Social media decision

AuthoredUp

Build — a competent engineer can replicate the core editor, extension-assisted scheduling and analytics over a few months; AuthoredUp's value is product polish, team features and a closed beta AI which are harder to match but not fundamental moats.

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Subscription$19.95/month ✓ verified
Initial build80 hours
Monthly upkeep8 hours + $50
Evidence2/3 runs agree

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.

What a replacement has to do

  • Compose and format a post in an editor, save as draft, schedule/publish to LinkedIn via a Chrome extension, collect post and engagement metrics, surface analytics and reuse suggestions.

What it still won’t have

  • Chrome-extension polish and edge-case handling for LinkedIn UI changes
  • Refined AI coauthor that learns individual voice (closed beta feature)
  • Enterprise/team features such as organization billing, roles and invoicing flows
  • Polished onboarding, documentation and support responsiveness

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying ischeaper in year one.

On cash alone, building overtakes the subscription at 3 seats.

Paid seatsseats

Money you would actually spend

Keep paying

Subscription price × seats × 12

Build it

AI build APIs + hosting

Time you would spend

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal self-hosted LinkedIn content studio (Next.js frontend + React for extension UI, Node/Express backend, Postgres DB, Redis for jobs) that supports: 1) a rich-text editor with bold/italic/emoji and preview, 2) drafts and unlimited snippets library, 3) calendar view with scheduling and reminder emails, 4) a Chrome extension that injects editor into LinkedIn and executes scheduled publishes via the user's session, 5) a collector flow (extension-assisted + manual import of LinkedIn archive) to ingest historical posts and metrics, and 6) basic analytics (impressions, reactions, engagement rate, best time heatmap, top posts and one-click reuse). Out of scope: paid billing, enterprise SSO, advanced AI voice-learning, and multi-tenant invoicing. Include error handling for LinkedIn UI changes, retry logic for publishes/collects, automated tests for backend endpoints and scheduler, and CI deployment scripts to a VPS (DigitalOcean) with secure environment config.
How we checked5 sources · 2/3 runs agreed · evidence score 63

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 5 cited sources+3
  • Price verified on pricing page+3
  • Evidence score63

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time — so the same evidence always produces the same number.

How scoring works →

Cited sources · 5

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat recorded