Video Marketing Series — Moodboard & Production Plan
Every feature.
One 30-second story.
A full-time video production system for Sniffer — dark-to-light storytelling, bold typography, gradient accents. Built to convert engineers, support leads, and agency owners.
7
Feature Videos
30s
Per Video
3
Audiences
4
Phases / Video
Visual Identity
Dark pain. Bright solution.
Every. Single. Time.
Every video follows one visual law: the problem lives in darkness, the solution explodes into light. The audience feels the shift.
Hook Phase · Dark Background
"Your engineers dug for 3 days.
Logs incomplete.
Steps unclear."
Logs incomplete.
Steps unclear."
Dark background #0d0d1a · White text fades in · Red/orange for pain words · Terminal-style flickers · No characters — pure text + atmosphere
Solution Phase · Light Background
Sniffer fixes that.
Clean white background · Gradient typography (purple → teal) · Screen recording overlays · Characters appear when needed for social proof · Professional, confident, energetic
Phase 1 — Hook
0s → 8s
Dark scene. Pain statement. Specific numbers. The viewer nods and says "yes, that's me." No product. No logo. Just the problem, raw.
→
Phase 2 — Flash Cut
8s → 12s
Hard cut. Screen flashes bright. Gradient logo appears. The moment of relief. Music tempo shifts up. The emotional switch.
→
Phase 3 — Feature Demo
12s → 24s
White background. Real screen recording. Gradient text highlights key features. Characters if context needs human proof. Fast, confident, satisfying.
→
Phase 4 — CTA
24s → 30s
Logo lock-up. Gradient headline. URL. One clean line. "Start free at sniffer.dev." Music resolves. End frame holds 2 seconds.
Color Palette
#0a0a12
#1a1a2e
#ff6b6b
#7F77DD
#1D9E75
#EEEDFE
#f8f9fb
#ffffff
Typography System
Display
Every Bug. Captured.
Syne 800 · Main titles, key statements, CTA headlines
Hook Text
"Three days gone. Still no answer."
Syne 700 · Pain statements on dark background · White color in-video
Body / VO
Sniffer fixes that. Every bug arrives with a full recording, console errors, network calls, and the exact line that broke.
Inter 400 · Voice-over scripts, descriptions
Code / Data
checkout.js:142 → NullPointerException → 92% confidence fix
JetBrains Mono 400 · Technical details, file paths, line numbers
Video Series — 7 Episodes
One feature.
One story. One video.
Each video targets a specific audience and pain point. The series builds a complete picture of Sniffer without repeating itself.
"When was the last time you pushed a release because of a bug no one could reproduce?"
✓
EP 01 — ✓ Produced
Bug Full Context
Engineers get full recording, console errors, network calls, root cause + AI-suggested fix with confidence score. The complete "why it broke" in one ticket.
"Your engineers type 'fix this bug'.
That's the whole workflow."
That's the whole workflow."
Next →
EP 02 — Proposed Script
MCP Server: AI-Powered Debugging
Sniffer MCP Server feeds full bug context into Cursor, Claude Code, and Windsurf automatically. Engineers type one command. The AI gets everything: recording, repro steps, root cause, suggested fix.
"Your support team spends 30 minutes per ticket just gathering context."
EP 03 — Planned
Support: 30 Minutes → 5 Minutes
Agent sends a recording link from Zendesk. Customer records in-browser in 2 minutes. AI report arrives: video + repro steps + root cause. No back-and-forth. No install required.
"12 client sites. 4 dev vendors. Every bug is a Slack thread with a cropped screenshot."
EP 04 — Planned
Agencies: Stop Managing Bugs in Slack
Capture on client site, annotate, assign to vendor. Dev team gets a dev-ready ticket with recording, browser info, and AI repro steps. Vendors get free seats — no subscription needed.
"You found out about the bug from a 1-star review.
Your monitoring said nothing."
Your monitoring said nothing."
EP 05 — Planned
Auto Error Detection: Before They Report It
One JS snippet passively captures console errors, network failures, and unhandled exceptions in real-time. Sniffer surfaces the bug before the customer does.
"Sprint 12: fixed it.
Sprint 14: it's back.
Same bug. Different engineer."
Sprint 14: it's back.
Same bug. Different engineer."
EP 06 — Planned
Regression Tests: The Bug That Came Back
Playwright/Cypress tests auto-generated from each bug recording. Built from real user steps, real navigation, real inputs. Push to CI so that bug never ships again.
"One bug.
Four AI steps.
Zero guessing."
Four AI steps.
Zero guessing."
EP 07 — Series Finale
The Full Pipeline
The overview video. Shows all 4 AI steps: Repro Steps → Analyze Errors → Recommend Fix → Generate Test. Hero video for homepage and paid ads. Strongest CTA in the series.
Script Detail
EP 02 — MCP Server
Full Script & Shot Plan
Proposed next video. This targets senior engineers and dev leads who already use AI coding tools (Cursor, Claude Code, Windsurf). Unique differentiator: MCP integration is rare — no competitor does this.
EP 02 · MCP Server: "Type 'fix this'. That's it."
Total: 30s · 4 phases
TIMECODE
VISUAL / ON-SCREEN
VOICE-OVER / TEXT
0s → 8s
HOOK · DARK
Visual
Black terminal screen. Red error text flickers: ERROR checkout.js:142
Jira ticket opens. Title only: "Checkout broken." Body: empty. Timer in corner counts up: 1h… 2h… 3h…
Jira ticket opens. Title only: "Checkout broken." Body: empty. Timer in corner counts up: 1h… 2h… 3h…
Voice-Over
"Your engineers open the ticket."
"No logs. No steps. Just a title."
[pause — 1 second silence]
"Three hours of investigation. Still nothing."
"No logs. No steps. Just a title."
[pause — 1 second silence]
"Three hours of investigation. Still nothing."
8s → 12s
FLASH · TRANSITION
Visual
Hard cut to white. Screen flashes. Sniffer logo appears with gradient. Cursor IDE opens — clean, professional, light theme. Music tempo shifts up noticeably.
Voice-Over
[no words — let the visual transition breathe]
[soft "whoosh" sound design]
[soft "whoosh" sound design]
12s → 24s
DEMO · LIGHT
Visual
Screen recording — Cursor IDE, white background.
Engineer types: "fix this bug"
Sniffer MCP auto-populates in AI context:
📹 Recording · 47 seconds
📋 3 repro steps · auto-generated
⚠️ checkout.js:142 · root cause identified
💡 Suggested fix · 92% confidence
🧪 Playwright test · ready to push
AI starts generating the fix immediately.
Engineer types: "fix this bug"
Sniffer MCP auto-populates in AI context:
📹 Recording · 47 seconds
📋 3 repro steps · auto-generated
⚠️ checkout.js:142 · root cause identified
💡 Suggested fix · 92% confidence
🧪 Playwright test · ready to push
AI starts generating the fix immediately.
Voice-Over
"With the Sniffer MCP Server, your AI coding agent gets everything."
"The recording. The repro steps. The root cause. The suggested fix."
"Type 'fix this'. That's the whole workflow."
"The recording. The repro steps. The root cause. The suggested fix."
"Type 'fix this'. That's the whole workflow."
24s → 30s
CTA · LIGHT
Visual
Clean white frame. Sniffer logo centered. Gradient headline fades in. URL appears. End card holds for 2 seconds. Subtle gradient pulse behind logo.
Voice-Over
"Your AI. Your workflow."
"Start free at sniffer.dev."
"No contract. Your data stays yours."
"Start free at sniffer.dev."
"No contract. Your data stays yours."
How I'll Produce This
Production system
for full-time delivery.
Each video follows the same production pipeline. Consistent quality, predictable schedule, scalable across the full series.
2–3
Days per video
Script → Screen recording → Edit → Color grade → Sound design → Final delivery
3
Formats delivered
16:9 for YouTube/web · 9:16 for Reels/TikTok · 1:1 for LinkedIn
2
Revision rounds
Script approval before filming. Edit review before final export. Fast turnaround.
Phase 1 — Script & Storyboard
- Write the full VO script and on-screen text for each video
- Storyboard: define each scene — what's on screen, when the dark-to-light transition hits
- Identify which scenes need a character/actor and which are pure screen recording
- Client approval on script before any filming begins
- Estimated time: 0.5 days per video
Phase 2 — Screen Recording & Assets
- Record Sniffer app at 4K resolution with clean demo data
- Capture all UI flows: Zendesk panel, Jira ticket, Cursor IDE with MCP
- Record character shots if needed (clean background, professional framing)
- Prepare all typography assets: gradient text animations, logo treatment
- Estimated time: 0.5 days per video
Phase 3 — Edit & Motion
- Assemble timeline: hook / flash cut / demo / CTA structure
- Animate gradient typography for feature highlights
- Color grade: deep contrast for dark scenes, clean bright for light scenes
- Sound design: subtle terminal sounds for hook, music shift for transition
- Estimated time: 1 day per video
Phase 4 — Delivery & Distribution
- Export in 3 formats: 16:9, 9:16, 1:1 — all from the same edit
- Provide subtitle/caption file (.srt) for accessibility and LinkedIn performance
- Thumbnail design for YouTube/website: dark background + gradient title
- Brief usage guide: where to post, what caption to use per platform
- Estimated time: 0.5 days per video
Tools & Software
Video Editing
Adobe Premiere Pro · DaVinci Resolve for color grading
Motion Graphics
After Effects · Animated gradient typography system
Screen Recording
Loom / OBS at 4K · Clean Sniffer app demo environment
Sound
Epidemic Sound / Artlist · Custom UI sound design
Review & Approval
Frame.io · Timestamped comments for fast feedback
Assets
Figma for typography design · Google Fonts (Syne)
Suggested Release Order
EP 02 is highest priority — MCP is Sniffer's strongest differentiator right now. EP 07 closes the series as a hero/overview video for the homepage.