Here is the comprehensive breakdown of all the golden nuggets, key insights, workflow methodologies, "mood board" (brand definition) components, and **every single prompt** used in the video to build an entire brand campaign from scratch. ### 🌟 Golden Nuggets & Key Insights * **The Power of Model Context Protocol (MCP)**: MCP is a game-changer. It allows a text-based LLM (like Claude) to securely talk to external tools (like Higgsfield for images/videos, or web searchers for research) without you having to manually leave the chat or switch tabs. * **The "Always Allow" Trick**: When setting up the Higgsfield connector in Claude, change the permissions to **"Always Allow."** If you don't do this, you will have to manually click to approve every single image and video generation request, completely ruining the automation. * **Research is the Secret Sauce**: The most crucial (and often skipped) step is real-world market research. Duncan uses Claude to scrape Reddit, TikTok, and Meta Ads to find out what people are *actually* complaining about. For the lens cleaner, he found that buyers were terrified of ruining their expensive anti-reflective coatings—an insight that became the central pillar of the marketing campaign ("Coating Safe"). * **Locking in the "Master Asset"**: Don't just generate a bunch of random images. Generate **one Master Packaging Image** first. Have Claude run a "vision analysis" on its own work to verify it looks correct. Once verified, instruct Claude to *reference the Job ID* of that specific master image for every subsequent image and video. This enforces strict visual consistency. * **Use the Right Model for the Job**: Duncan specifically switches from Claude 3.5 Sonnet to an "Opus 4.8" model (note: he likely means Claude 3 Opus or a specific local alias, as Opus is Anthropic's most capable reasoning model). He notes that complex, multi-step marketing tasks require a higher-tier reasoning model, not just a fast one. * **Cost-Saving Video Hack**: AI video generation (like Seedance 2.0) can get expensive. Inside the MCP settings, you can instruct the tool to generate videos at 720p or 480p instead of 1080p. This cuts your API token/credit costs in half while you are testing and prototyping. * **Folder Scoping**: Before starting, create a dedicated folder on your desktop (e.g., "Higgsfield") and drop your raw, unedited product photo in there. Open Claude Code *within* that directory so it has direct access to read your photo and save all the generated assets locally. --- ### 🎨 The "Mood Board" & Brand System Construction Instead of manually putting together a mood board, Duncan uses a **"Brand Definition" prompt** to force the AI to create a mathematical, locked-in brand system that it can reference later. The AI generates: * **Brand Voice Rules**: E.g., Clean, technical, modern-masculine, no-nonsense. * **A Strict 6-Color Hex Palette**: Primary, Secondary, Tertiary, Dark Typography Accent, Single Metallic, and Contrast (e.g., Electric Blue `#2E5FFF`, Titanium Silver `#C7CDD4`). * **Typography Hierarchy**: Specifying exact Google fonts (like Space Grotesk and Inter) and their weights for Wordmarks, Headlines, Displays, and Body text. * **A 12-Week Theme Map**: A content calendar framework that dictates the "theme" of the hero image for the next 12 weeks of social posting. --- ### 💻 ALL PROMPTS USED IN THE VIDEO *Note: Duncan reveals that this is a 12-prompt chain. Here are the exact prompts shown in the video for you to copy, paste, and adapt for your own products.* #### Prompt 1: The Product Brief (Vision & Setup) *First, drop your raw product photo into the folder and tell Claude you have done so.* **Your input message:** "You already have access to an image photo inside of the folder." **The Prompt:** ```text You are a brand strategist. I'm giving you a product photo and a category description. Fill out the brief below based on what you observe in the image and what you know about this category. Do not invent features. Only state what you can visually confirm or reasonably infer from a standard product of this type. Flag every inferred field with [INFERRED]. [ATTACH PRODUCT PHOTO] Category: [e.g. precision lens cleaning spray for eyeglasses] Fill in every field: Brand Brief Product name: [Derive from packaging if visible, otherwise suggest one] One-line pitch: [A pocket-sized... What it does, who it is for, in one sentence] Product category: [Refine the category label] Brand promise: [Unsolved problem -> inferred hypothesis -> research will confirm in the next prompt] Five proof points: [What you can confirm or reasonably claim for this product type] Brand color (primary identity): [Extract from packaging] Brand mood: [Infer from packaging design, color, and style] Audience: [Infer from category and packaging aesthetic] Cultural reference brand: [Suggest the brand whose cultural strategy fits this best and why] Output the brief cleanly with every field filled. Flag anything inferred. ``` #### Prompt 2: Market Intelligence & Research ```text Using the product brief you just generated, run market research to validate and sharpen it with real evidence. Run the following in parallel: 1. Search TikTok for [product category] + "problem" and [product category] + "review" - sort by likes, 90-day window, 10 only 2. Search Reddit and web forums for the single biggest unsolved complaint in this category 3. Search Meta Ad Library for top active competitor ads sorted by impressions Then deliver: - The single unsolved problem worth attacking - one sentence - Three pieces of cited evidence for that problem (links or sources) - Top 3 competitor positioning angles currently running in paid media - Any proof points from the brief that research does not support - flag for removal - Any stronger proof points research revealed that should replace them Output as a clean research summary with all citations included. ``` #### Prompt 3: Brand Definition (Locking the "Mood Board") ```text Using the product brief and the research summary you generated in this session, lock the brand definition. Deliver clearly labeled: 1. Brand name (final) 2. Positioning statement - one sentence formatted as: "For [audience] who [problem], [Brand] is the [category] that [key differentiator]." 3. Primary tagline (functional) 4. Secondary tagline (emotional) 5. Community line 6. Brand voice rules - one paragraph: words we use, words we never use, casing rules, punctuation rules, tone, what this brand sounds like in a text message 7. 6-color palette in hex: - Primary - Secondary - Tertiary background - Dark typography accent - Single metallic - Contrast 8. Typography hierarchy - font name and weight for each level: - Wordmark, Display, Headline, Body, Caption 9. 12-week theme map - name 3-4 word theme names per week in launch sequence Output all 9 sections. The theme map will drive hero image generation and the full content calendar in later steps. ``` #### Prompt 4: The Packaging Master (The Reference Asset) *Note: Include the phrase "using Higgsfield" to explicitly trigger the MCP.* ```text Using go-banana gpt2 . Using the product brief and brand definition you generated in this session, lock the master packaging image. This image will be the visual reference for every downstream asset. Do not generate anything else until it is verified. Step 1 - Generate a single master packaging image using a photoreal model (nano_banana_2 or equivalent). The prompt must specify all of the following: - Form factor and dimensions - Body color in hex (from the brand palette) - Cap color and joint detail (ring, seam, or magnet) - Surface finish: matte / satin / glossy - Wordmark text, font weight, and position on the body - Base treatment - Any glyph or icon: its design and position - Lighting/setup aesthetic - Specific photographer references (e.g. Carl Kleiner x Aaron Tilley x Hugh Kretschmer) Step 2 - Run vision analysis on the rendered image and verify: - Wordmark spelling is correct - Colors match the brand palette hex values - Proportions look production-ready - Nothing looks distorted or off-brand Step 3 - Output: - The image - The master image URL - The Job ID - A pass/fail verdict on visual verification - If fail: what needs correcting and a re-rolled image Do not proceed until the master passes visual verification. ``` #### Prompt 5: 10 Brand-Kit Images ```text Using the brand definition and the master packaging image you generated in this session, produce the 10 brand-kit images below. Reference the master packaging job ID in every generation to enforce visual consistency. Generate all 10 in parallel. Apply the brand color palette and the photographer/lighting aesthetic from the packaging master to every image. 01 - Packshot (1:1): clean centered D2C hero, white or brand-color background 02 - Three-variant flat-lay (4:5): product family shot showing range 03 - Product close-up with human element (4:5): hand, eye, or skin detail 04 - Billboard hero with copy lockup (16:9): primary tagline overlaid 05 - Reels cover with native typography (9:16): scroll-stop vertical format 06 - Surreal floating product, no copy (4:5): editorial hero, nothing anchored 07 - Merch flat-lay (1:1): product alongside branded supporting objects 08 - TV trix key art with tagline (16:9): three-product lineup 09 - Open carton / unboxing flat-lay (1:1): packaging element 10 - Variant + color system chart (1:1): visual reference card Output: Image URL and Job ID for each. Label them 01 through 10. ``` #### Prompt 6: 5 Master Videos (Using Seedance 2.0 via runwayml) ```text Using the brand definition, the master packaging image, and the research summary you generated in this session, produce five 10-second master videos. Each video is built from 3 x 10-second shots stitched via ffmpeg hard-cut concat. Use Seedance 2.0. Reference the master packaging job ID in every shot. Videos to produce: V1 - UGC pain reveal (9:16): shot 1 the problem in real life, shot 2 discovery, shot 3 result V2 - Cinematic flagship (16:9): three shots each proving one of the top proof points V3 - ASMR unboxing (9:16): carton open, product reveal, variant display V4 - POV demo (9:16): setup, live demo or proof test, satisfied reaction V5 - Surreal product hero (16:9): float, macro detail, pull-back resolve Production rules: - Seedance 2.0: 10 seconds per shot maximum, 4-job concurrency ceiling - Submit in batches of 4, poll to terminal before starting the next batch - No whip pans, no cuts within a shot, soft 1-2% handheld drift only - If a shot is rejected for NSFW, rewrite without trigger words and resubmit once only - All shots share the brand color-grade After all 15 shots are confirmed: FFmpeg concat with stream copy (-c copy) for each master, then re-encode at 1080p, 16mbps, AVC H264. Output: Job IDs and URLs for all 15 individual shots + 5 stitched master video URLs. ``` ### 📈 Post-Asset Generation Steps (Mentioned at the end) Though he didn't show the full prompt texts for these in action, he explains that the final prompts in the 12-prompt sequence instruct Claude to take all of the above data and generate: 1. **5 Weekly Reels** (Splicing the videos generated into vertical content). 2. **A 12-Week Content Calendar** (Mapping the themes to actual post text and schedules). 3. **Paid Media Budget** (Telling Claude to act as a media buyer to allocate ad spend across platforms). 4. **Success Targets** (Defining KPIs, repeat purchase rates, and CPA goals). 5. **A Master PDF** (Compiling the brand book, research, calendar, budgets, and all image/video asset URLs into one downloadable, formatted document for the team).