- Platform
- Web App
- Duration
- 14 weeks
- Industry
- MarTech / SaaS
- Read time
- 5 min read
LinkedIn rewards consistency. The professionals building the strongest networks and getting the most inbound are not necessarily the best writers. They are the ones who show up every week without fail.
Most people who want to post regularly do not have a writing problem. They have a starting problem, a review problem, and a scheduling problem. They have the ideas but not the workflow to turn those ideas into published content without burning an hour each time.
We built Draftly to close that gap. AI handles the blank page. Real-time collaboration handles the review cycle. The queue handles the calendar. In the first 60 days after launch, 500+ professionals were active on the platform and posting three times more often than before.
before & after
What changed
- Professionals wanted a consistent LinkedIn presence but lacked the time to write regularly, with weeks passing between posts
- Teams reviewing drafts over email created version confusion and 2 to 3 day delays, with a single approval thread accumulating eight draft versions
- No central place to see what was scheduled, published, or waiting for sign-off: content fell through or went out twice
- Starting a post from scratch consumed most of the available time, leaving actual content quality as a secondary concern
- No way to match an AI draft to an individual's voice and positioning rather than producing generic LinkedIn prose
- AI generates a ready-to-edit draft in under 30 seconds from a topic and tone selection, tuned to LinkedIn format rather than blog prose
- Multiple editors work on the same draft simultaneously with inline comments, resolved threads, and full version history
- Drafts route through a configurable approval chain before publishing. Approvers are notified, and nothing goes live without sign-off
- A scheduling queue shows every post (draft, approved, scheduled, live) in one view and publishes at the optimal time per user
- A voice profile built during onboarding shapes every AI draft around the writer's role, audience, and the topics they want to be known for
What we had to solve
- 01
Making AI output usable without a second round of heavy editing
The blank page is solved in seconds. But if every AI draft needs 20 minutes of cleanup before it reads like the person who supposedly wrote it, the tool has not saved any time. The challenge was tuning the generation layer so that GPT-4o produced LinkedIn-native output: short paragraphs, a real hook in the first line, natural language rather than corporate tone. That required a system prompt built around how LinkedIn actually performs as a platform and a voice profile per user that draws from their stated positioning rather than generic professional defaults. The goal was a draft that needs light editing, not a rebuild.
- 02
Building an approval workflow faster than just using email
Approval chains only work if they are faster than the default behavior, and the default is email. If routing a draft for sign-off adds a day and requires the approver to remember which version they were asked to review, the team reverts to the thread. The challenge was designing the approval interface so that an approver could open a notification, read the draft in context, leave feedback or approve, and be done in under two minutes. Inline comments with resolution tracking, version history, and a clear queue of posts pending their sign-off made that possible without asking anyone to learn new habits.
outcomes
What we achieved
Professionals were averaging 1 to 2 posts per month. Without a drafting tool, the blank page won every time.
Review rounds via email took 2 to 3 days on average. A single thread would have 8 or more versions attached.
There was no product serving the overlap of LinkedIn content creation and team collaboration.
Your team is still reviewing LinkedIn drafts over email?
the build
What we built
Draftly is built around the idea that writing and reviewing should happen in the same tool, not across five apps.
A ready-to-edit LinkedIn draft in seconds — shaped around the writer's voice and topics
Enter a topic, choose a tone (professional, conversational, story-driven) and Draftly generates a ready-to-edit draft in seconds. The AI understands LinkedIn format: short paragraphs, natural hooks, no corporate jargon. A voice profile built during onboarding shapes every draft around the writer's role and the topics they want to be known for.
Marketing lead and executive refine the same draft simultaneously — no stale copies
Multiple editors work on the same draft simultaneously. Inline comments, resolved threads, and a full version history mean no one is ever working on a stale copy. Changes sync live without refreshing the page, so a marketing lead and an executive can refine the same draft in real time.
Posts can't be scheduled until every required reviewer signs off
Route drafts through a configurable approval chain before they reach the scheduling queue. Approvers get a notification and see the draft in context, not attached to an email thread. A post cannot be scheduled until every required reviewer signs off.
Full pipeline visible in one calendar — nothing gets missed between draft and live
Drag and drop posts into a weekly calendar. Draftly publishes at the optimal time per user or lets you pin a specific slot. The queue shows the full pipeline (draft, approved, scheduled, live) in one view so nothing gets missed.
Want results like these for your business?
stack
Why we chose this stack
- 01Next.jsApp Router with React Server Components gave us fast initial page loads and a clean server-driven architecture that scales without adding client-side complexity to features that do not need real-time sync.
- 02SupabaseReal-time subscriptions power the live collaborative editing without a custom WebSocket server. When one editor types, every other editor in the same draft sees the change immediately.
- 03OpenAIGPT-4o generates drafts with a system prompt built for LinkedIn format and voice matching: short paragraphs, strong hooks, the user's stated positioning. Generic AI prose was the exact problem Draftly was replacing.
- 04AWSScheduled post publishing runs on Lambda with an EventBridge rule per scheduled post. Posts go live at the exact time the user set without a persistent background process running at all times.
Common questions about Draftly
During onboarding, Draftly asks you to describe your role, your target audience, and the topics you want to be known for. That profile shapes every draft. The AI does not write generic LinkedIn posts, it writes for your positioning. You can update the profile at any time and the next draft reflects it immediately.
Yes. Draftly supports multiple team members with role-based access: writers can create drafts, reviewers can comment and approve, and one designated poster publishes to LinkedIn. No shared credentials are needed, and the approval chain ensures nothing goes live without the right person signing off.
Draftly uses LinkedIn's official marketing developer API and publishes within its rate limits. The scheduling queue spaces posts to stay within platform guidelines automatically. If LinkedIn updates its API, the integration layer handles it without users needing to change how they use the product.
Every draft is generated fresh per request. Draftly does not use a shared library or recycle output across users. Your drafts are stored in your account only and are never used to train any model.
We built Draftly (AI draft generation, real-time collaborative editing, approval workflows, scheduling queue, and LinkedIn API integration) in 14 weeks. That timeline was possible because we started with a focused core loop: generate, review, approve, schedule. Tools with more AI personalization layers, multi-platform publishing, or deeper analytics would take longer. Contact us to estimate based on your specific requirements.
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