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How America's beloved tea brand Harney & Sons runs agentic influencer campaigns and gets 34% reply with messages like "Thanks for taking the time to really understand who I am and what I'm about! This sounds like the beginning of a great relationship." Harney & Sons achieved what most marketers think is impossible: truly personalized influencer outreach that feels genuinely human - entirely executed by AI agents from aigencia that coordinate with Collabs.io. Forget spray-and-pray templates with "We love your content!" that influencers ignore. This is a complete paradigm shift: 1. Semantic Vibe Matching: First, a brand research agent analyzes Harney's brand to capture their essence. Then the the matchmaker agent uses advanced vector embeddings to transform both brand identity AND creator content into mathematical fingerprints. This allows for deep matching based on shared values, aesthetic styles, and audience compatibility, FAR beyond superficial keyword matching. 2. Hyper-Personalization: "Your recent post about the dreamy homemade cinnamon rolls caught our attention..." The matchmaker agent studies 25 recent Instagram posts from each creator and references specific content that aligns with brand values. 3. End-To-End Automation: When creators say yes (and 34% do), the system automatically ships products through Shopify, tracks delivery, and monitors campaign deliverables. The proof is in creator responses like: "Thanks for taking the time to really understand who I am and what I'm about! This sounds like the beginning of a great relationship" The marketing director himself confirms it: "The caliber of influencers and the impressive matching process have exceeded my expectations. aigencia has helped us scale our UGC campaign efforts without sacrificing quality." - Emeric Harney, Marketing Director This isn't just finding people with large followings. It's creating genuine connections at scale through intelligent orchestration of AI agents that truly understand a brand's essence. The future of influencer marketing isn't human marketers managing spreadsheets of creators and templated emails. It's AI agents running millions of personalized conversations that feel authentic because they ARE authentic, based on true content alignment. Detailed article (link in comments) breaking down how this works. --- DM me to implement agentic influencer campaigns for your brand with aigencia Subscribe to my agenticbrand.ai newsletter to learn more about building AI-native brands for the agent economy.

Agentic CRO via MCP. AI Agent rewrites landing page after analyzing thousands of session recordings, clicks, scrolls, and inspecting the code. Conversion rate optimization is traditionally a slog. Watch session recordings. Stare at heatmaps. Interpret drop-offs. Then try to guess what might work. This flips that. The CRO agent analyzes thousands of sessions for you and returns with diagnoses and redesigns. It's like having a CRO analyst, UX researcher, and front-end dev on your team, working 24/7. Watch my demo as I show how I built this conversion rate optimization agent that analyzes thousands of sessions for you and returns with diagnoses and redesigns. Through the Model Context Protocol (MCP) server I built, I connected Claude to the Hotjar behavioral data of a brand that gets 50K daily sessions linked to an AWS S3 + Athena pipeline for real-time querying of the session data. Then I asked Claude: "Can you review the past 30 days of user behavior and tell me how to improve this landing page?" And it did. - Pulled a live screenshot of the page - Queried AWS Athena for behavioral events - Analyzed scroll drop-offs and short session durations - Connected those insights with page layout and code - Suggested specific, UX-aware fixes like floating CTAs, reordering content, and mobile optimizations Then 𝐑𝐄𝐖𝐑𝐎𝐓𝐄 the landing page code for A/B testing. This isn't prompt engineering. It's a fully agentic system around the LLM: autonomous querying, visual inspection, contextual reasoning, and code generation. Every step grounded in real data. No more guesswork, no more hours of watching screen recordings. You get a sharper, automated, actionable feedback loop that improves conversion every day. If you're spending money on paid traffic and tired of vague analytics, this agentic CRO engine actually moves the needle. Detailed article link in comments. --- DM me to implement this agentic CRO setup for your brand with a.gentic Subscribe to my agenticbrand.ai newsletter to learn more about building AI-native brands for the agent economy.

Agentic commerce via MCP. Personalized shopping in Claude all the way to checkout. Will people shop like this in the future? I just demoed something game-changing: using Model Context Protocol (MCP) to transform AI shopping experiences from "I don't have current product information" to complete personalized shopping journeys. OpenAI announced support for Anthropic's MCP last week. This will now become the industry standard for agentic commerce. It's like a USB-C port connecting brands directly to AI assistants. For my demo I vectorized my favorite surf-lifestyle brand Finisterre's products and set up an MCP server that talks to it. In my demo: --- - Regular Claude: Clueless about product details - MCP-enabled Claude: Instantly accessed Finisterre's real-time product database - Recommended perfect surf gear/clothing for Rhode Island weather conditions - Created a complete checkout cart with Stripe integration The difference is dramatic: MCP+RAG enables AI to understand your specific needs, pull real-time inventory data, make genuinely personalized recommendations, and complete transactions without leaving the conversation. Brands that implement MCP servers will crush their competition in the coming wave of AI-driven commerce. Those who move first will own the new AI shelf space - potentially more valuable than traditional SEO or paid advertising. Watch the full demo (links in comments) to see how it works. --- DM me to discuss implementing MCP for your brand with a.gentic. Subscribe to my agenticbrand.ai newsletter to learn more about building AI-native brands for the agent economy.

10 AI agents working together to create a video ad in 6 minutes and 33 seconds. Watch them at work. DM for access. Agentic Ad Making Part 3: Video Assembly Aigents (links in comments) This is the final link in aigencia’s automated ad creation pipeline that transforms storyboards into fully finished, deployment-ready video ads. In addition to the 5 aigents described in Part 1 and Part 2: 𝐕𝐢𝐝𝐞𝐨 𝐂𝐨𝐦𝐛𝐢𝐧𝐞𝐫 𝐀𝐢𝐠𝐞𝐧𝐭: Stitch matched scenes into one seamless video, optimizing for consistent quality and smooth transitions. 𝐕𝐨𝐢𝐜𝐞𝐨𝐯𝐞𝐫 𝐀𝐢𝐠𝐞𝐧𝐭: Automatically generate emotionally-rich, natural voiceovers perfectly timed for each scene. 𝐕𝐨𝐢𝐜𝐞𝐨𝐯𝐞𝐫 𝐎𝐯𝐞𝐫𝐥𝐚𝐲 𝐀𝐢𝐠𝐞𝐧𝐭: Expertly synchronize voiceovers with visuals, ensuring professional audio balance. 𝐂𝐚𝐩𝐭𝐢𝐨𝐧 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐨𝐫 𝐀𝐢𝐠𝐞𝐧𝐭: Produce precise, readable captions synchronized to voiceovers. 𝐂𝐚𝐩𝐭𝐢𝐨𝐧 𝐎𝐯𝐞𝐫𝐥𝐚𝐲 𝐀𝐢𝐠𝐞𝐧𝐭: Burn polished, optimized captions directly into the final video. These specialized AI agents replace traditional video editing roles, performing tasks that normally take weeks—in minutes. The secret sauce: a sophisticated API orchestration layer that seamlessly manages the entire workflow from storyboard to delivery. - Speed: From weeks to minutes - Cost: Dramatic reduction by automating specialized roles - Iteration: Quickly test multiple ad versions to optimize performance - Quality: Consistent, professional results every time Next up on our Agentic Brand journey I'll explore Anthropic's MCP Server standard with a demo and how this can help brands communicate directly with LLMs and AI agents. ----- Subscribe to my agenticbrand.ai newsletter to learn more on building an AI-native brand for the agent economy. DM for access to the Ad Maker Aigents, as well as Scene Prep Aigent and aigencia's fully autonomous influencer campaign aigents.

Agentic Ad Making Part 2: Storyboard Aigents. Performs hundreds of hours of work in minutes. Uses hot off the oven OpenAI Agents SDK with multi-agent hand-offs & guardrails. aigencia Storyboard Aigents - an orchestrated multi-agent system that transforms simple ad concepts into complete visual storyboards. 𝐂𝐚𝐦𝐩𝐚𝐢𝐠𝐧 𝐁𝐫𝐢𝐞𝐟 𝐀𝐢𝐠𝐞𝐧𝐭: Turns basic ad description into comprehensive strategy document with audience personas and messaging frameworks based on a detailed brand profile created by aigencia's Brand Insights Aigent. 𝐂𝐫𝐞𝐚𝐭𝐢𝐯𝐞 𝐁𝐫𝐢𝐞𝐟 𝐀𝐢𝐠𝐞𝐧𝐭: Turns campaign brief from the previous aigent into concrete creative direction with visual style, tone, and narrative flow. 𝐒𝐭𝐨𝐫𝐲𝐛𝐨𝐚𝐫𝐝 𝐀𝐢𝐠𝐞𝐧𝐭: Takes creative brief from the previous aigent and maps out every scene with precise visual elements, camera angles, and timing. 𝐒𝐜𝐞𝐧𝐞 𝐂𝐫𝐢𝐭𝐞𝐫𝐢𝐚 𝐄𝐱𝐭𝐫𝐚𝐜𝐭𝐢𝐨𝐧: Converts storyboard scenes into precise search parameters in your brand's vector database to find the perfect visuals. 𝐕𝐢𝐬𝐮𝐚𝐥 𝐀𝐬𝐬𝐞𝐭 𝐌𝐚𝐭𝐜𝐡𝐢𝐧𝐠: Searches your vector database (created by the Scene Prep Aigent from Part 1) to assemble a visual storyboard with actual footage. Perfect harmony between specialized AI agents like a virtual production team working in minutes, not weeks. But the real magic comes from connecting this to your Scene Prep pipeline from Part 1. Links in comments. Coming in Part 3: How to automatically assemble these matched scenes into finished ads ready for deployment. ----- Subscribe to my agenticbrand.ai newsletter to learn more on building an AI-native brand for the agent economy. DM for access to Storyboard Aigent, as well as Scene Prep Aigent and aigencia's fully autonomous influencer campaign aigents.

Agentic Ad Making: Part 1 - Scene Prep Aigent. Raw video is hard for AI to use. Here's how to turn it into searchable, reusable ad assets with aigencia's Scene Prep Aigent. 1. Scene Detection: Automatically finds perfect spots to split your video into scenes. 2. Scene Slicing: Cuts scenes into reusable video clips, like LEGO blocks you can rearrange endlessly. 3. Frame Extraction: Picks key snapshots from each scene, capturing the visual story clearly. 4. AI Vision Analysis: Understands emotions, brand messaging, and visuals—so each clip is richly described. 5. Vector Database: Turns this analysis into mathematical vectors, making your content easily searchable by meaning, not just keywords. No more manual tagging—saving hundreds of hours. And because you own these vectors (stored securely in your own S3 and Pinecone accounts), you maintain total control over your data. I believe this vectorized asset data is important intellectual property for agentic brands. Detailed article link in comments. Want to learn how these prepped scenes are used to automatically create targeted ads? Stay tuned for Part 2. ----- Subscribe to my agenticbrand.ai newsletter to learn more on building an AI-native brand for the agent economy. DM for access to the Scene Prep Aigent as well as aigencia's fully autonomous influencer campaign aigents.

How do agentic brands find high-match influencers the modern way? By leveraging vector similarity in high-dimensional space. Let me explain. DM to jam. Surface-level keyword matching belongs to the past. Companies still using "sustainable" brand tag + "sustainable" in bio = match are missing what makes influencer marketing actually work. The technical breakthrough comes from dense vector embeddings. We use NVIDIA's llama-text-embed-v2 with 1024 dimensions to transform brand essence into mathematical fingerprints that capture semantic relationships. These embeddings go through Pinecone vector database for sub-second retrieval against 250,000+ creator profiles. The query uses cosine similarity to find the closest vectors in this high-dimensional space - effectively identifying semantic twins rather than keyword matches. For brands, the most effective embeddings combine mission statements, core values, audience pain points, and voice/tone characteristics into a unified vector representation with properly weighted components. On the creator side, our system generates embeddings from their last 25 posts rather than static profile information. This temporal analysis captures recent content evolution that traditional matching systems miss entirely. The query complexity gets interesting when implementing proper constraints. We're effectively solving for: "Find me creators with 90%+ content alignment whose followers match my target demographic within a 0.75 similarity threshold." Database architecture matters tremendously. We initially stored embeddings in a different database but hit performance bottlenecks at scale. Moving to Pinecone with optimized indexes reduced matching from 30 seconds to under 500ms. The engineering challenge isn't just technical - it's interpretability. We've built a multi-dimensional scoring system that explains match quality across content alignment, audience fit, values compatibility, and brand safety dimensions with letter grades. Every brand should build their own vector database to prepare for AI agents interacting with their data. The future of marketing is autonomous and mathematically principled - not driven by intuition and keywords. Link in comments for a more comprehensive article I wrote. ----- Subscribe to my agenticbrand.ai newsletter to learn more on building an AI-native brand for the agent economy. DM for access to aigencia's fully autonomous influencer aigents.

Humans will stop visiting websites. Father of UX says to design for agents instead. First step to agentic brand: vectorize. I'll explain. DM to jam. Jakob Nielsen predicts AI agents will replace humans on websites, automating browsing, searching, and decision-making. "Focus on designing for agents, not humans," he warns. This isn't science fiction—63% of websites already received visits from AI agents by early 2025. Need proof this affects real businesses? Hubspot lost 80% of their blog traffic as AI search provided answers without clicks. Yet their CMO Kipp Bodnar in a convo with Kieran Flanagan revealed something fascinating: "Our traffic from LLMs is increasing because now we're not just influencing humans, we're influencing robots." Traditional SEO is dying while AI-optimized content thrives. The question isn't whether this transition happens, but how quickly. The first step to becoming an "agentic brand" is to vectorize your data. Vector databases transform your brand's information into mathematical representations that capture semantic meaning—making it AI-native. Think of it as teaching AI to truly understand your unique value. This way your in-house AI agents as well as external AI agents can interact with your vector database directly. Envision an "agents.json" standard (like robots.txt or sitemap.xml) that instructs AI agents how to interact with your brand. This could point to vector endpoints for products, support, and pricing data. Consider this scenario: a user asks their AI "Find me a sustainable backpack under $150 that will last for years." Non-agentic brands get overlooked as the AI struggles to extract information from their websites. But agentic brands will have their vector endpoints deliver semantically rich data about sustainability certifications and lifetime warranties—making them the top recommendation. The benefits extend beyond sales. Support requests once requiring humans can be handled autonomously when your knowledge base is properly vectorized. Even more exciting: vectorizing your media assets enables AI to generate perfectly branded advertising at a fraction of the cost. Creative production costs can drop 60-80% while output increases tenfold. Don't just survive this transition—thrive in it. Agentic brands will enjoy preferred placement in AI recommendations, more accurate representation, and reduced costs. Link to my full article in comments.

🎙️ Thanks to Bora Celik for featuring resbiotic Founder & CEO Dr. C. Vivek Lal, MD, FAAP on his Brand Architects podcast to discuss the Gut-Lung Axis, entrepreneurship, and so much more. Tune in to hear C. Vivek Lal, MD, FAAP share about... 🫁 The science behind resB Lung Support Probiotic ✅ Navigating biotech entrepreneurship 💊 Bringing scientific rigor to the supplement industry 🎧 Don’t miss out! Listen here: https://lnkd.in/eeKr2mzw Collabs.io #Microbiome #biotech #entrepreneurship #GutLungAxis #resbiotic #gutmicrobiome #guthealth #brandarchitects #podcast Stefany N. Casie Jarman Brittany Zenner Stephenie Samudio Ma. Jessa Pacoma Noah V. Brian Peeters Gregory Bonfilio

AI agents working with each other to run influencer campaigns. Start to finish without human intervention. DM me for invite. What they do right now: - Conduct deep brand research to create a custom brand profile - Use vibe match (AI semantic search) to find likely-match influencers (explainer link in comments) - Analyze influencer content in real time for advanced matching - Select influencers with an 80%+ match and craft ultra-personalized outreach (mentioning relevant influencer posts) - Send outreach emails automatically - Ship products to influencers once they agree to terms - Monitor and confirm posted content Next up: - Contract management - Payment processing This is aigencia. A multi-agent platform by Collabs.io. No humans required—just AI agents running influencer campaigns from start to finish. If you’re interested in trying it for your brand, DM me for early access.