Manicule
AgentRel — Devrel For Agents
LinkedIn Content Marketer
About the role
Manicule is building AgentRel: systems that help companies become sources AI agents cite and recommend.
Most B2B LinkedIn content is indistinguishable: the same hooks, the same founder lessons, and the same carousels nobody remembers.
I’m looking for someone who can make technical founders interesting without turning them into LinkedIn influencers. You can interview someone, find the idea underneath what they said, and write it in a voice that still feels like theirs.
You understand developer tools and B2B attribution. You care about replies from the right people, qualified inbound, and pipeline - not likes from other content marketers.
You should use AI deeply, but have enough taste to know when it made the writing worse.
What you’ll do
- Own LinkedIn strategy for Manicule and our customers.
- Interview founders, engineers, and subject-matter experts.
- Turn technical ideas into sharp posts and longer narratives.
- Measure profile growth, qualified engagement, inbound, and pipeline.
- Turn your process into repeatable AI workflows and quality checks.
Who we’re looking for
- 1+ years writing LinkedIn content for technical or B2B companies.
- Experience with developer tools, infrastructure, or AI.
- A portfolio with at least two projects showing strategy, execution, and results.
- The ability to preserve someone’s voice instead of replacing it with yours.
Your first 30 days
You’ll own LinkedIn strategy for one customer end to end: learn the product, interview the founder, define their point of view, ship content, and build a clear attribution system.
The goal is not “post consistently.” It is to make the right people remember what the company believes.
Details
- In person in Singapore.
- $50K–$100K USD annually.
- 0.5%–1% equity.
- Unlimited GPT and Claude, including Fable.
About Manicule
Manicule is trying to solve a problem most people have given up on: getting AI to write well.
Everyone can get a model to produce words, but it feels so empty. Almost no one can get it to produce writing with a point of view, a logically sound structure, and a unique tone.
We want to solve these problems at scale. That means turning the judgment of strong writers into something repeatable that an AI can actually run on. Part of the work is engineering: prompts, evals, the harness around them. Part of it is editorial taste. Most of the work is experimentation, because nobody has the answers yet, and the frontier moves every few weeks.
We also think the audience for writing is changing. More and more, what we produce is read by agents as much as by people, and we're already working on catering to them.
We're small, we hire rarely, and people stay. If the idea of teaching a machine to write the way you'd want to read excites you more than it worries you, we should talk.
