Documentation
Back to Dashboard

Content Reservoirs

Strategic content collections that fuel every social post, thread, and newsletter. Build once, draw from forever — and let AI suggest the keywords that keep them current.

A Content Reservoir is a strategic collection of source material — articles, threads, transcripts, notes, links — organized around a theme you want to publish on. Once built, it fuels every downstream content surface: X threads, LinkedIn posts, Meta Threads posts, newsletters, blog drafts.

What are Content Reservoirs?

Traditional approach. You sit down to write a tweet or a post. You start from a blank page and try to remember what you know about the topic. You miss your best material because it's buried in old notes, browser history, or your head.

Reservoir approach. You build the reservoir once — a curated collection of the best source material on a topic, with AI analysis layered on top. When you sit down to write, you pull from the reservoir. The hard work happened upstream; the moment of writing is just selection and shaping.

This pattern compounds: every piece of source content you save makes future content stronger. Reservoirs don't go stale — they get more powerful.

Key Concepts

Reservoir structure

Each reservoir has:

  • A theme — the strategic topic the reservoir is built around (e.g. "AI agent architecture", "Developer productivity tools", "B2B SaaS go-to-market")
  • Source items — individual content pieces inside the reservoir. Each item carries the URL, content, your notes, and AI-enriched metadata (themes, key arguments, confidence, freshness)
  • Keywords — the monitoring vocabulary tied to this reservoir. New content matching these keywords flows in automatically via Content Monitoring
  • Generation lineage — which reservoir fed which published piece, so you can trace what's working

Content intelligence

Every item in a reservoir is analyzed by AI on ingest:

  • Primary themes extracted
  • Key arguments identified
  • Evidence and data points surfaced
  • Confidence scored (how strongly this item supports the reservoir's theme)
  • Freshness tracked (recent content scored higher in selection)

This means when you generate content from a reservoir, the AI isn't reaching into a bag of links — it's reaching into a graph of arguments and evidence that already knows what each piece is for.

Multi-platform distribution

A single reservoir can feed every platform. Same source material, different formats:

  • A long-form blog post that's the canonical statement
  • A 5-tweet thread that summarizes the key argument
  • A LinkedIn post that frames it for a professional audience
  • A Threads post that opens the conversation casually
  • A newsletter section that contextualizes recent items

The reservoir is the substance; the formats are the surfaces. Content Generation covers how this gets wired together.

Reservoir Workflow

  1. Create a reservoir at /admin/reservoirs with a clear theme name. Choose a reservoir theme template for quick setup, or start blank.
  2. Add source content — manually paste a link or article, forward emails into the reservoir's inbound address, or let monitored keywords flow content in automatically.
  3. AI analysis & planning — every item gets enriched on ingest. The planning view groups items by theme and suggests publishing angles.
  4. Generate & distribute — pick items, choose a format, generate a draft. Drafts land in their respective editors (X Studio, LinkedIn Studio, Threads Studio, newsletter composer) for review. From there: Post Distribution Dashboard tracks where every published piece has been pushed.

Unified Keyword Management

Reservoir keywords serve double duty: they define what new content auto-flows into the reservoir AND drive content monitoring discovery.

Automatic monitoring integration. Every keyword added to a reservoir is automatically active in content monitoring. Reddit, Twitter, RSS, and other configured sources match against these keywords and pipe matching content into the right reservoir.

Protected management. Reservoir keywords are versioned and protected from accidental deletion. The monitoring system and the reservoir system share the same source of truth — no manual reconciliation.

How to manage reservoir keywords

  • Add/remove keywords directly in the reservoir's settings panel
  • Bulk-import keywords from a CSV or paste-in list
  • AI-suggested keywords (see below) come pre-filled but require explicit approval before going live

AI-Powered Keyword Generation

When you create a new reservoir or want to expand an existing one, the AI suggests keywords based on the theme name and existing source content.

Smart ChatGPT integration

The keyword generator uses your stored OpenAI key (configured in Settings) to:

  1. Read the reservoir's theme name and any seeded source items
  2. Propose a vocabulary of 20–60 keywords spanning literal terms, synonyms, related concepts, and adjacent topics
  3. Surface them in a review UI where you accept, edit, or reject each suggestion

Only accepted keywords go live — nothing is added without your sign-off. The aim is to give you a faster cold-start, not to flood your monitoring queues with noise.

Read more about keyword management →

Workflow detail pages

Related

Want this page as machine-readable markdown? GET /docs/features/content-reservoirs.md