal notes into LinkedIn-ready posts written in your voice. It synthesizes multiple sources at once, matches your rhythm from example posts you paste in, and hands you two variants to copy into LinkedIn. It is a drafting tool — it does not post for you.
How is TL;IN different from other LinkedIn AI tools?
Most LinkedIn AI tools are scheduling and analytics platforms that bolt on generic AI rewriting. TL;IN is narrower and deeper: it synthesizes multiple sources into one post, tunes to your voice from your own writing samples, and gives you cheap hook-only regeneration. It has no scheduler, no auto-posting, and no engagement tracking — you copy the draft into LinkedIn yourself.
What sources can TL;IN accept?
Article URLs, YouTube video links (with transcripts auto-fetched), PDF files, and pasted text or personal notes. You can combine several of these in a single draft so the post reflects the actual shape of how you took in the material.
Does TL;IN post automatically to LinkedIn?
No. TL;IN never posts on your behalf. It generates a draft that you review, edit, and copy into LinkedIn yourself. This is intentional — auto-posting is against LinkedIn's best practices and makes it too easy to publish something that doesn't actually sound like you.
How does TL;IN match my voice?
You paste a few of your best existing LinkedIn posts (or any prose that sounds like you) into a voice-matching step. The model extracts your rhythm, vocabulary, opener patterns, and angle, then uses that profile for every subsequent draft. The samples stay in your browser's local storage and never reach any TwoSetAI server.
Is my data stored on TwoSetAI servers?
No. TL;IN stores your API key, your voice-matching samples, and your drafts locally in your browser. Source text is sent directly from your browser to the Anthropic Claude API using your own key. TwoSetAI does not operate a backend for TL;IN, so there is no account to sign into and no logs of your content on our side.
How much does TL;IN cost?
The TL;IN app itself is free. You bring your own Anthropic API key and pay the Anthropic API directly at their published per-token rates. A typical draft costs a few cents, depending on source length and which Claude model you pick. There is no TwoSetAI subscription or paywall.
What models does TL;IN support?
TL;IN uses Anthropic Claude models (Sonnet and Haiku by default) via your BYOK key. You pick the model at draft time: lower-cost Haiku for quick iteration, higher-quality Sonnet for polished final drafts.
Who built TL;IN?
Angelina Yang, the sole operator of TwoSetAI and a fast.ai fellow. She built TL;IN for her own LinkedIn workflow after realizing that every generic AI tool produced posts that sounded nothing like her. It is part of Angelina's Lab, a collection of free BYOK tools.