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

Drew and Rory are back for episode 69, which is legally required to begin with at least one immature joke before immediately collapsing under the weight of Google’s latest AI product avalanche.This week, they dig into Google Omni, Gemini 3.5 Flash, Google Flow, Google Pics, Nano Banana, Veo, and whatever else Google launched before anyone had time to make coffee. The big question: are these actually meaningful creative upgrades, or did Google just throw 19 AI names into a blender and call it innovation?They break down early Omni and Flow tests, why video physics still feel weird, where Seedance and Kling may still be ahead, and why Runway Aleph 2.0 feels promising but imperfect. Rory shares hands-on examples with character swaps, driving videos, golf swings, agent mode, and Flow’s new tool-building features. Drew tries to keep the conversation coherent while quietly wondering if every AI product now needs a map, glossary, and mild sedative.The episode also gets into Gemini as a search replacement, creepy context awareness, privacy tradeoffs, AI tools connecting to personal data, the fuzzy definition of “agentic,” the limits of auto-clipping tools, GPT Image 2’s SynthID watermarking, metadata headaches for client work, and the universal pain of wasting $15 trying to make an image model spell “stump.”If you’re trying to understand what Google’s AI updates actually mean for creators, marketers, AI video workflows, image generation, creative direction, and the future of agentic media tools, this episode is half useful breakdown, half group therapy for people with too many tabs open.---⏱️ Fast Hour00:00 Cold open00:32 Google’s AI naming avalanche01:39 AI hype vs actual workflow value02:34 Why AI launches feel like iPhone upgrades06:12 Google’s “throw everything” strategy07:08 Omni vs Veo 4 expectations07:43 Video physics and speed problems09:03 Google Pics, Flow, Omni, and Flash10:04 How Rory actually uses Gemini11:51 Gemini 3.5 Flash breakdown12:38 AI benchmarks feel like marketing13:42 Gemini as a better search layer15:18 Creepy Gemini context awareness17:35 Why AI data connections feel too early19:15 The privacy tradeoff gets darker21:19 Google Omni vs Runway Aleph 2.022:12 Google Omni testing starts rough23:39 Google Veo 3.1 feels forgettable25:21 Why Omni feels early26:19 Higgsfield clipper test fails27:59 Why auto-clipping still misses31:30 Rory tests Flow and Omni live32:41 Omni character swap struggles33:33 Runway Aleph panda test34:07 Flow’s new interface and tools35:02 Building custom tools inside Flow36:10 The joy of making tools from nothing37:39 Agent mode for still-image workflows39:05 Batch creative directions in Flow40:03 Omni turns six images into video40:47 Driving physics still feel off41:55 Why consistency matters for adoption43:03 Kling, Seedance, and the update race43:59 Seedance handles complex camera motion45:42 GPT Image setup for golf video46:53 Testing the same prompt in Flow49:25 Why agentic platforms can feel thin51:10 The need for visual design systems52:21 Flow’s golf swing result53:56 Everyone is racing toward agentic54:18 What “agentic” actually means56:03 Claude feels more genuinely agentic57:04 Josh Hart quote analysis detour58:44 Reverse-engineering creative patterns59:53 Pizza, calzones, and prompt structure01:00:26 SynthID and GPT Image 2 watermarking01:01:47 Metadata problems for client work01:02:51 Google Pics enters the chat01:04:03 Too many image models to track01:04:52 Midjourney color still hits different01:06:01 GPT Image 2 quality frustration01:06:59 Image models still struggle with scale01:08:26 Bad AI weeks happen too01:09:20 Midjourney 8.2 speculation01:10:01 Tell your florist

In episode 68 of Fast Hours, Drew and Rory return from a two-week hiatus to prove that yes, the AI news cycle did continue without their permission. Rude.

They dig into Freepik changing its name to Magnific, why enterprise AI image tools are starting to feel more like creative operating systems, and how brands may be better off using approved model aggregators instead of building weird internal Franken-tools that immediately become outdated.

Then things get nerdier. Obviously.

Rory breaks down how he’s using Codex, GPT-Image-2, Claude Code, MCPs, Higgsfield, Seedance, and visual style reference sheets to create repeatable image systems, character references, and bulk creative workflows without living inside a giant text prompt forever. Drew pushes into where Midjourney V8.1 still dominates, especially photorealistic faces, color, texture, and images that do not look like corporate stock photography that lost the will to live.

They also talk about Midjourney’s upcoming 8.2, 8.3, V9 roadmap, edit model ambiguity, personalization drift, Luma Uni comparisons, Pinterest’s internal AI image model, Salesforce going headless, and why AI video audio still sounds like it was recorded inside a cursed podcast booth.

And because no episode is complete without accidentally getting philosophical, they close with the viral Claude Monet AI social experiment, the weird bias people bring to AI-generated images, and why “how it was made” keeps hijacking whether people can actually see what’s in front of them.

Basically, it’s an episode about the future of AI creative tools, with two guys trying to sound calm while the ground turns into soup beneath them.

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⏱️ Fast Hour

00:00 Cold open01:12 AI news fatigue is real01:44 Claude Code runs the day now03:11 Remote work and coffee shop crimes08:21 3 Ninjas nostalgia break10:09 Freepik becomes Magnific11:47 Why Magnific works for enterprise13:00 Model aggregators vs internal tools18:01 Pinterest builds its own AI image model22:11 Salesforce goes "headless"24:08 Higgsfield, MCPs, and Meta ads29:51 Codex for GPT-Image-2 workflows32:45 Pulling style from video frames34:05 Building visual style reference sheets37:36 Codex and textured illustration systems39:34 The evolution beyond text prompts41:50 Seedance storyboards and visual prompts43:01 Reference images as reusable seeds44:51 AI video still has an audio problem46:13 Audio reference hacks in Dreamina50:52 Omni-reference for video control52:37 Midjourney V8.1 updated take53:28 The blue and pink problem returns55:37 Midjourney still owns realistic faces58:56 Reworking old prompts with Describe01:01:10 Luma Uni vs Midjourney color01:02:11 Midjourney 8.2, 8.3, and V901:03:46 Midjourney edit model questions01:07:13 Midjourney plus Seedance films01:09:03 Midjourney’s strange lane01:12:28 The Monet AI social experiment01:15:13 Why people over-detect AI01:20:09 AI backlash and disclosure debates01:22:50 AI as a career unlock01:24:30 Keep making weird stuff01:25:45 Wrap-up and seamstress CTA

Fast Hours has entered the witness protection program. Same Drew. Same Rory. But fewer syllables and more chaos.In this episode, Drew Brucker and Rory Flynn officially drop “Midjourney” from the podcast name and relaunch as Fast Hours, a broader home for the creative AI ecosystem: image models, video models, LLMs, vibe coding, Claude, ChatGPT, Midjourney, and whatever tool drops five minutes after they hit publish. Naturally, the rebrand lasts about four minutes before they’re elbows-deep in GPT-Image-2, OpenAI’s new ChatGPT image model that quietly showed up and immediately started making designers question their calendar, career choices, and relationship with kerning.The big topic: GPT-Image-2 is shockingly good with text, typography, brand systems, visual decks, product mockups, and multi-image outputs. Rory walks through how he used ChatGPT and Claude to create a custom typeface from visual references, generate a premium typography presentation, extract geometry, and turn the whole thing into usable font files. Drew then shows how he turned his own handwriting into a working typeface, because apparently “personal brand” now includes making your lowercase g file a tax asset.They also dig into the uncomfortable middle ground of AI creative work: when it saves time, when it still needs human judgment, why anti-AI panic and AI hype both miss the point, and why the real advantage is context. Not prompts. Not magic buttons. Context.The episode also covers GPT-Image-2 vs Nano Banana Pro, richer color rendering, micro-text improvements, AI-generated sports graphics, brand kit concepts, Freepik settings, Claude Design, 4K video generation, Kling, Veo 3.1, Seedance, and the strange reality that a custom brand typeface can now go from “that’ll be $150K” to “Rory did it before lunch.”Basically, it’s an episode about the exact moment creative production stops feeling like a tool demo and starts feeling li ke a factory someone accidentally left unlocked.---⏱️ Fast Hour00:00 Fast Hours is (re)born03:36 Going tool-agnostic04:34 GPT-Image-2 quietly drops05:31 Text becomes the unlock07:31 The AI backlash returns10:57 Hype, fear, and the middle12:10 Typography gets weird14:50 What custom fonts cost15:43 GPT-Image-2 vs Nano Banana17:39 Rory’s font experiment18:47 Fiddleheads become a typeface19:39 Building the type deck20:36 The nine-slide image unlock21:14 Geometry, spacing, and logic22:11 Turning images into font files23:02 Micro-text gets better24:19 Claude builds the font package26:41 The revision loop changes27:50 Context is the silver bullet32:11 Drew makes a handwriting font35:35 Why designers obsess over type37:52 Reverse-engineering prompts39:51 Richer color and sports graphics41:27 Fixing artifacts and details42:37 Nano Banana vs GPT-Image-2 tests44:26 Sports realism gets scary good45:27 Why teams need this now46:43 Freepik settings and ratios48:36 Testing, tokens, and limits49:44 Brand kits and rebrand concepts53:19 Google I/O and the next model53:48 Veo 3.1 falls behind55:04 Kling adds native 4K56:40 Character sheets and macros58:07 Rebrands as visual prototypes01:00:53 Building a reference library01:01:36 Three weeks in a row01:02:58 Claude Design tease01:03:37 Tell your local [fill in the blank] spam finale

Midjourney finally dropped v8.1, so Drew and Rory did what any responsible adults would do: generated way too many images, argued with style codes, stress-tested text, and immediately started asking whether the edit model is the part that actually matters.In episode 66 of Midjourney Fast Hours, the boys dig into why Midjourney v8.1 feels way better than v8, where it still falls short, and why this release feels less like a victory lap and more like Midjourney finally arriving at the version v8 probably should’ve been in the first place. They get into faster generations, native 2K output, mood boards, prompt depth, describe, personalization profiles, text rendering, image weight, --exp behavior, old v6 style-code weirdness, and the growing sense that the real make-or-break feature is still the edit model.They also get into how Midjourney stacks up against tools like Nano Banana, Grok, Reve, and Luma, why image generation still feels fragmented across platforms, and whether Midjourney should even bother chasing video or just go all-in on images, editing, and control.Then, because this is still Midjourney Fast Hours, the episode somehow ends with a deeply important discussion about custom Mac folder icons.If you care about Midjourney v8.1, prompting strategy, style references, AI image workflows, generative art tools, or where Midjourney is actually headed next, this one’s got the goods.---⏱️ Fast Hour00:00 Intro and v8.1 arrives01:05 Is v8.1 actually better than v8?04:09 The edit model is the real test06:22 Should Midjourney even chase video?10:07 v8.1 needs more prompt depth12:07 Mood boards feel usable again14:28 Testing the new describe tool21:00 Personalization profile matters most22:09 Text tests and object recognition23:57 “Photo” vs art and stylize tests29:54 Why v8.1 feels a bit like v630:43 Old style codes hit differently now42:08 --sv7 issue and style-code confusion45:47 Missing parameters and what still works47:26 Hidden text tests and image weight49:57 --exp tests and behavior shifts52:35 Grid view and the alpha site54:50 Office Hours, 8.2, and edit timing01:03:27 Custom Mac folder icon detour01:09:01 Wrap-up and parting nonsense

In episode 65, Drew Brucker and Rory Flynn return for another round of Midjourney Fast Hours and immediately do what they do best: poke at bleeding-edge AI tools until something breaks, gets weird, or accidentally becomes useful.They kick things off with fresh Midjourney V8 impressions, including what changed after another week of testing, why resetting personalization profiles helped, where the weird magic still shows up, and why V8 still feels like it is waiting for its real arrival. They also dig into the rumored Midjourney V8.1 update, what it could fix, and why the real test may come down to the edit model, text rendering, consistency, and whether Midjourney can pull serious users back into the platform.Then the episode takes a sharp turn into Claude, and honestly, this is where things get deliciously nerdy. Drew and Rory unpack how they are building with Claude in real life: when something should become a skill, how Claude MD files shape everything downstream, why auditing your own setups matters, how to think beyond rigid workflows, and what happens when your AI starts feeling less like a chatbot and more like a strange little operating system trained on your habits, instincts, and creative baggage.They also get into edge-case detection, memory files for collaborators and clients, private repos, Codex as backup muscle, analogy engines, and a growing obsession with building a “creative intelligence layer” that can carry more of his actual thought process into AI tools. ---⏱️ Fast Hour00:00 Intro and the boys are back01:12 Why the podcast got bigger than Midjourney03:25 Rory’s updated Midjourney V8 take04:40 Why new personalization profiles helped06:31 The weird Midjourney magic is back13:24 Midjourney 8.1 might be the real V816:36 Why the edit model really matters18:51 Claude skills: what should be a skill23:58 Why Claude MD files matter so much25:23 Building flexible AI systems, not rigid ones38:38 Rory’s edge-case detector skill41:55 Memory files for people and projects43:48 The creative analogy engine50:35 Why examples beat vague prompting53:38 Back up your Claude brain immediately55:30 Rory’s orchestrator and skill roster01:06:04 Hard-coded flows vs flexible AI judgment01:07:43 Building a creative intelligence layer01:18:01 William Shatner, Babe Ruth, and better analogies01:20:53 Outro and comment bait

Drew and Rory crawl back from travel chaos, token addiction, and mild creative delusion to answer the question everyone’s been asking: did Midjourney V8 finally land... and was it worth the wait?In this episode, they break down their real first impressions of Midjourney V8, including what feels better, what feels busted, why mood boards are suddenly acting possessed, and why the old “short and vibey” prompting style may have quietly lost its crown. They get into coherence, SV6 vs. SV7 behavior, stylize weirdness, failed generations, the alpha-site disappointment, and the one thing that actually matters now: whether Midjourney can ship a truly usable edit model before everyone wanders off to easier tools.Then the conversation mutates into a full-blown Claude Code spiral. Drew and Rory unpack the Chrome extensions, internal skills, markdown systems, Notion setups, custom workflows, and tiny automations they’re building at an alarming pace. There’s talk of AI writing detection, reusable agent pipelines, presentation hacks, Pinterest utilities, GitHub repos, and the growing suspicion that the real side effect of Claude Code is not productivity. It is total psychic collapse with excellent output.If you care about Midjourney V8, Claude Code, mood boards, AI image generation, prompt structure, creative workflows, Chrome extensions, automation systems, or what happens when two visual AI nerds disappear for a few weeks and come back with opinions, this one’s for you.

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⏱️ Fast Hour

00:00 - Midjourney V8 finally lands

01:25 - Rory’s travel chaos and failed gens

05:06 - First impressions and alpha letdown

11:30 - V8 coherence and vibey prompts

13:30 - SV6 vs SV7 mood board test

21:44 - Mood board degradation gets real

25:56 - V8 looks better, but fails too often

33:04 - Structured prompting may matter more

35:29 - Q4, HD, and stylize confusion

39:09 - The real missing piece: edit model

43:45 - Why nobody wants workaround theater

48:04 - The strange realism hiding in V8

54:45 - Claude Code takes over their brains

58:19 - Rory’s skill stack and agent hub

01:04:15 - Drew’s “ghost system” for writing

01:07:07 - Killing Calendly with Claude

01:11:17 - Tiny tools, huge leverage

01:17:13 - Ask the model how it wants data

01:26:31 - Billboard shout-out

01:32:32 - Wrap-up, RIP Sora, subscribe

After a brief hiatus, the boys are back!

With Midjourney v8 expected next week, Drew and Rory zoom out and ask the bigger question: does v8 even matter as much as we think?

Because while everyone waits for v8, Kling 3.0 and Seedance 2.0 are raising the bar, Claude Code and Claude Cowork are quietly changing how builders operate, and Claude Agents are turning workflows into autonomous systems.

Meanwhile, Higgsfield is melting down in public, Hollywood is panick-maxxing, and creators are realizing that building “skills” inside LLMs might matter more than generating prettier images.

This episode breaks down:

• Why Midjourney v8’s native 2K and edit models matter• Why personalization could be the real differentiator• How Claude Code is quietly enabling operator-level leverage• Why skill-building beats agent hype• What Kling 3.0 and Seedance 2.0 signal about video AI• The real lesson behind Higgsfield’s fallout• Why the creative skill gap is widening right now

This episode moves from Midjourney roadmap analysis to AI workflow engineering to business survival strategy.

If you care about Midjourney v8, Claude Agents, Kling 3.0, Seedance 2.0, system prompts, autonomous workflows, or where creative leverage is actually going…

This one isn’t optional.

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⏱️ Midjourney Fast Hour

00:00 – Winter chaos & NYC survival03:59 – AI’s quantum leap moment06:51 – Radio vs podcasts analogy08:55 – AI series vs Hollywood model10:59 – Game of Thrones AI sequel14:14 – CGI patchwork & filmmaking16:14 – AI replacing exec decisions18:03 – Seedance & model hype19:48 – Midjourney v8 timeline20:15 – Rating party (Round 2 + beyond)23:18 – 2K native resolution talk24:26 – Batch-four replacement25:48 – Edit model improvements26:14 – v8 text rendering progress27:03 – Arbitrary resolution support29:06 – Personalization in v830:36 – Mood boards as leverage32:18 – AI overwhelm & X fatigue34:12 – Claude agents & automation36:04 – “Something is happening”39:45 – AI skill-building strategy45:47 – Pattern matching workflows48:54 – Silicon Valley middle-out50:24 – Claude comedy experiment53:24 – Word clouds & ad thinking55:14 – Hollywood recycling IP58:41 – Marketing narrative engine01:03:57 – Higgsfield controversy01:11:36 – Final thoughts & sign-off

Episode 62 starts where every serious AI podcast should: Adam Sandler movies, Bobby Boucher lore, and a suspicious black eye.Then things spiral fast.Drew Brucker and Rory Flynn catch up after the holidays and dive headfirst into what’s actually happening across Midjourney, Nano Banana Pro, system prompts, and the growing gap between “fun” image generation and production-ready work. They unpack why Midjourney V8 still hasn’t landed, what the Style Creator and personalization updates really mean, and why editing remains the most important missing piece.From there, they break down how system prompts, structured workflows, and layered instructions are quietly becoming the real unlock for visual AI. Expect deep talk on nodes, Claude, Gemini, Nano Banana Pro, mood boards, contact sheets, consistency at scale, and why most people are still underusing these tools.Then the existential dread kicks in.They explore Moltbook and autonomous AI agents talking to each other, forming communities, filing bug reports, questioning consciousness, and accidentally exposing their owners. It’s funny. It’s uncomfortable. It’s probably important.The episode closes with Google Genie, open-world AI environments, and the creeping sense that we’ve officially crossed into “things are getting weird” territory.Equal parts practical, hilarious, and mildly alarming. Just another normal week in AI.---⏱️ Fast Hour00:01 – Episode intro and the mystery black eye00:35 – Waterboy, Bobby Boucher, and Sandler nostalgia05:53 – Why mid-budget fun movies disappeared07:46 – Midjourney Office Hours and no v8 yet09:26 – Mood boards, Style Creator, and quality drop-offs10:39 – New Style Creator controls and SREF biasing11:40 – Why Midjourney is still fun to use13:35 – Corporate phrases as horror prompts16:26 – Midjourney UI vs other tools19:01 – What “higher quality” actually needs to mean22:18 – Consistency problems at scale23:06 – Personalization updates explained26:03 – Editing models and what’s missing28:18 – Nano Banana Pro vs Midjourney for client work30:00 – System prompts as visual infrastructure31:19 – Why most people misuse Nano Banana33:32 – Multi-step prompts and real workflows36:34 – Letting LLMs define style for you39:06 – Mood boards, Cosmos, and dataset curation44:49 – Building AI-ready style guides from images49:21 – Open-source Nano Banana prompt libraries56:07 – Claude organizing chaos at scale01:06:26 – Moltbook and autonomous AI agents01:09:30 – Bots forming communities and social behavior01:14:54 – Consciousness, validation, and AI identity01:21:45 – Google Genie and open-world AI01:26:19 – Wrap-up and listener call-outs