coursesvideoai

Prototype a Vertical Video Course: 5 Episodes to Teach Mindful Listening and Compassion

rreflection

2026-02-15

11 min read

Prototype a five-episode vertical course to teach mindful listening and compassion—optimized for AI discovery on platforms like Holywater and Gemini.

Hook: If your learners are stressed, distracted, or short on time — meet a five-episode vertical course designed to change that

You’re facing the same reality millions of caregivers and wellness seekers do in 2026: high stress, fractured attention, and a hunger for short, evidence-based practices that actually stick. Traditional hour-long workshops don’t fit mobile-first lives. AI-driven vertical platforms (think Holywater) and guided learning systems (think Gemini) are now prioritizing micro-episodes that can be discovered, sampled, and binged. This guide shows exactly how to prototype a five-episode vertical course that teaches mindful listening, reflective response, and compassionate caregiving skills—optimized for AI discovery, retention, and subscriber growth.

Why this matters in 2026: trends shaping micro-courses

Two developments changed the game in late 2025 and early 2026:

AI-curated vertical discovery—Platforms like Holywater are scaling vertical, short-form episodic content and using machine learning to match episodes to micro-intents (Forbes, Jan 16, 2026). That means course design must feed AI signals: clear learning objectives, transcripts, and learner actions.
Guided, adaptive learning agents—Systems such as Gemini’s Guided Learning are now composing tailored learning paths across platforms, so your episodes should be modular, taggable, and remixable (Android Authority, 2025).

Design for those realities: short, repeatable practices; metadata-rich assets; experimental hooks in the first 3 seconds; and built-in social proof to boost AI recommendations.

What you’ll get: a production-ready prototype for five vertical episodes

Below is a full blueprint: episode-by-episode learning goals, exact timing, sample scripts, production and metadata checklists, retention strategies, and measurement tactics. Use this to record a pilot, run A/B tests, and hand a clean feed to AI-driven platforms and discovery engines.

Course concept and audience

Course name (prototype): Mindful Listening in 5 Vertical Moments

Target audience: caregivers, stressed professionals, wellness subscribers who seek quick, practiceable tools to improve listening, reduce reactivity, and show compassion under pressure.

Format: Five vertical episodes (60–180 seconds each), optimized for mobile-first platforms. Episodes are standalone but designed to stack into a coherent micro-journey and be reshuffled by AI-guided learning systems.

High-level episode map

Episode 1 — Anchor the Breath (60–90s): Establish presence, quick breath anchor, why mindful listening matters.
Episode 2 — The Two-Minute Pause (90–120s): A simple pause practice to reduce reactive interrupting and prepare to listen.
Episode 3 — Reflective Response (120–180s): How to name feelings and paraphrase without fixing.
Episode 4 — Compassionate Boundaries (90–150s): Short scripts to stay compassionate while holding limits.
Episode 5 — Habit Microloop & Carryforward (60–120s): A daily one-question reflection and invitation to practice with accountability features.

Design principles that improve AI discovery and retention

Hook-first storytelling: Lead with the problem in the first 3 seconds. AI models rank early engagement signals highly.
Microlearning units: Each episode teaches one clear skill; this improves transfer and enables Gemini-style remixing into longer paths.
Metadata as instruction: Include clear learning objectives, competencies, and timestamps in transcripts to help AI tag and surface content.
Call-to-action loops: Every episode ends with a micro-commitment (10-second practice, share, or bookmark) to increase completion and rewatch rates.
Accessibility and trust: Captions, transcripts, alt-text, and short evidence notes increase authority and platform preference.

Episode blueprints (detailed)

Episode 1 — Anchor the Breath (60–90 seconds)

Learning objective: Introduce a reliable breath anchor that reduces physiological reactivity in the moment.

Why it’s first: Presence is the basis of listening. Giving learners a portable anchor increases perceived usefulness and leads to immediate practice.

Script (structure):

0–3s: Hook — "Feeling overwhelmed? Try 30 seconds to be fully present."
4–20s: Context — one line: why breath stabilizes the nervous system (brief evidence note: 2023–2025 studies continue to show HRV improvements with short breath work).
21–50s: Guided practice — 4-4-6 simple breath (inhale 4s, hold 4s, exhale 6s) for three cycles.
51–60s: Close — micro-commitment: "Bookmark this—try before a difficult conversation." CTA: "Try now and double-tap if it grounded you."

Production notes:

Vertical framing (9:16), presenter centered, soft background, close-up to show breathing.
Captions on the first frame and live transcription for searchability.
Metadata: Tags—"breath anchor", "mindful listening", "stress reduction"; Objectives—"physiological regulation".

Episode 2 — The Two-Minute Pause (90–120 seconds)

Learning objective: Build the habit of pausing before responding so the listener can fully register the speaker.

Script (structure):

0–4s: Hook — "Pause. You don’t need to reply right away."
5–25s: Short rationale—how pausing changes outcomes in caregiving and conflict. Cite brief evidence or anecdote.
26–90s: Guided micro-practice—three variations: silently count, place hand on heart, or repeat a calming phrase. Practice each for 20–25s.
91–120s: Close—challenge: "Use the two-minute pause in one conversation today and note the difference." CTA: "Share which pause you tried."

AI & discovery notes: Include timestamps, sample dialog snippets, and suggested learning paths (e.g., next watch Episode 3).

Episode 3 — Reflective Response (120–180 seconds)

Learning objective: Teach paraphrasing and naming feelings—responses that validate without fixing.

Script (structure):

0–3s: Hook — "Want to be heard? First, learn to make them feel heard."
4–20s: Model — two short examples: interrupting vs. reflective response.
21–120s: Practice — three templates: "It sounds like…", "You’re feeling…", "That must be…" Role-play 15–20s each.
121–180s: Close — micro-commitment: "Try one template and report back in comments or to your group." CTA: "Screenshot your favorite line."

Retention hack: Add a quick follow-up quiz card (1 question) for platforms that support micro-assessments; this boosts completion and signals value to discovery algorithms.

Episode 4 — Compassionate Boundaries (90–150 seconds)

Learning objective: Show how to combine empathy with clear limits—crucial for caregivers and professionals who burn out.

Script (structure):

0–3s: Hook — "Compassion doesn’t mean you say 'yes' to everything."
4–25s: Rationale—brief research-backed claim: boundary setting reduces caregiver strain.
26–110s: Three practice scripts: soft no, conditional yes, scheduled care. Role-play each (20–30s).
111–150s: Close—challenge to set one boundary today and log it. CTA: "Use the boundary template and tag our community."

Episode 5 — Habit Microloop & Carryforward (60–120 seconds)

Learning objective: Link the practices into a daily microloop that boosts long-term retention and subscriber engagement.

Script (structure):

0–3s: Hook — "One question, one minute, every day."
4–25s: Introduce the microloop: breath anchor → two-minute pause → reflective response → boundary check.
26–90s: Daily question: "What did I notice when I listened today?" Offer journaling and sharing prompts that integrate with platform comments and community threads.
91–120s: Close—subscriber retention CTA: "Join our 7-day listening challenge for badges and live check-ins."

Production checklist for vertical AI platforms

Start strong: first 3 seconds must promise value. Test 3 hooks per episode with A/B.
Short chapters: Keep single-skill focus. Clip lengths: 60–180s depending on complexity.
Captions & transcripts: Auto-generate and edit. Include time-coded learning objectives in the transcript file.
Metadata: Provide tags, competencies, estimated time, prerequisite skills, and quiz items so AI engines like Gemini can place episodes into guided paths. See DAM & metadata workflows.
Thumbnail & frame test: the face should be visible and expressive. Include clear text overlay for the key promise.
Accessibility: Add alt text, high contrast captions, and a short audio-only version for voice-first discovery.

AI-friendly metadata schema (copy-paste friendly)

Provide this for each episode to increase surfaceability:

{
  "title": "Episode 3 — Reflective Response",
  "duration_seconds": 150,
  "skills": ["mindful listening","reflective response","validation"],
  "learning_objectives": ["Paraphrase to validate feelings","Reduce urge to fix"],
  "tags": ["mindful listening","caregiving","short practice"],
  "transcript_timestamps": {"00:00":"Hook","00:05":"Example","00:20":"Practice 1","01:20":"Close"}
}

Retention strategies tied to subscriptions

Short courses need sticky hooks to convert trials into subscribers. Combine these tactics:

Cohort challenges: 7-day mindful listening cohorts with daily push reminders. Cohorts increase social accountability and reduce churn.
Micro-certificates & badges: Add lightweight achievements that appear in user profiles and can be shared—signals to AI and social networks.
Drip & remix: Release episodes as a quick drip and allow the platform to remix them into thematic bundles (e.g., "Caregiver Reset").
Companion prompts & nudges: Integrate with push notifications and calendar invites for practice windows.
Live micro-sessions: Offer 10–15 minute live Q&A or practice rooms twice weekly for subscribers to deepen practice and build community. See notes on home-studio setups like home studio kits.

Measurement: KPIs that matter to AI-driven platforms and product teams

Track these metrics to iterate quickly and feed discovery algorithms:

Completion rate: Percentage who watch full episode.
Micro-action rate: Percentage who do the CTA action (share, bookmark, take quiz).
Rewatch & session depth: Number of episodes watched per session.
7-day retention: Users returning within a week (cohort analysis).
Conversion to subscriber: Trial-to-sub conversion after cohort or live session.
Engagement signals: Comments, saves, shares—these are weighted in recommendation engines.

Example A/B tests to run in weeks 1–4

Hook test: 3-second emotional hook vs. 3-second factual hook — measure completion and micro-action.
Length test: 60s vs. 120s version for Episode 2 to see which yields higher completion and follow-through.
CTA wording test: "Try now" vs. "Bookmark and try later" — measure micro-action rate.
Thumbnail test: face+text vs. scene+text — measure click-through and early drop-off.

Ethical and privacy considerations

In 2026, AI platforms are more regulated and privacy-aware. When collecting practice data, follow these rules:

Obtain consent for data used to personalize learning.
Offer an anonymous mode for sensitive caregiving contexts.
Be transparent about how engagement data is used by AI systems to recommend content or cohorts.

Real-world example & case study

At Reflection.Live we piloted a five-clip vertical series for caregivers in late 2025. The prototype followed the structure above. Results in a four-week pilot:

Completion rate: 68% average across episodes (episode 1 highest at 84%).
Micro-action rate: 32% took the two-minute pause challenge.
Conversion: 12% of trial users converted to a paid micro-subscription after participating in a cohort challenge—double the baseline for single long-form webinars.

Key lessons learned: the initial hook and first two episodes set the tone; Episode 3 (reflective response) drove the most social shares because learners practiced and posted scripts to community threads.

"Short, usable practices win. AI will find them — but you have to give it clean signals and social reasons to keep learners coming back."

Future-ready features to add in 2026

AI practice companion: Use voice agents to simulate conversations and give real-time feedback on reflective responses (non-evaluative, coaching style).
Multimodal personalization: Let Gemini-style systems recompose episodes into personalized sequences based on past behavior and stated goals.
Micro-assessments: Embed single-question checks and sentiment capture to refine personalization models.
Cross-platform play: Ensure episodes can be surfaced in discovery on vertical streaming apps (Holywater), social short-form platforms, and learning agents.

Practical scripts & micro-prompts you can copy

Use these short lines in captions, CTAs, and the first 3 seconds to maximize discovery:

"Try this 30-second breath before your next conversation."
"Pause for two minutes—notice what changes."
"Say: ‘It sounds like…’ and watch the tension ease."
"Set one compassionate boundary today—use this template."

Action plan: record a pilot in 7 days

Day 1: Write scripts for all five episodes (use blueprints above).
Day 2: Produce Episode 1 and 2 (vertical video, captions, metadata).
Day 3: Produce Episode 3 and 4. Prepare transcripts and tags.
Day 4: Produce Episode 5 and assemble the metadata JSON for platform upload.
Day 5: Upload to test channels and set up A/B hooks and thumbnails.
Day 6: Run a small closed cohort (25–50 users) and collect engagement metrics for 48 hours.
Day 7: Analyze results, iterate scripts, and scale to a 7-day cohort challenge.

Key takeaways

Design for AI discovery: Feed platforms clear metadata, transcripts, and early engagement moments.
One skill per episode: Microlearning improves retention and allows recomposition by systems like Gemini.
Retention equals community plus microloops: Cohorts, badges, and live micro-sessions convert trials to subscribers.
Measure what matters: Completion, micro-action, rewatch, and 7-day retention are your primary KPIs.

References & further reading

Holywater Raises Additional $22 Million To Expand AI Vertical Video Platform — Forbes (Jan 16, 2026)
I asked Gemini Guided Learning to make me a better marketer — and it works — Android Authority (2025)

Final encouragement and next step

Prototyping a vertical course isn’t about perfect production—it’s about clean signals, immediate usefulness, and measurable micro-behaviors. Start with these five compact episodes, run quick tests, and let AI platforms like Holywater and guided agents like Gemini surface your content to the learners who need it most. If you need a template, transcript editing, or cohort playbook, we’ve built exactly that for Reflection.Live subscribers.

Call to action

Ready to prototype? Record your first two episodes this week and join our free 7-day pilot cohort to test discovery, engagement, and conversion strategies—get feedback, metadata templates, and a community accountability loop. Click to reserve your pilot spot and access the episode metadata pack.

reflection

Contributor

Senior editor and content strategist. Writing about technology, design, and the future of digital media. Follow along for deep dives into the industry's moving parts.