Fast Hours

Anthony Pompliano chooses AI projects around problems he needs solved, friction worth fixing, and builds he enjoys.After investing in 300+ companies, Pomp still builds software because something in his own day annoys him. He joins Drew Brucker and Rory Flynn to explain when an AI idea earns his time, when paying for existing software makes more sense, and why a weekend experiment can be valuable just for the practice. The hosts recognize the habit of turning every free evening into another build (their podcast website gives them away).Anthony Pompliano covers AI project selection, build versus buy decisions, and rapid product iteration. Silvia, ChatGPT, Claude, custom AI models, and Slack support agents supply concrete examples. Personal AI command centers, podcast repurposing, YouTube comment filtering, and creative context connect AI development to everyday work.#AIAgents #AnthonyPompliano #FastHours---⏱️ Fast Hour00:00 Meet Anthony Pompliano02:47 The Personal Problem Behind Silvia AI04:46 The $550,000 AI Bill That Forced a Rethink06:17 Inside Silvia's Custom AI Stack09:56 10 People, Dozens of AI Agents10:48 Toby: AI Support With Human Approval13:23 Competing When Big AI Labs Copy Your Features17:12 Building AI Products People Want to Keep Using21:13 The AI Command Center Pomp Built for Himself22:11 Building With AI Through Fast Iteration23:29 Shipping Speed as an AI Investing Signal25:16 Should You Build It or Keep Paying for Software?26:38 The AI Projects Pomp Makes Time For27:06 Turning Podcast Episodes Into Articles and Clips32:24 Pomp's Late-Night AI Building Habit33:16 Using Multiple AI Agents to Find Opportunities36:28 Protecting Family Time When You Love Building40:06 Why AI Saves Time and Creates More Work40:36 Training an AI to Filter YouTube Comments41:34 How Pomp Spots an AI Idea Worth Building43:12 Spotting Real AI Adoption47:43 When Expertise Gets in the Way of New Ideas48:39 Asking AI What to Do Next50:31 Giving AI the Context to Be More Creative51:19 How AI Changed Pomp's Curiosity and Delegation53:20 The Fast Hours Sign-Off---🔗 Resources/ CONNECT WITH ANTHONY POMPLIANO / Website: https://www.anthonypompliano.com/Silvia: https://www.cfosilvia.com/X: https://x.com/APomplianoLinkedIn: / anthonypomplianoInstagram: / pompglobalThe Pomp Letter: https://pomp.substack.com/Anthony’s books: https://www.anthonypompliano.com/books/ THE POMP PODCAST /Website: https://www.pomppodcast.com/YouTube: / anthonypomplianoSpotify: https://open.spotify.com/show/0bn8XQH...Apple Podcasts: https://podcasts.apple.com/us/podcast...---FOLLOW FAST HOURSWebsite: https://fasthourspodcast.com/Spotify: https://open.spotify.com/show/0yAw8VH...Apple Podcasts: https://podcasts.apple.com/us/podcast...

Creative teams get to one click by building and testing Figma Weave workflows, then packaging repeat work into shared tools.

Figma Weave Creative Workflow Advocate Ron Baranov shows how the hours behind a one-click AI workflow become a tool the whole team can run. Drew Brucker and Rory Flynn follow the builds, from looping animations to locked illustration styles, and Rory discovers version history after explaining his backup routine. (Excellent timing.)

[Discussed in this episode]

Figma Weave connects large language models (LLMs), image generation, and video generation into repeatable creative workflows. Ron Baranov covers automated prompt writing, looping animations, locked brand styles, character contact sheets, and shared team tools. Figma integration, Model Context Protocol (MCP), version history, and Gen Effect controls support production workflows and creative decisions.

#FigmaWeave #AIWorkflows #CreativeAutomation #FastHours

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⏱️ Fast Hour

00:00 Opening and Ron Baranov's Creative Background

08:07 What a Creative Workflow Advocate Does

12:39 Helping Enterprise Teams Build AI Workflows

17:11 The LLM Gap in Creative Workflows

24:35 Learn Figma Weave by Taking Workflows Apart

27:24 One Prompt, Six Image Models

32:04 LLMs Write Camera-Angle Prompts

34:44 Which AI Models Can Enterprise Teams Use?

38:30 Teaching AI Without Overwhelming a Team

43:24 Automating Loop Animations

45:35 Turning a Workflow Into a Tool the Team Can Run

47:27 A Brand Illustration Tool With One Input

49:35 Connecting Weave Assets to Figma Frames

55:17 Running Weave Tools Through Claude and MCP

57:30 What It Takes to Get to One Click

1:02:01 Using Custom Weave Tools Inside Figma

1:04:47 Building Characters From Visual Contact Sheets

1:07:28 Version History Surprises Rory

1:11:36 Keeping Creative Choices in the Workflow

1:14:18 Inside the Workflow Advocate Team

1:18:45 Creating Custom Effects With Gen Effect

1:23:17 Getting a Whole Creative Team Using AI

1:31:28 The Creative Skills Ron Would Learn Next

1:34:49 Behind the Figma Config Presentations

1:39:33 Figma Weave Office Hours and Community

1:40:13 Handlers, Fixers, and the Closing Shout-Outs

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✱ Resources from the episode

/ Workflows & Tools /

Ron's create character workflow: https://app.weavy.ai/flow/ChkZWxAE74RbiTn20eIjbc

Intro to Figma Weave workflow: https://app.weavy.ai/flow/2ACz7n2ycDm6jxbh0D0jf1

Gen Effect workflow: https://app.weavy.ai/flow/Y5IBkzwFyc0zeYioDmGB6K

Extract a product from image tool: https://app.weavy.ai/flow/YI6F6lHjCn7K6T6HZg1bjg

/ Tutorials /

Weave first steps: https://www.youtube.com/watch?v=1pwXwbtqjBQ&t=1426s

Figma Weave youtube channel: https://www.youtube.com/channel/UCWqrnJYussMFHy5_AxwK5gg

/ Ron's Social /

Linkedin: https://www.linkedin.com/in/ron-baranov-b31740100/

Instagram: https://www.instagram.com/ronbaranov/

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⚡️ Explore all episodes, transcripts, tools, and guests: https://fasthourspodcast.com/

Drew Brucker and Rory Flynn have officially reached the point where their AI agents are doing more work than they can keep track of.Six months ago, they were discussing who they'd need to hire to scale Fast Hours. Now they've built an interconnected system handling everything from podcast clips and thumbnails to website publishing, creative production, and client workflows.Naturally, that freed up enough time for Drew to spend an unreasonable number of hours building a squirrel video game with his dad, while Rory assembled an army of AI agents inspired by Lord of the Rings.Somewhere between the squirrels, the robots, and the existential questions about creative work, there's a pretty compelling picture of what happens when AI gives people the ability to execute their ideas.[Discussed in episode]Drew Brucker and Rory Flynn explain AI agents, Claude skills, Model Context Protocol integrations, and reusable creative workflows. Fast Hours production covers Riverside, Cloudflare, YouTube packaging, clip selection, and thumbnails. Creative experiments span Blender, Magnific, Runway, Higgsfield, and Figma. Examples show agent teams, model specialization, automated quality control, and context-driven production.#AIAgents #CreativeAI #AIWorkflows #ContentCreation #FastHours---⏱️ Fast Hour00:00 Fast Hours hits 100K subscribers04:21 Flying cars are getting ridiculous11:26 Cars are becoming software platforms14:40 Why AI is destroying traditional software moats16:09 AI can reverse-engineer entire software products20:32 The competitive advantages that still matter23:11 We built an entire creative team with AI agents25:33 The AI creative explosion30:26 Combining AI, Blender, Excel, and code32:25 The new formula for creating with AI34:37 Building a video game with Claude43:13 Turning curiosity into an AI learning program46:44 A new approach to creative ideation48:41 Building a team of specialized AI agents52:39 Tracking how AI crawlers interact with websites54:51 Using AI skeptics to improve creative work56:47 Our AI-powered podcast production system1:00:51 Cutting thumbnail production from 6 hours to 30 minutes1:02:37 Automating podcast publishing with AI agents1:04:45 Building reusable AI workflows for clients1:07:01 Running entire creative projects with AI agents1:09:49 Creating interactive websites with AI1:12:22 Automated creative testing and quality control1:17:10 Better AI video with virtual camera operators1:18:39 Recreating Fast & Furious scenes with AI and Blender1:21:51 The problem with unlimited creative possibilities1:23:36 Drew shares 12 free Claude skills1:26:18 Rory's Lord of the Rings AI agent army1:29:24 Should AI agents handle your personal life?1:36:03 Midjourney explores MCP integration1:36:55 Apple, Meta, and the future of local AI1:41:38 Remembering Napster, LimeWire, and early computing1:46:43 Final thoughts and shout-outs---🔗 ResourcesDrew's Claude Skills: https://github.com/dcbruck/claude-skillsDrew's Squirrel Game: https://squirrelscramble.com/Fast Hours Podcast Website: https://fasthourspodcast.com

Phil Rivers is using AI to scale his agency by automating approvals, task creation, onboarding, and shared workflows across his team.Drew and Rory spend an embarrassing amount of time obsessing over AI visuals. Phil Rivers shows up with 40 clients, 16 employees, and an entirely different obsession: automating all the boring stuff nobody wants to do.And it turns out the boring stuff might be where the biggest opportunities are hiding.Phil has rebuilt his agency around an AI-powered operating system that handles client approvals, project management, task creation, onboarding, and internal knowledge sharing.His goal? Double the number of clients his existing team can handle without hiring another employee.And he's already built much of the infrastructure to pursue it.Phil Rivers breaks down an AI-powered agency operating system built with Claude Code, Model Context Protocol (MCP), Supabase, GitHub, Slack, Asana, and Figma. Automated client approvals create campaign tasks and deadlines. A Slack agent named Tim drafts Asana tasks with dependencies. Klaviyo data, onboarding automation, permissions, and shared knowledge help teams handle more clients.#AIAutomation #ClaudeCode #AgencyOperations #FastHours

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⏱️ Fast Hour

00:00 Who is Phil Rivers?

08:16 Why rebuild an agency with AI?

11:15 How an email agency first used Midjourney

14:24 How do you adopt AI without slowing down?

24:35 How to build an agency on AI from day one

27:03 How can Asana automate campaign planning?

34:36 Why service keeps clients longer than results

37:30 How do you build client context into AI?

43:20 Who decides what the AI remembers

47:38 How AI unblocks account leads to just serve

49:52 How can teams share AI skills?

54:11 How does one MCP support an entire team?

58:17 Why one-off tasks break agency teams

1:00:13 Meet Tim, the Slack agent that writes tasks

1:05:41 How many clients can AI add with zero new hires

1:09:19 Can AI shorten employee onboarding?

1:14:27 Which AI projects aren't worth building?

1:18:20 How do you keep AI workflows current?

1:19:13 How to prove AI ROI to your boss

1:24:50 How do you secure shared AI infrastructure?

1:30:11 What can Obello automate for brands?

1:34:42 How many clients can the team handle?

1:35:42 How does AI automate client onboarding?

1:38:33 What's Phil's biggest AI operations lesson?

1:41:24 Who should viewers tell about Fast Hours?

Claude Opus feels like Midjourney because it can take minimal direction and produce imaginative visual work.Drew Brucker and Rory Flynn gave Claude Opus room to create, then watched the to-do list get ambitious (their neglected websites finally got some attention). A promo’s visual style carries into animated podcast clips, while a handwriting experiment reshapes Drew’s site.Claude Opus powers motion graphics, podcast clipping, and website builds from creative references. Midjourney supplies the creative comparison and visual references for animation. Riverside Model Context Protocol connects recordings and transcripts. ChatGPT image generation builds animation assets. Magnific and ElevenLabs support sound effects and narration.#ClaudeOpus #Midjourney #MotionDesign #FastHours---⏱️ Fast Hour00:00 What's coming in Fast Hours 85?04:20 Why does context improve creative quality?05:35 Why does Claude Opus 5.5 feel like Midjourney?06:07 One design system, a creative domino effect09:07 We built a custom AI clipping workflow10:01 A blind grader judging clip hooks?13:35 Why does Riverside MCP matter for clipping?14:26 How do reference clips train an AI editor?16:37 How do you build clips around out-of-order hooks?19:32 Podcast clips get branded motion graphics23:52 Motion designers losing their sh*t over AI democratization29:58 How precise are code-based motion graphics edits?32:14 Domain expertise raises the ceiling for AI motion design39:17 Drew let his daughters' handwriting shape his brand website44:52 How do you prompt a cohesive website redesign?49:56 Fast Hours builds a website from its creative DNA52:05 Can transcripts power a searchable website?58:28 Music-reactive web design with a face1:00:20 Code-based animation gets a story to tell1:04:00 How does one image become an animation asset library?1:05:48 How do AI tools add animation and narration?1:11:24 How does ElevenLabs find a voice from a description?1:16:15 How real does a Tavus conversation feel?1:21:41 What will Phil Rivers teach about AI operations?

Opus 5.5 made editable AI video practical: build motion graphics in code, then revise shots, text, and variations without starting over.A cocktail graphic from Rory’s T-shirt became an animation system. Then came four more drinks, a Pokémon battle, podcast promos, and a client-style video. Drew and Rory sound like two people who’ve spent years hearing “one tiny change” and knowing exactly how much work that used to mean.Claude Opus 5.5 turns one cocktail image into a JavaScript or HTML animation system and produces four more recipe videos. Three.js lets Rory block a Pokémon battle and change camera angles for complex scenes. Riverside supplies context for Fast Hours promos. Drew tests a client-style video using a website and company context file.#Opus55 #AIVideo #MotionGraphics #claudeai ---⏱️ Fast Hour00:00 What are Drew and Rory making this week?07:31 Why is AI adding work for project managers?9:29 Why most companies are stuck at basic AI17:36 What is production debt, and why AI took off20:45 Is the $200 AI plan a different product?21:19 What changed with Claude Opus 5.525:04 How one T-shirt image became a motion graphic26:28 Why code-rendered video is infinitely editable28:19 How to turn one render into an animation pipeline31:25 Can Opus 5.5 render a 3D Pokémon battle?36:58 How can Three.js block a complex shot?41:36 How did AI make a Fast Hours promo?42:28 Do you need brand guidelines for this?45:41 Can AI pick a stronger clip hook?47:34 Cutting a promo with no instructions49:18 Why creatives aren't siloed anymore50:39 Watching a sponsor promo render live53:38 What one Opus 5.5 prompt gets you for a B2B SaaS video56:09 The exact prompt behind the one-shot video57:21 Claude Code vs Cowork for motion builds59:17 How do editing and motion graphics combine?1:03:05 How did Drew turn his kids' handwriting into a font?1:10:33 Stop sending AI output without the context1:14:17 How to share a skill that runs anywhere1:18:40 Why trading transcripts beats trading drafts1:20:40 Can you share a Claude project?1:24:18 How to get email discounts, then unsubscribe1:27:44 Where does the episode close?

After 20 years in creative, building Golden Wolf and selling it to Doodles, Ingi Erlingsson went deep on AI to start a new chapter at his company, SYSTMS.Ingi has spent two decades making work for brands including Nike, Adidas, Jordan, Disney, Netflix, Coca-Cola, and Cartoon Network. He built Golden Wolf from the ground up, sold the studio to Doodles, became Doodles’ Chief Content Officer, and now builds custom AI creative systems at SYSTMS.So naturally, Drew and Rory spend half the episode staring at his ComfyUI graphs wondering what the hell is happening.Ingi breaks down how he actually works with AI: custom ComfyUI nodes, LoRAs, agents, model fine-tuning, Wan 2.2, Krea 2, GPT 2.5, After Effects, transition models, and the reusable systems behind his visual work. The conversation also gets into creative control, originality, attention, open source, prompt hunting, and why experienced creatives may have an advantage as AI gets more capable.More importantly, Ingi explains why the goal matters more than the prompt, why rapid iteration changes the creative process, and why giving AI more capability does not automatically mean giving it more creative decisions.#GenerativeAI #ComfyUI #AICreative #creativedirector ---⏱️ Fast Hour00:00 Who is Ingi Erlingsson?02:58 How much creative freedom do top brands give?05:56 How do studios get hired for their style?10:59 What did Doodles teach Ingi about brand work?13:05 How do you turn attention into recognition?18:13 How does Ingi build his signature AI style?26:13 Why does AI make experimentation cheaper?29:01 How do AI and After Effects work together?30:20 Why did Ingi move into ComfyUI?31:42 What hardware does Ingi use for ComfyUI?34:34 What does ComfyUI let you control?38:33 How does Ingi create tracked AI graphics?42:05 How do you build custom ComfyUI nodes?47:11 How does Ingi combine fine-tuned AI models?51:09 How should you train a style LoRA?55:13 What should a video LoRA learn?58:50 How much creative control should you keep?1:01:04 Do AI videos need longer generations?1:07:28 How can open-source AI sustain itself?1:11:31 What did Doodles and Web3 teach him about AI?1:15:01 How does viral content connect to X payouts?1:17:42 AI critics keep moving the goalposts1:19:12 How do bots expose themselves in replies?1:21:48 How does AI search surface a local business?1:24:04 Why do comment-for-workflow posts spread?1:25:42 What should young creatives learn now?1:28:23 What should AI creatives get good at?1:32:15 Do creatives still need to collect prompts?1:32:54 How did Ingi end up working on DuckTales?1:36:12 Who gets the Fast Hours sign-off?---🔗 Links Ingi's X: https://x.com/ingi_erlingssonIngi's Instagram: https://www.instagram.com/ingi.ai/Ingi's company (SYSTMS): https://www.systms.ai/

So, what can OpenAI’s Astra and GPT Image 2.5 actually do?

Drew Brucker and Rory Flynn put OpenAI’s Astra and GPT Image 2.5 models through a golf course build, a vintage typewriter animation, and a round of image edits. Rory’s golf course experiment burns 70% of his weekly allowance. Drew spends three hours getting a typewriter to type. Their gift for turning a quick test into a side project remains undefeated.

The pro-AI half of the show. The other half: a viral AI resignation that looks planned to the minute, Anthropic's 154-page report on how people misused Claude, and GPT Image 2.5 quietly fixing the reasons everyone kept running back to Nano Banana.

This episode covers OpenAI Astra with computer use, two ChatGPT chats collaborating inside one project, Three.js and Blender renders, a fantasy football analytics hub, and Astra running Midjourney with mood boards and style references. GPT Image 2.5 multi-edit comments, sketch input, custom aspect ratios, and template creator. Anthropic's threat report, Moonshot and Kimi distillation, and the viral AI researcher resignation.

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⏱️ Fast Hour

00:00 What’s on Fast Hours this week?

06:35 Why do traumatic moments burn into memory

07:42 What was different before social media

13:48 This week: Astra, GPT Image 2.5, a viral resignation

15:04 Did an AI researcher really resign over ASI

18:40 How to tell what is true in AI news

20:42 Why quitting your AI job can't stop superintelligence

27:01 What do the cited reports allege about Kimi

28:33 What AI misuse examples do the hosts discuss?

34:07 How did Astra build a golf course prototype?

35:35 How did research improve Astra’s first attempt?

36:33 What happened when two AI chats collaborated?

39:29 Why did Rory stop the drainage research?

40:02 How did Drew approach his Blender experiment?

40:52 How did Astra recreate Drew’s typewriter?

43:49 How long does AI-assisted 3D work take?

44:43 How did Drew build a ChatGPT dashboard?

48:32 What happened when Astra explored Midjourney?

53:56 How did mood boards shape Astra’s prompts?

58:49 What improved in GPT Image 2.5?

01:00:24 How do GPT Image 2.5 edit comments work?

01:01:47 How do you request multiple image variations?

01:03:30 How well did GPT Image 2.5 resize ads?

01:07:11 How reusable templates in GPT Image 2.5 can help brands

01:08:37 What’s coming next for Fast Hours?

To run a solo business on AI, build a system of small skills and agents that handle the admin, comms, and ops so your time goes to creating.

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Two founders who swore AI would give them their time back open the hood on what they actually run.

Drew walks through 37 hand-built skills and a 21-layer system for writing in his own voice.

Rory runs his whole business out of Notion and Claude, down to finding an online fax machine for New York State. Neither of them can remember what half their own skills do.

That's kind of the point.

This episode covers building an AI operating system for a one-person business. Topics include Claude skills and agents, a voice system for writing, email and call ingestion, Notion as a CRM, red-teaming contracts and MSAs, predicting LinkedIn reach, Nano Banana prompt engineering, and handling taxes, invoices, and vendor forms. Fable and Astra model releases open the show.

An AI creative director combines design fundamentals, AI fluency, tool selection, and repeatable workflows to produce better creative work.

The boys over at Fast Hour invites a 24-year-old AI creative director to give away her playbook and somehow gets reminded that buying more AI subscriptions does not count as mastery.

Jamey Gannon explains why AI is a skill, what top operators do differently, how Midjourney mood boards become brand systems, and why sometimes the smartest AI move is opening Photoshop.

Jamey Gannon explains how self-taught design, social media, freelancing, and AI fluency shaped her work as an AI creative director. Jamey Gannon demonstrates Midjourney mood boards, SREFs, Midjourney V8.2 Edit, Krea K2, Claude, Figma, Photoshop, Flora, Nano Banana, and the CXO brand system, including when to build custom tools instead of forcing an existing workflow.

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⏱️ Fast Hour

00:00 Who is Jamey Gannon?

06:43 How Jamey taught herself design at 15

12:23 Why Gen Z chases money over job titles

15:35 What first freelance clients look like at 17

18:43 Why social media is a freelance prerequisite

22:16 Freelance math: 20 clients vs one salary

24:13 How her sister makes $5K–$10K/month with AI

27:08 What is an AI creative director?

28:58 What the AI Creative Director course teaches

33:05 Is Krea catching Midjourney?

35:53 The "easy, fast, cheap" AI lie

38:43 Three moments that hooked Jamey on AI

42:23 How to build brand mood boards

46:00 How one SREF cracked the brand style

46:27 Midjourney + Figma: the pixel shader pipeline

49:06 When you should not use AI

51:53 Two ways to use Midjourney mood boards

56:44 What top AI creatives do differently

59:44 Build the tool when the workflow doesn't exist

1:11:28 Midjourney V8.2 Edit: first live tests

1:15:00 What works and what drifts in Midjourney Edit

1:20:06 Midjourney Edit vs Nano Banana: identity lock

1:21:32 Can Midjourney edit text and fonts now?

1:25:23 Can Midjourney's edit model preserve logos and apparel graphics?

1:31:05 Is Midjourney inpainting or regenerating?

1:34:33 The verdict: using Nano Banana less

1:37:34 Where Nano Banana still fits

Brands pay five figures for AI workflows that turn repetitive creative work into reusable systems teams can run at scale.Drew Brucker and Rory Flynn speedrun their way into a useful business model while trying to explain node-based AI without melting anyone’s brain. The opportunity itself is practical. Find expensive, repetitive creative bottlenecks, turn them into reusable workflows, and make the complicated machinery simple enough that an entire team can actually use it.The boys break down Figma Weave, node-based AI workflows, system prompts, batch processing, arrays, Claude, ChatGPT, Gemini, Flux, Nano Banana, Gen Effect, and MCP. SharkNinja and BarkBox examples show how AI workflows support localization, product visualization, asset re-versioning, creative production, team handoff, and scalable content generation.The bigger idea here is that the value comes from encoding the process, creative logic, and standards into a system that can be reused across hundreds of assets without starting from zero.#AIWorkflows #CreativeAutomation #GenerativeAI #FigmaWeave #aiforbusiness ---⏱️ Fast Hour00:00 Cold opener07:22 Why a full Figma Weave episode09:53 How node workflows went mainstream in a year14:10 Why use a node-based AI tool at all?19:02 Inside the Figma Weave AI toolbox20:53 How to sell AI workflows to businesses23:24 Why brands pay five figures for AI workflows24:33 How SharkNinja localizes across 35 markets30:07 Why recurring tasks belong in workflows31:34 Live build: your first AI workflow39:09 What the Gen Effect node can do44:00 How to turn an image into a 3D asset48:46 Scale one fashion image into reusable assets55:18 How to build a batch-processing engine1:03:24 Prompt vs system prompt: what's the difference?1:05:38 Turn a node graph into a reusable tool1:12:17 Engineering an automated listicle video1:14:51 One-shot video vs modular AI production1:24:29 How BarkBox fixed one production bottleneck1:35:20 Where AI workflows create business ROI1:38:20 Why workflows survive every new AI model1:39:29 Paste your workflow into Claude to debug it1:42:57 Use AI workflows as callable functions1:44:28 Publish your workflows into Claude MCP1:46:09 Resources and wrap-up---FIGMA WEAVE 15% OFF: Use code FASTHOURS15 at checkout- 15% off the first purchase of a Figma Weave Starter, Pro, or Team subscription- One-time use per person- Applies to the first month (for monthly plans) OR first year (for annual plans)OUR FREE FIGMA WEAVE WORKFLOWS:

• Drew's Apparel Photoshoot: https://app.weavy.ai/flow/JV8vBtbkOl3vNeiJjAYwxN
• Drew's Product Social Images: https://app.weavy.ai/flow/la8iMD20eGX4eGF91qunVu
• Rory's Listicle: https://app.weavy.ai/flow/SpLj0jsU8hThMmHWtfmT37
• Rory's SD2.5 Prompting: https://app.weavy.ai/flow/MdYt6UJi6ch0MkgxTaCe6r
• Rory's GenEffects Collage: https://app.weavy.ai/flow/sX4dJgsrp9DIrOz5f9ojX1
• Rory's Batch Generator: https://app.weavy.ai/flow/f9OljOQLkPbJ9Q04iN8Uou
• Rory's El Camino Concept: https://app.weavy.ai/flow/BPfVXywHhoymEi3CFxOO3Q

Rourke Sefton-Minns scaled his AI creator business from zero to eight figures in one year by turning audience, education, and creative AI into a business system.Drew and Rory invited Rourke Sefton-Minns on to discuss AI and somehow ended up reverse-engineering a business built on sleep streaming, 420 straight days of posting, multiple failed creator experiments, hitting zero in the bank, and an apparently unhealthy refusal to quit. Rourke breaks down how Gen HQ grew, why brand partnerships now drive hundreds of thousands in monthly revenue, why learning AI tools is often the least important part of getting paid, and why the best move for aspiring AI creatives may be finding the client before figuring out every last detail.Rourke Sefton-Minns explains Gen HQ, AI creator businesses, brand partnerships, LinkedIn client acquisition, spec work, creative partner programs, Meta advertising, Adobe Photoshop Generative Fill, CapCut, Google Gemini, node-based workflows, narrative-loop content, creator burnout, AI careers, and generative AI-powered fandom. He also shares a practical three-month playbook for landing paid AI creative work and his mission to create 100,000 jobs for creatives through AI.---⏱️ Fast Hour00:00 Rourke Sefton-Minns, Gen HQ and 100K jobs02:55 Five social pages before the one that worked05:03 The sleep-streaming business that changed everything09:03 Making $10K a month at 21, then burning out13:04 Betting everything on a six-month ski channel17:11 The persistence lesson behind hitting zero20:50 420 days of posting before the AI pivot28:40 Why Gen Z sees generative AI as the enemy33:01 Why great AI content starts with communication35:10 Inside his vibe-coded content idea system39:19 How long a viral AI video takes to make43:20 Why AI creators burn out46:14 Outsourcing creativity made burnout worse47:27 Why changing formats brought the fun back50:25 How narrative-loop videos create retention52:44 How his 8-figure AI business makes money56:10 Why $40K a month in Meta ads is not enough57:12 The business skills AI creatives overlook01:00:51 The 100,000-jobs North Star01:03:29 How to land your first paying AI client01:07:51 What major AI brands actually want01:12:30 Why boring products can win spec-work clients01:14:09 The four-post strategy for winning brands01:17:47 AI fan content as a new growth engine

Build an AI universe by compounding recognizable characters, consistent worlds, recurring stories, and creative assets instead of starting from zero.⁨

BLVCKL!GHT has spent thousands of hours doing the thing most AI creators accidentally avoid: sticking with one weird idea long enough for it to become an actual universe. Route 47 now spans 28 interconnected shows and characters, four seasons, recurring locations, expanding lore, and even a game in development.

characters → worlds → stories → audience → distribution → monetization

Drew and Rory dig into:

+ how creative consistency becomes leverage

+ why cult audiences can beat virality

+ and why every finished asset can make the next one easier to create.

BLVCKL!GHT breaks down AI world-building, Route 47, original AI IP, character development, consistent AI art styles, audience compounding, and FAST TV distribution. Krea, Magnific, MiniMax H3, Seedance 2.5, Flux 3, Runway, RunComfy, Comfy Cloud, Higgsfield, and Luma Dream Machine frame the AI image and video workflow discussion. AI agents, creator economics, model costs, synthetic media, and creative ownership shape the broader conversation.

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⏱️ Fast Hour

00:00 Who is Blvckl!ght?

04:15 Why did Blvckl!ght change his mind on AI?

09:06 Why does Gen Z hate AI but love his work?

12:15 What shaped Blvckl!ght's visual style?

16:19 What is Route 47?

19:04 How do you build an AI universe?

22:31 How do you stay creatively consistent?

24:35 Which AI tools does Blvckl!ght use?

26:42 Can AI agents make creatives slower?

29:14 Why can a cult audience beat virality?

30:15 How can AI creators monetize on FAST TV?

32:44 How does AI content reach mainstream media?

34:34 How do AI film projects get financed?

38:14 What is “Hi-Fi Slop” and why does it fail?

40:00 How do shorts become a real series?

46:52 Why can obvious AI feel more authentic?

47:57 What is AI's real creative opportunity?

50:14 MiniMax H3 vs Seedance 2.5

53:38 Local AI video vs cloud generation

54:39 How fast can one AI creator produce?

55:55 What is Flux 3?

56:57 How do you control AI generation costs?

59:06 How do unlimited AI generations work?

01:00:29 Brand equity vs capability in AI tools

01:03:26 Why do creators stay loyal to AI tools?

01:10:13 Where should AI creators draw the line?

01:18:26 Should AI make personal decisions?

01:27:01 Where should you start with Route 47?

01:28:45 How can AI check story consistency?

A good AI workflow remembers what worked last time, so you don’t have to rebuild the same process from scratch.Drew Brucker and Rory Flynn attempt to explain how advanced AI workflows actually work, then accidentally expose the mildly concerning machinery behind their own. The useful version of AI goes far beyond isolated prompts. It remembers prior decisions, pulls from real conversations, reuses approved skills, evaluates its own output, and saves the human from rebuilding the same process every Tuesday like a highly caffeinated goldfish.The episode breaks down context files, AI agents, evaluation loops, prompt amplifiers, reusable skills, call transcripts, sales data, and personal knowledge systems. Drew and Rory also examine Seedance 2.5, Midjourney V8.2, emerging AI-assisted 3D workflows, synthetic video detection from NVIDIA, LinkedIn’s AI slop button, and the growing gap between generating faster and building systems that improve with use.---⏱️ Fast Hour00:00 What is next for Fast Hours?05:39 Why criticize AI while using it?08:56 How can AI recover old creative work?10:46 Why did 90s sports design feel better?19:07 What is LinkedIn's AI slop button?22:37 Why did LinkedIn reward lower effort?29:10 How are creators gaming account reach?32:43 Why do large platforms ship so slowly?33:48 What changed in Seedance 2.5?39:57 What is new in Midjourney V8.2?43:48 How does texture improve AI prompting?49:25 Why is Midjourney regaining momentum?50:04 Why is AI entering its 3D moment?58:12 Can people still detect synthetic video?01:01:21 How does NVIDIA detect fake video?01:07:10 Why does speed devalue AI creative work?01:11:13 How do eval loops prevent AI slop?01:13:00 How can calls create original content?01:16:20 Why can't AI automate your opinion?01:21:54 What should AI content systems ingest?01:25:27 How can AI improve sales calls?01:29:41 Why should prompts stop starting at zero?01:31:08 How should AI skills be customized?01:33:29 When should AI workflows be deleted?01:35:12 How do you build an AI skill vault?01:38:23 What is Fast Hours' next milestone?

AI images stop looking generic when creators steer models with real expertise, original references, hand-built assets, and selective craft.

Finn McKenty joins Drew Brucker and Rory Flynn to explain why the fastest route to better AI work may involve drawing by hand, reading the manual, and making fewer things. The three alleged efficiency experts also wander into AI burnout, fake UGC, Higgsfield trust problems, Midjourney’s long game, and the deeply inconvenient possibility that one great image may beat the 1,000 they can generate before lunch.

Topics and tools covered:Midjourney, Weavy, ComfyUI, Claude, Gemini 2.5, GPT Image, Nano Banana, Flux, Krea, Figma, Adobe Photoshop, and Higgsfield anchor the practical discussion. Sketch references, image references, style references, out-of-distribution inputs, material-specific prompting, systems thinking, AI adoption, fake UGC, creator trust, and durable AI-assisted SEO define the core concepts.

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⏱️ Fast Hour

00:00Who is Finn McKenty?

03:13 Why did Finn quit YouTube?

05:30 Do creators need a large audience?

12:05 Which existing skills create an AI edge?

14:26 Does expertise accelerate AI mastery?

16:27 Are creatives too attached to process?

18:17 Why do companies fail to adopt AI?

20:17 Why does advanced AI work cause burnout?

27:33 Where should creators invest brainpower?

29:31 How do creators steer probabilistic AI?

31:27 What made Midjourney click for Finn?

34:00 How did AI produce 10x SEO traffic?

37:44 Why reject polished AI perfection?

38:41 Why does handmade design feel better?

41:06 How should AI and manual craft combine?

46:24 Why does making more have zero value?

50:57 How does material knowledge improve prompts?

55:03 Why choose Weavy over ComfyUI?

55:44 How do sketches improve AI images?

58:33 How should creators divide work with AI?

01:02:12 What does out-of-distribution mean?

01:05:56 How do original references beat AI slop?

01:07:03 Why does fake AI UGC destroy trust?

01:11:31 What went wrong with Higgsfield?

01:22:33 Why did Midjourney acquire Co-Star?

01:24:09 Has Midjourney had the right vision?

01:27:30 Why are creators returning to Midjourney?

01:29:10 Why does bootstrapping protect creativity?

01:34:01 Why does AI creative work need fun again?

01:35:04 Does direct attribution kill creativity?

#Midjourney #AICreativity #AIDesign #GenerativeAI #FastHours

AI is making creative production faster while increasing the value of human craft, imperfection, and hands-on creative control.Drew and Rory start with Netflix’s 300 AI-assisted programs and somehow end up defending Blockbuster, boxy cars, greasy roommates, and the radical act of making creative work harder on purpose. Between the usual intellectual potholes, they uncover why invisible AI succeeds, why perfect outputs are becoming exhausting, and why human-made work may become the premium signal.Covered in this episode:Netflix generative AI workflows span concept development, pre-visualization, visual effects, post-production, and release. Suno, Udio, Strudel, Foley artistry, AI music licensing, Runway visual storytelling, Claude, ChatGPT, Figma shaders, Photoshop retouching, creative consistency, nostalgic design, imperfect aesthetics, and hybrid human-AI production define the broader creative shift.---⏱️ Fast Hour00:00 Why are guests returning to Fast Hours?03:45 Why does summer trigger nostalgia?10:49 How is Netflix using generative AI?20:39 Could Blockbuster have become Netflix?24:04 What AI tools has Netflix open-sourced?28:36 What did the Suno breach reveal?32:21 Should AI be used to make music?43:31 Breaking down Runway's lamp film—hy does it work?51:43 How many movie story arcs exist?53:32 Does AI increase the value of human craft?57:53 Why are creators rejecting AI perfection?01:06:16 Why is nostalgic design returning?01:17:09 Why do simple stories feel better?01:23:09 How do AI projects maintain consistency?01:25:43 Who should Fast Hours interview next?#GenerativeAI #AIFilmmaking #AIMusic #CreativeProcess #FastHours

In Episode 73, Salma Aboukarr joins the show. A creative director and founder, she explains how she moved from painstaking CGI workflows in Blender and 3Ds Max to AI-native campaigns for brands including Coca-Cola, Panasonic, and Google Labs. She breaks down her viral IKEA exploding-room video that helped brands see the commercial potential of generative AI video, the detailed JSON prompting method behind it, and the modern AI creative stack she uses across Claude, Midjourney, Nano Banana, Seedance, FAL.ai, Z-Image Turbo, Qwen, style LoRAs, and custom AI agents.The conversation goes deep on AI advertising, product fidelity, photorealistic skin, color correction, video upscaling, automated client workflows, and why high-end AI work still depends on original concepts, trained taste, and obsessive finishing. They debate whether AI can truly be original, why technical teams struggle to manufacture taste, how creators survive a feed flooded with AI content, and why the next creative moat may come from the experiences, references, and strange little details nobody else can copy.---⏱️ Fast Hour00:00 Meet Salma Aboukarr02:17 From CGI agency to AI-first studio04:44 Product fidelity before AI got good07:34 The duct-taped road to photorealism11:10 Art direction beyond basic prompting14:28 Salma’s current AI creative stack16:08 How she stress-tests every new model20:20 Why color correction still matters22:25 The IKEA video that changed everything27:13 Going viral and handling AI backlash30:38 Originality as the next creative moat33:05 Can AI actually be original?38:52 Inside an AI-native creative agency39:55 Z-Image Turbo and aesthetic base models43:06 From client brief to automated pipeline47:54 Style LoRAs for brand consistency49:11 Claude, MCP, FAL, and leaving ComfyUI51:07 The model that cut a day to 15 minutes55:13 Why AI content stopped feeling special01:00:57 The value trapped in AI archives01:02:06 Create for yourself or the audience?01:04:31 Can engineers manufacture taste?01:08:38 Finding inspiration outside the feed01:11:57 Jackie Chan and thumbnail fuel01:15:29 Final lessons from a creative trailblazer#AICreative #AIAdvertising #GenerativeAI #AIVideo #CreativeDirection #Midjourney #ClaudeAI #NanoBanana #SeedanceAI #AIWorkflow #AIAgency #AIContentCreation #BrandMarketing #CreativeTechnology #ProductPhotography #AIBranding #FutureOfAdvertising #FastHours

The boys are back with episode 72, where Rory Flynn and Drew Brucker attempt to discuss AI like serious adults. Yeah, that didn't work. They immediately detour into Figma Config, Waymo trust issues, Invisalign lisp watch, and the quiet horror of paying for AI models that may or may not be getting nerfed behind the curtain.

This one gets into the big question creative teams keep circling: is taste still a moat in the AI era?

Drew and Rory break down why “taste as a moat” is getting shakier, what types of taste are actually durable, and why timing, novelty, cultural awareness, editorial judgment, brand systems, and compounding context may matter more than ever.

They also dig into Claude Fable, government access to stronger AI models, the widening gap between public and private model capability, Figma’s new AI workflows, Weavy integration, Adobe Firefly Foundry, Disney’s custom AI model deal, and Midjourney’s V8.2 preview, texture upgrades, editing roadmap, and secret search tricks.

---⏱️ Fast Hour00:00 The boys are back00:11 Rory recaps Figma Config03:13 Rory tries Waymo for the first time08:52 The algorithm ding09:59 Invisalign enters the chat10:41 Claude Fable returns nerfed13:32 AI regulation gets messy18:44 AI tools and IP risk22:33 Taste as a moat gets challenged25:02 Breaking down types of taste27:40 Timing, novelty, and AI trends29:53 Trend cycles hit warp speed31:12 AI slop can damage brands34:45 Vintage aesthetics and timing38:37 Taste needs systems now40:14 Evolving visual taste43:19 South Park and imperfect taste45:55 Figma updates and custom tools52:39 Shaders, motion, and Weavy56:01 Retention beats acquisition01:00:59 Adobe Firefly Foundry01:02:25 Disney enters custom AI models01:03:34 The custom model problem01:07:09 Midjourney preview mode01:08:18 Midjourney V8.2 texture and skin detail01:16:13 Midjourney V9 training and web redesign01:16:43 Midjourney editing roadmap01:21:34 Secret search tip01:23:03 Broken toes and podcast lore01:25:14 Listener shoutouts01:27:13 Subscribe, hype, tell a mechanic#FastHours #ArtificialIntelligence #AI #AICreative #GenerativeAI #AIArt #Midjourney #ClaudeAI #AdobeFirefly #Figma #Weavy #AITools #BrandStrategy #CreativeAI #AIWorkflow

Midjourney spent years helping people generate impossible images. Then it used that image money to build a machine designed to look inside the human body.

In Episode 71, Drew Brucker and Rory Flynn, two men with zero medical degrees and a medically concerning level of confidence, unpack Midjourney Medical and David Holz’s surprise hardware reveal. At the center is the Midjourney Scanner, a water-based, full-body Ultrasonic CT prototype designed to capture detailed 3D body maps in roughly 60 seconds.

They break down how the scanner uses sound waves, water, and serious computing power; why Midjourney plans to introduce it through a San Francisco spa; and how a bootstrapped company with no investors can make a bet this strange. They also separate the scanner’s current body-composition ambitions from the much bigger MRI-level future Midjourney hopes to pursue through research, testing, and FDA approval.

Then the episode gets even less normal.Claude Fable 5 appears, dramatically accelerates Rory’s coding, Blender, and MCP workflows, and disappears days later following a US government directive. Naturally, this sends the hosts directly into Conspiracy Corner with no adult supervision.

Along the way, Drew and Rory explore how brand adoption of AI has changed, why some of the most advanced commercial AI work stays hidden behind NDAs, how companies can reward employees for useful AI innovation, and why first-time reaction content remains one of the internet’s strongest viral formats.

Is Midjourney’s full-body scanner a medical breakthrough, an ambitious wellness experiment, or the first clue to a much larger hardware roadmap? The hosts attempt to answer that question while also discussing the World Cup, the Knicks, government intervention, possible AI futures, and several topics their wives wisely avoid asking them about.

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⏱️ Fast Hour

00:00 Knicks, World Cup, and viral tourism

10:14 Sports, culture, and AI gatherings

13:06 Midjourney reveals secret hardware

15:49 David Holz explains the bigger mission

18:27 The 60-second full-body medical scanner

20:18 How bootstrapping made this possible

23:26 Water, spas, and medical skepticism

28:56 The scanner demo and nine-person team

40:30 Midjourney’s bigger secret roadmap

48:11 How brand AI adoption has changed

58:57 Claude Fable 5 appears, then vanishes

1:00:41 Inside the Fable 5 conspiracy corner

1:04:48 Why Fable 5 felt revolutionary

1:13:58 The AI race and 12 possible futures

1:18:22 Four years of Midjourney and the outro

In Episode 70, Drew Brucker and Rory Flynn are joined by Tyler Bernabe, better known as jboogxcreative, a full-time generative AI creator, strategist, and social menace responsible for some of the wildest AI videos your algorithm has probably shoved into your face at 1:13 a.m.

They get into how Tyler has gone viral across multiple generations of AI tools, why copying trends is creative quicksand, how shock value actually works when it is paired with taste, and why the best AI creators are building formats instead of chasing them.

The conversation also goes deep into the unglamorous machinery behind creative internet magic: Instagram to Patreon funnels, ManyChat, six-hour livestreams, creator burnout, client work, taste, consistency, and why “just post more” is advice usually given by people who should post less.

Then things get properly nerdy.

Tyler breaks down his current AI creative stack, including Midjourney 8.1, Seedance, Claude, YAML-style video prompting, Nano Banana, GPT image editing, Kling, Artcraft, Venice AI, Magnific/Freepik Spaces, Weavy, Reeve 2.0, and the never-ending wait for a proper Midjourney editor.

Along the way, they cover Chinese prompt translation for Seedance, 10,000-character prompt workflows, reference image construction, anime style development, mood board blending, why AI should sometimes pull you away from your own creative bias, and why the smallest edit in AI video still feels like defusing a tiny cursed bomb.

⏱️ Fast Hour00:00 Fast Hours welcomes Tyler aka jboogxcreative01:51 Going viral through every AI era02:35 The anatomy of scroll-stopping AI03:07 The seductive food video origin story05:32 Running opposite the AI meta08:24 Is AI art? Tyler’s best answer10:35 Why clients pay for your thing12:10 Stop copying other creators17:11 Viral views vs real conversion22:03 Building a creator business solo26:28 Burnout, longevity, and going through it33:05 Tyler’s current AI tool stack38:15 Artcraft, Seedance, and Chinese prompts42:05 Claude, YAML, and 10K prompts50:44 Tyler’s reference image hack58:15 Dream sketches and creative prototyping01:04:10 Reve 2.0 and layered editing01:10:38 Waiting for Midjourney’s editor01:16:02 Closing thoughts

#FastHours #jboogxcreative #AIVideo #AIArt #GenerativeAI#Midjourney #Seedance #ClaudeAI #AICreator #AIWorkflow #ContentCreation #AIPrompting #CreatorEconomy #AIAnimation#CreativeAI