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Case study • Conversation design • Content ops tooling

Helping small content teams decide what to post next with a Voiceflow AI assistant

Small creative and content teams rarely struggle with a lack of ideas—they struggle with deciding what to prioritize and where it should live.

My role

Conversation design, prompt design, Voiceflow prototyping

Audience

Small creative/content teams (understaffed, multi-channel)

Tools

Voiceflow, LLM prompting, structured evaluation prompts

Outcome

Reduced “what do we post?” decision friction by turning messy idea dumps into a ranked plan.

The problem

Most small content teams don’t have a content shortage. They have a prioritization problem: too many ideas, too many channels, not enough time, and no clean way to make decisions quickly.

  • Backlogs of drafts and half-finished ideas
  • Limited bandwidth for strategy and planning
  • Multiple channels with different audience expectations
  • Decision-making becomes the bottleneck (not creativity)

What I built

The chatbot guides users through a structured decision flow—basically a lightweight strategy session in conversational form.

Key design decisions

1. Lower the friction to start

Users are explicitly told that messy input is welcome. This reduces hesitation, encourages brainstorming, and mirrors real creative workflows where ideas rarely start fully formed.

2. Gather context before generating output

The bot asks about goals, audience, channels, and tone before evaluating ideas. This structured context dramatically improves the relevance of the final output and prevents generic recommendations.

3. Position AI as a collaborator, not a replacement

The bot focuses on analysis and prioritization—tasks many creative teams find draining—while leaving ideation and execution to humans. This framing makes the tool feel supportive rather than threatening.

  1. Clarifies the team’s primary goal
  2. Defines the target audience
  3. Identifies available content channels
  4. Establishes tone and positioning
  5. Collects a “messy is fine” list of 5–10 content ideas
  6. Evaluates and compares each idea
  7. Recommends what to publish next

Process

The assistant works best when it behaves like a structured planning partner: gather context, accept messy input, then evaluate ideas against the team’s real constraints.

1) Intake

Collect goal, audience, channels, and tone before touching the idea backlog. Context first, always.

2) Evaluation

Score ideas against relevance, effort, and fit. Compare options instead of generating endless new ones.

3) Output

Return a ranked recommendation plus a simple next-step plan so the team can actually ship.

Screenshots

Coming soon. This will include a quick look at the flow, plus example outputs.

Screenshot

Flow overview (placeholder)

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Screenshot

Example evaluation output (placeholder)

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What I learned

This project taught me to think about AI and creativity differently. Creative teams aren’t short on ideas— they’re short on time, clarity, and decision support.

Instead of replacing creative work, AI can reduce the logistical overhead: ingest messy inputs, surface patterns, and help teams compare options faster—so humans can stay focused on the creative parts they actually enjoy.

Try the bot

Demo

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