In the Pit with Cody Schneider | Marketing | Growth | Startups

https://www.graphed.com/ - AI data analyst to build dashboard and get insightsAI “agents” have been hyped to death—but very few are truly delivering real-world impact. In this episode, we cut through the vaporware with Christian Wiens, co-founder of Loman, an AI voice agent platform transforming how restaurants handle customer calls, orders, and reservations. Christian shares how Loman went from a two-person idea to serving hundreds of restaurants and hitting $1.5M ARR in record time. We dive into why voice is the most natural, context-rich way for humans to communicate—and how AI agents that do real work (not just answer questions) will change how we interact with businesses forever. You’ll hear how Loman’s restaurant agents integrate directly with POS systems to take orders end-to-end, the surprising reasons Gen Z prefers talking to AI over humans, and why the future of a brand’s “front door” may be an AI personality instead of a website. Christian also breaks down Loman’s explosive growth playbook—from ditching cold email for native social ads, to filming on-location customer stories that convert like crazy. We cover the realities of AI-generated ads, programmatic SEO, and why outcome-driven automation is the only AI worth paying for.What You’ll Learn in This EpisodeWhat really defines an AI agent—and why most products don’t qualifyHow voice-based AI can capture richer customer context than any app or formThe operational pain restaurants face with missed calls and how AI solves itWhy customers don’t care if it’s AI or human—only that it gets the job doneGen Z’s surprising comfort with AI calls (and discomfort with human ones)The two make-or-break factors every AI agent needs to succeedHow to create “native feel” ad creatives that crush on socialWhy hyper-specific vertical integration beats horizontal AI every timeThe massive untapped potential for outbound AI voice (and the legal gray areas)Christian’s vision for a future where AI agents replace websites as the primary customer touchpointChapters00:00 – Intro & The AI Agent Hype vs. Reality 04:18 – What an AI Agent Really Is 09:02 – Why Voice Is the Ultimate Interface 13:47 – The Restaurant Industry’s Missed Call Problem 18:25 – Gen Z’s Comfort with AI Calls 22:58 – Vertical vs. Horizontal AI Strategies 27:41 – Loman’s Explosive Growth Playbook 32:16 – Ads That Feel Native & Convert 37:08 – Outbound AI Voice & Legal Considerations 42:55 – The Future: AI Agents as the New Websites 47:20 – Closing Thoughts & How to Connect with ChristianConnect with Christian Wiens:LinkedIn – https://www.linkedin.com/in/christianwiens/Website – https://www.loman.ai/

https://www.graphed.com/ - AI data analyst to build dashboard and get insightsAI-driven search (AISEO) is opening a new lane for brands in competitive categories. Joe Davies from FATJOE explains why branded mentions (not just links) are increasingly what LLMs use to decide recommendations—and how teams can systematically earn those mentions. We cover tactics like guest blogging at scale, context-seeding your USP across reviews/listicles, building deep product docs to feed LLMs, and using tier-two links to get your “influencer pages” ranking. Early data shows 2–3× higher conversion rates from AI-referred traffic because buyers arrive pre-educated and ready to act.What You’ll LearnWhy AISEO rewards brand mentions and clear USPs more than classic link metrics.How AI-referred traffic converts 2–3× higher than traditional search.A repeatable process to seed your brand in listicles, reviews, and comparisons.How to “context-seed” your USP so LLMs recommend you for the right reason.Why deep help docs / knowledge bases make LLMs more confident recommending you.How to choose targets (DR + real traffic), then lift them with tier-two links.The state of AISEO observability (what to track, what’s still immature).Tactical Playbook (Step-by-Step)Define your USP: the specific “best for ___” angle you want LLMs to repeat.Keyword map long-tail, bottom-funnel queries (e.g., “best X for Y,” “X vs Y,” “X alternatives,” “[product] review”).Prospect targets with credible traffic (DR is fine as a filter, but prioritize verified organic traffic).Commission content: secure guest posts/listicles and full reviews on those sites. Mix formats to look natural.Context-seed your USP in every placement (e.g., “Best for small teams,” “Most features,” “Best value”).Include competitors in listicles/reviews so the page is useful (LLMs prefer balanced sources).Boost with tier-two links (niche edits, syndication) to help these pages rank on pages 1–3.Expand surface area: Reddit answers, YouTube/tutorial mentions, and social chatter to reinforce brand salience.On-site foundation: build exhaustive docs—features, integrations, FAQs, facts sections—so LLMs can learn you deeply.Measure pragmatically: track referral traffic from AI surfaces and downstream conversions; current “AI visibility” tools are early.Resources & MentionsChatGPT Path (shows the searches/sources ChatGPT runs under the hood): https://chromewebstore.google.com/detail/chatgpt-path/kiopibcjdnlpamdcdcnphaajccobkbanFATJOE — Brand Mentions Service: http://fatjoe.com/brand-mentionsFATJOE: https://fatjoe.com/Key TakeawaysAISEO is early but growing fast and already drives higher-intent traffic.Focus on being mentioned credibly across the open web; LLMs synthesize those signals.Listicles + reviews on high-trust, real-traffic sites are the current highest-leverage assets.Your docs are marketing now—LLMs read them and recommend accordingly.Don’t abandon SEO; it remains the foundation that AI systems lean on.Chapters00:00 Cold open: AISEO’s opportunity & why mentions matter03:45 Data: AI referrals converting 2–3× vs. classic SEO07:50 Who should prioritize AISEO (and who can wait)10:30 Tactics: listicles, reviews, and “context-seeding” your USP15:45 Tools & workflows; extension that reveals ChatGPT’s queries19:45 Content ops: human vs. AI writing, plans, and clustering22:30 Build deep product docs to feed LLM understanding26:10 Ranking the influencer pages + tier-two links33:00 Observability today: what’s useful, what isn’t yet36:50 The next 5–10 years: AI + SEO, not AI vs. SEOGuestJoe DaviesX: https://x.com/fatjoedaviesLinkedIn: https://es.linkedin.com/in/joe-davies-seoWebsite: https://fatjoe.com/

https://www.graphed.com/ - AI data analyst to build dashboard and get insightsUnlock the practical side of vibe coding and AI‑powered marketing automations with host Cody Schneider and guest CJ Zafir (CodeGuide.dev). If you’ve been flooded with posts about no‑code app builders but still wonder how people actually ship working products (and use them to drive revenue), this conversation is your blueprint.CJ breaks down:What “vibe coding” really means – from sophisticated AI‑assisted development in Cursor or Windsurf to chilled browser‑based tools like Replit, Bolt, V0, and Lovable.How to think like an AI‑native builder – using ChatGPT voice, Grok, and Perplexity to research, brainstorm, and up‑level your technical vocabulary.Writing a rock‑solid PRD that keeps LLMs from hallucinating and speeds up delivery.The best tool stack for different stages – quick MVPs, polished UIs, full‑stack production apps, and self‑hosted automations with N8N.Real‑world marketing automations – auto‑generating viral social content, indexing SEO pages, and replacing repetitive “social‑media‑manager” tasks.Idea‑validation playbook – from domain search to Google Trends, plus why you should build the “obvious” products competitors already prove people pay for.You’ll leave with concrete tactics for:Scoping and documenting an app idea in minutes.Choosing the right AI coding tool for your skill level.Automating content‑creation and distribution loops.Turning small internal scripts into sellable SaaS.Timestamps(00:00) - Why vibe coding & AI‑marketing are everywhere (00:32) - Meet CJ Zafir & the origin of CodeGuide.dev (01:15) - Classic mistakes non‑technical builders make (01:27) - Sponsor break – Talent Fiber (03:00) - “Sophisticated” vs “chilled” vibe coding explained (04:00) - 2024: English becomes the biggest coding language (06:10) - Becoming AI‑native with ChatGPT voice, Grok & Perplexity (10:30) - How CodeGuide.dev was born from a 37‑prompt automation (14:00) - Tight PRDs: the antidote to LLM hallucinations (18:00) - Tool ratings: Cursor, Windsurf, Replit, Bolt, V0 & Lovable (23:30) - Real‑world marketing automations & agent workflows (25:50) - Why the “social‑media manager” role may disappear (28:00) - N8N, JSON & self‑hosting options (Render, Cloudflare, etc.) (35:50) - Idea‑validation playbook: domains, trends & data‑backed bets (42:20) - Final advice: build for today’s pain, not tomorrow’s hype SponsorThis episode is brought to you by Talent Fiber – your outsourced HR partner for sourcing and retaining top offshore developers. Skip the endless interviews and hire pre‑vetted engineers with benefits, progress tracking, and culture support baked in. Visit TalentFiber.com to scale your dev team today.Connect with Our GuestX (Twitter): https://x.com/cjzafirCodeGuide.dev: https://www.codeguide.dev/Connect with Your HostX (Twitter): https://twitter.com/codyschneiderxxLinkedIn: https://www.linkedin.com/in/codyxschneiderInstagram: https://www.instagram.com/codyschneiderxYouTube: https://www.youtube.com/@codyschneiderx

https://www.graphed.com/ - AI data analyst to build dashboard and get insightsIn this episode, Adam Silverman — co-founder & CEO of Agent Ops — dives deep into what “AI agents” actually are, why observability matters, and the very real marketing & growth automations companies are shipping today. From social-listening bots that draft Reddit replies to multi-agent pipelines that rebalance seven-figure ad budgets in real time, Adam lays out a practical playbook for founders, heads of growth, and non-technical operators who want to move from hype to hands-on results.Guest socials• LinkedIn: https://www.linkedin.com/in/adamsil• 𝕏 / Twitter: https://x.com/AtomSilverman• Company: https://agentops.aiTimestamps00:00 — Defining “agents”: reasoning-powered automations, not AGI00:54 — Introducing Adam & the 50+ internal agents his team uses daily03:32 — “Vibe marketing” and why every employee will soon have an AI assistant05:18 — Live example: an inbound-lead-scoring agent that books calls automatically08:11 — Metric shift: revenue / agent & revenue / token10:45 — Three-point filter for agent ROI: expensive, repeatable, low-risk tasks12:56 — Social-listening agents for Reddit, X & forums (human-in-the-loop posting)16:14 — OrcaBase + TripleWhale: agentic ad-spend rebalancing for e-com21:29 — WhisperFlow → Claude to generate entire email sequences in minutes25:04 — Multi-agent systems & OpenAI Agents SDK (Crew AI, Llama-Index, etc.)40:12 — Tech stack cheat-sheet: AgentQL, BrowserBase, Composio, Anthropic Claude 3, Gemini 1.5 Pro48:07 — Internal hackathons & “minimum viable post” culture for continuous learningKey Points• Observability is table-stakes. Enterprises won’t deploy agents without 99.99 % reliability, so logging, evals & debugging are critical.• Marketing automations that already work:– Social-listening + auto-response (Reddit, X “Radar”)– Lead-scoring & routing directly inside Superhuman– Real-time ad-budget re-allocation with TripleWhale’s OrcaBase agents– UGC ad generation at ¢-scale via HeyGen API• Tooling matters: mix-and-match lower-cost LLMs (Gemini/Claude) for chain-of-thought tasks and premium models (GPT-4o) for reasoning or code.• Multi-agent ≠ many prompts. Think specialized “teammates” passing JSON, each with its own LLM, tools & memory.• Hire for AI-nativity, not job titles. A VA fluent in Cursor or WhisperFlow can 10× output overnight.• Run micro-hackathons. One day a month of structured tinkering keeps teams ahead of vendor fluff.Six Practical Plays You Can StealExpensive + Repeatable + Low-Risk AuditMap every workflow; circle anything that costs $$$, repeats weekly, and won’t tank the business if it fails. Start there.Social-Listening AgentRadar (X) or manual Boolean search → Agent drafts replies → human approval → schedule via Buffer/Zapier.Ad-Spend RebalancerPipe TripleWhale or GA4 ROAS data into an agent that shifts budget between Meta, Google & TikTok every 60 min.Outbound “Industry Brief” Generatoryou.com’s Ari agent → 5-page PDF tailored to the prospect’s vertical → attach in first-touch email.Auto-Follow-Up ComposerFathom meeting transcript + Superhuman “Ask AI” → ready-to-send recap with action items.Internal Hackathon Framework• 15 min YouTube tutorial• 45 min build using Gumloop / Lutra AI (no-code)• Demo & share Loom — highest-impact sprint gets pushed to prod.Notable Quotes“We’ve got more agent headcount than human headcount.” — Adam Silverman“Stop talking AGI. Look for tasks that are expensive, repeatable, and low-risk — that’s where agents print money.”“Your revenue per employee metric just became revenue per token.”“Build once, sell twice: every podcast, video or doc should spawn emails, tweets and a downloadable PDF.”2025 Takeaway: The winners won’t be the teams with the biggest models; they’ll be the teams that turn everyday processes into measurable, observable agent workflows — and iterate on them faster than their competitors can finish a slide deck.

https://www.graphed.com/ - AI data analyst to build dashboard and get insightsIn this episode, I chat with Niels Klement (Head of Growth, Perspective) about how “app-feel” mobile funnels—with quiz questions, instant personalization, and 1-second load times—are crushing the old landing-page model. We dig into paid-ads math, creative iteration, and why a single 90-second video can double your business. Perfect for agencies, SaaS founders, and anyone chasing dollar-in → five-dollars-out predictability.Timestamps00:00 – Intro & why most builders fail on mobile01:00 – Perspective’s path to €10 M ARR / 6 000 customers02:30 – From web-design agency to quiz-funnel SaaS06:00 – Interactivity, sunk-cost bias & personalization09:30 – Page-speed math: 5 s vs 1 s loads12:30 – Designing funnels that feel like native apps17:30 – Best-fit customers: agencies & B2B teams22:00 – Paid ads vs organic: guaranteed distribution27:00 – Creative ops: turning 1 ad into 100 variants33:00 – Dog-fooding Perspective to grow Perspective38:00 – AI, “vibe-marketing,” and small-team scale42:00 – Free 14-day trial & closing remarksKey Points (to skim fast)Mobile-first, one-page apps load ~1 s and behave like IG Stories.Quiz/configurator flows lift conversions and qualify leads.1 s load time ≈ 2.5× conversion—that’s a $1 M → $2.5 M funnel without extra spend.Paid ads = best first lever for predictable, measurable growth.Creative flywheel: launch 100 assets, kill 98, scale the 2 that print money.Dog-food advantage: marketing uses Perspective daily, feeding product loops.Notable Quotes“A 90-second ad can change the trajectory of your entire business.” – Niels Klement“Remove the right friction—interactive questions—and conversions jump.” – Niels Klement“Paid traffic is guaranteed distribution. If the math works, keep printing customers.” – Niels KlementQuick Funnel FrameworkCraft an irresistible offer (free trial, template, case study).Map the funnel steps backward from that goal.Add interactive questions to personalize and pre-qualify.Obsess over load speed and mobile UX.Measure, prune, scale—let data pick winners.Guest SocialsLinkedIn – https://www.linkedin.com/in/nielsklement/ Perspective – https://www.perspective.co/

https://www.graphed.com/ - AI data analyst to build dashboard and get insightsIn this episode, I chat with Jonathan, a rapidly rising expert on Twitter known for building and scaling AI-driven marketing automations using tools like n8n and custom API integrations. We explore the practical realities of "vibe marketing" automation beyond hype, revealing how real-world workflows are being constructed today and why true expertise in marketing is essential for effective automation. Listeners will gain insights into automating audience research, creative production, and ad performance analysis at scale, as well as actionable tips for getting started and leveraging AI tools to 10x their output.Timestamps(00:00) – Introduction to Jonathan and Marketing Automation The host introduces Jonathan and sets the stage for a discussion on modern marketing automation tools and why they’re currently so powerful.(02:45) – Jonathan’s Background and Automation Journey Jonathan shares how he got into marketing automation, his paid ads background, and the evolution from manual work to automation.(07:30) – Key Tools and Stack for Automation The host and Jonathan discuss their tech stacks, highlighting n8n, railway.com, and custom front-end interfaces to streamline automation.(12:15) – Top Marketing Automation Workflows Jonathan outlines his most effective workflows: audience research, creative generation, and scaling marketing insights.(18:00) – Audience Research Automation: Reddit Scraping and Analysis A deep dive into using n8n to scrape Reddit, filter and analyze discussions, and extract actionable marketing insights and customer language.(25:40) – Twitter Insights Automation How Jonathan automates scraping Twitter for popular posts, identifying top-performing content and structuring it for ongoing content creation.(31:10) – Creative Production Automation Jonathan explains workflows for bulk generating ad variations using OpenAI’s Image Gen API, including reference image analysis and prompt engineering.(38:20) – Custom Front-End Interfaces for Workflows The pair discuss integrating user-friendly front-end UIs (using Lovable or Bolt) with n8n backend automations for client and team use.(44:50) – Automating Ad Performance Analysis Jonathan describes a flow for pulling and analyzing Facebook Ads data, using sub-agents for performance analysis, deep research, and new ad creation.(51:10) – Video Ad Automation and Future Trends A look at how video ad automation is evolving and the current limitations and opportunities, including upcoming tools like Google Veo 3.(56:40) – Speeding Up Workflow Creation with Perplexity and Claude The host and Jonathan discuss using AI (Perplexity, Claude 4) to generate n8n workflow JSON, streamlining the automation development process.Key PointsExpertise in Marketing is Essential for Automation: To automate marketing workflows effectively, you need a deep understanding of marketing processes themselves. Only then can you define, script, and automate successful campaigns[1].Automating Audience Research Drives Results: Bulk scraping and analyzing platforms like Reddit and Twitter allow marketers to extract pain points, trigger events, and customer language at scale, informing ad copy and creative direction.Creative Volume is Game-Changing: Automation tools like OpenAI’s Image Gen API enable the generation of hundreds of ad variations, feeding algorithms for higher performance and lower costs.Custom Front-Ends Improve Workflow Accessibility: Building user-friendly interfaces (using tools like Lovable or Bolt) for complex n8n automations makes them accessible to non-technical team members and clients.AI Accelerates Workflow Development: Using AI tools like Perplexity and Claude to generate n8n workflow JSON reduces the time and technical skill required to build sophisticated automations.Human-in-the-Loop Remains Critical: While automation handles the heavy lifting, human oversight is still needed for nuanced analysis, curation, and final ad selection.Notable QuotesJonathan: “You have to be an expert at that thing to be able to go and actually build out these automations. But when you do that, you can automate 80% of the work that you previously were doing.”Jonathan: “I literally just tell Claude what I want to build, and then it maps it out for me. And then you kind of have a canvas that is like 60, 70, 80% there depending on the complexity.”Cody: “Your customers are your best advertisers, so taking their exact wording and phrases is for sure going to be an effective marketing strategy a lot of the time.”Actionable Takeaways for Founders, Marketers, and PodcastersStart with a Core Marketing Process: Identify a repeatable marketing workflow you fully understand before attempting to automate it.Invest in Audience Research Automation: Use tools to scrape and analyze discussions on Reddit, Twitter, and other platforms to extract customer pain points and language for your messaging[2].Bulk Generate and Test Creatives: Leverage AI to produce hundreds of ad variations, enabling rapid testing and optimization of creative assets.Automate Performance Analysis: Implement workflows to automatically pull and analyze campaign performance data, allowing you to focus on strategy and execution[8].Simplify Tool Accessibility: Build custom UIs for your automation tools to make them accessible for your entire team, not just engineers.Accelerate Workflow Development: Use AI-powered tools like Perplexity and Claude to generate automation scripts and reduce development time.Brought to you byTalentFiber – Hire top offshore engineers with US experience at half the cost of US hires. - talentfiber.comWhere to the find Guest: https://x.com/vibemarketer_ https://linktr.ee/vibemarketerResources Mentionedhttps://www.youtube.com/@nateherkhttps://www.youtube.com/@Mark_Kashefhttps://www.youtube.com/@AI-GPTWorkshop/videosRapidAPI – Access a wide range of third-party APIs for quick integrations. - rapidapi.comApify – Scrape websites and extract data at scale. - apify.comTwitterAPI.io – Free and affordable Twitter data scraping tool. - twitterapi.io

https://www.graphed.com/ - AI data analyst to build dashboard and get insightsIn this episode, I sit down with Louis Shulman of Orbit Flows Marketing to dive deep into why a warmed email list is the single most valuable asset a brand can own. We explore how consistent, process-driven newsletters can drive thousands of targeted clicks weekly, share real-world examples and metrics, and unpack the exact frameworks, templates, and AI-powered workflows Louis uses to produce hundreds of newsletters a month for some of the world’s fastest-growing companies. Whether you’re resurrecting a dormant list or scaling a six-figure send, you’ll walk away with concrete steps to build, clean, and monetize your newsletter with repeatable, bite-sized automation.About the GuestLouis Shulman Louis leads client success and content strategy at Orbit Flows, where his team of five writers produces over 50 email newsletters per week for a collective audience exceeding one million subscribers. He’s spent years perfecting the playbook for turning long-form expert conversations into high-impact weekly sends that consistently deliver 3,000+ clicks per issue.Key TakeawaysEmail Newsletters as Owned Media: A weekly newsletter is an asset you own and control, unlike social platforms or paid ads.Process Over Perfection: Success comes from simple, repeatable systems (templates, cadence, checklists)—not chasing “perfect” content.Customer Journey Mapping: Structure newsletters around problem-aware, solution-aware, and vendor-aware stages to guide subscribers down your funnel.Bridge of Belief: Craft content that anticipates and answers subscriber objections before they arise—turn objections into subject lines.AI as an Accelerator: Treat AI like a managed teammate—define clear sub-steps and approval checkpoints to get 90% of the work done, then add human polish.List Hygiene & Segmentation: Start conservatively, re-engage dormant subscribers with win-back sequences, and prune non-openers after five sends to protect deliverability.Lead Magnets & Growth: Educational email courses and targeted downloadable assets (e.g., “5 Day Course on Accounting Pitfalls”) drive higher opt-in rates than generic “join my newsletter” pitches.ROI in Click Equity: With a 170,000-subscriber list sending twice weekly, 10,000 clicks per send saves upwards of $800,000 in paid LinkedIn ads annually.Episode Highlights00:00 – 01:00 – Why Email Is King: The host frames newsletters as the most valuable, yet overlooked, marketing channel.01:00 – 02:00 – Sponsor Break: Acclaim Podcasting: Full-service agency that builds your weekly content machine (acclaimpodcasting.com).02:00 – 04:00 – Volume & Scale: Louis shares that Orbit Marketing dispatches 50+ newsletters weekly to 1M+ subscribers—and how one weekly send drives ~3,000 clicks.04:00 – 07:00 – Defining “Newsletter”: Establishing clear expectations, consistent format, and landing-page first mindset for newsletter signups.07:00 – 11:00 – Customer Journey & Content Strategy: Reverse-engineer subscriber beliefs at each funnel stage; problem, solution, vendor.11:00 – 15:00 – Objections into Subject Lines: Proactively address subscriber doubts (e.g., “Is TikTok still worth it?”) in your newsletter copy.15:00 – 18:00 – Ideation & Prompts: Three core content buckets—personal stories, business strategies, industry insights—and 100+ ghostwriting prompts for weekly topics.18:00 – 22:00 – Templates & Systems: Pin down a weekly structure with 3–5 sections to eliminate decision fatigue and ensure consistency.22:00 – 26:00 – AI-Powered Workflow: Build “Orbit Flows” with templates, voices, knowledge bases, and spaces—treat AI like a junior teammate with incremental approvals.26:00 – 30:00 – List Building & Hygiene: Start small with new or cold lists, run win-back sequences, remove non-engagers after five weeks to maintain deliverability.30:00 – 34:00 – Lead Magnet Mastery: Email courses and downloadable guides convert far better than generic newsletter invites—package education, not just tips.34:00 – 38:00 – Productizing Internal Tools: How Orbit spun its own AI newsletter engine into the OrbitFlows SaaS platform, with live demos of templates and research pipelines.38:00 – End – Final Advice & Connect: Louis drops his top three rapid-fire tips for B2B founders and shares where to reach him next.Resources & LinksGuest SocialsLinkedIn: https://www.linkedin.com/in/louisshulman/Orbit Marketing: https://www.orbitmarketing.io/X (formerly Twitter): https://x.com/LouisShulman/Brought to you byAcclaim Podcasting: https://acclaimpodcasting.comOrbitFlows (Built by Louis & Team)Product Site: https://orbitflows.com

https://www.graphed.com/ - AI data analyst to build dashboard and get insightsIn this episode, Cody hosts Romain Torres, co-founder of ArcAds, to dive into the next evolution of paid advertising — using AI to generate and test thousands of ad creatives at scale. Romain shares the strategies behind ArcAds’ explosive success and how marketers can now use AI agents, automation, and avatars to unlock hyper-efficiency in ad performance. This episode is a masterclass in modern performance marketing for eCommerce, mobile apps, and agencies alike.Timestamps: 00:00 – Why top e-commerce advertisers generate 1,000s of creatives01:10 – The old UGC content model: $100K for 1,000 ad variations01:57 – ArcAds and AI avatars explained03:00 – Lessons from gaming companies and their ad testing obsession06:30 – How to make ad testing 10x cheaper and easier with AI10:20 – Meta’s only recommendation to big advertisers: more creatives13:10 – Why creative volume is now the biggest growth lever15:00 – Romain’s 6-week creative testing sprint process20:05 – The “Notion board” system for organizing ad experiments25:40 – Automating script generation via Facebook Ad Library + Whisper29:20 – AI’s true strength: copying and remixing top-performing formats35:15 – Real examples: language apps, e-com, and viral ad structures40:05 – Why localization with AI avatars is a game-changer44:40 – Using failure and emotion in ads (gaming tactics for e-com)47:50 – “Ads that don’t feel like ads” – winning creative philosophy49:10 – Final frameworks and where to start with AI adsKey Points: • AI is shifting ad creative from an expensive, human-led process to scalable, high-volume automation — unlocking massive performance gains• Meta’s performance advice is now centered on one thing: creative iteration• ArcAds enables users to generate hundreds of UGC-style video ads using AI avatars, voice synthesis, and automated scripting• Creative success depends on three pillars: strong scripts, tested variations of actors, and good editing• Winning ad strategies rely less on creative instinct and more on statistical volume — test everything, let the data decideCreative Frameworks Discussed:Weekly Iteration LoopOrganize creative ideas in a Notion boardTest 10+ variations per conceptReview weekly results → double down on winnersCommit to a 6-week testing cycle to uncover scalable conceptsAI Agent Automation WorkflowScrape competitors’ Facebook ads using the Ads Library APITranscribe videos with WhisperAnalyze hooks and trends with GPTGenerate new scripts, swap in AI avatars, and produce at scaleBest Performing Ad FormatsUGC-style narration with product demo B-rollSplit-screen “AI tutor” dialogue format for language appsLocalized voiceovers for different geographiesStreet interview simulations using avatars for finance/dating appsGrowth Tactics: • Use AI to localize ad content and reach global markets without extra production• Automate creative inspiration by spying on competitors and remixing their winners• Build feedback loops with performance data to fuel ongoing ad ideation• Don’t try to guess the best creative — let scale + data reveal the winnerNotable Quotes:“You just don’t know which actor is best for your ad until you test it.” – Romain Torres “Meta figured out the targeting. Now you have to figure out the creative.” “AI is bad at being creative — but it’s amazing at copying what works.” “Your edge is not doing one thing well. It’s doing everything at 100x volume.”Guest: https://fr.linkedin.com/in/romain-torres-arcadshttps://x.com/rom1trshttps://www.arcads.ai/