After Things Podcast

You show this eyeball-looking thing some respect! A neat idea for invasive species. Blue Origin is tapped to make the second-next lunar lander and we debate the worthiness of doing that now. pando pando pando pando. Got something weird? Email [email protected], subject line “Weird Things.” [No After Things this week!] Picks: Justin: I Think You Should Leave, season 3 Brian: Spider-Man: Across the Spider-Verse Bryce: EGG GAME

Bryce jumped on the whiteboard train feet-first and we chat about whiteboards, writing and organizing tasks, habit-building, and getting motivated to start. Send your project questions/ideas to [email protected], subject line “After Things.”

The episode begins with Andrew describing a memory-methods thread from the previous week and how it led him to build a face-and-name practice app. He explains that he prototyped the tool in JavaScript and then used GPT-4 to convert and expand it into a polished iOS app, with generated faces, tutorial copy, App Store text, and a webpage all created or assisted by the model. The discussion then widens into a long debate about how well ChatGPT understands context, why GPT-4 feels stronger for coding, and how priming prompts can improve style imitation and task performance. The back half of the episode shifts into hypnosis, with the hosts comparing stage hypnosis, hypnotherapy, Mesmerism, suggestibility, placebo effects, accountability, crowd dynamics, and whether hypnosis is best understood as an altered state, performance, or agreement. Key topics Memory techniques and face-name recall: Andrew opens by talking about memory methods, memory palaces, and his difficulty remembering faces and names, which motivates the app he built. GPT-4-assisted app development: Andrew says he used GPT-4 to build a JavaScript prototype, convert it to SwiftUI, and generate supporting copy and pages for Memory Snap. AI-generated faces for practice: Andrew explains that he used DALL·E to create hundreds of faces, discarded poor images, and selected convincing ones for the app. ChatGPT as a coding assistant: The hosts discuss how ChatGPT/GPT-4 can explain code, suggest libraries like faker.js, and hel

The episode opens with a light memory test where Bryce asks the others to close their eyes and recall what everyone is wearing. That leads into a broader discussion of memory, attention, and how much people can notice about familiar faces and clothing when they are not allowed to prepare ahead of time. Andrew uses Harry Lorraine's classic audience-name routine as a jumping-off point to explain why "photographic memory" is usually overstated. The hosts discuss autobiographical memory, diaries, repeated reinforcement, and the idea that many impressive memory feats come from learned techniques rather than innate perfect recall. The conversation then moves into practical mnemonic methods: associations, absurd imagery, spaced repetition, memory palaces, body lists, narrative chaining, and number or card pegs. The hosts also connect memory training to modern tools like AI and augmented reality, and argue that remembering names and personal details is a useful social skill, not just a party trick. In the picks segment, Brian recommends The Science of Storytelling, Justin recommends Guardians of the Galaxy 3, and Bryce recommends Defunctland's Disney's Fast Pass: A Complicated History. The picks close the episode after a discussion of how memory, story, and theme park queue design all reflect broader patterns of human behavior. Key topics Initial clothing memory game: Bryce starts the episode with a closed-eyes clothing recall challenge, asking the others to identify what everyone is

Tips direct from Andrew on how to level up your ChatGPT prompts straight from the robot-horse’s mouth. Easy tips to add more context and style, create outlines, and automate common requests. Send your project questions/ideas to [email protected], subject line “After Things.”

The episode opens with a long discussion of SpaceX's Starship test launch and the condition of the launch pad afterward. The hosts say the rocket reached flight but suffered a rapid disassembly, likely after debris from liftoff damaged engines and carved a large crater in the concrete; they also talk about possible fixes such as a flame diverter, more water cooling, and other launch-pad changes, while joking about Andrew Mayne's pie bet. A large middle section focuses on generative AI and synthetic media. The hosts discuss Runway's video tools, ChatGPT plugins, code-interpreter-style rapid prototyping, AI-assisted editing and research, and then move into concerns about fake images and AI-generated music. They compare the coming fight over AI music to Napster and sampling, speculate about licensing or revenue-sharing models for artist voices and styles, and note how streaming platforms might adapt. Key topics Starship launch damage and launch-pad mitigation: The hosts describe the Starship test as successful in reaching flight but damaging to the pad, with a crater, debris, and likely engine damage. They discuss flame diverters, water cooling, and other infrastructure changes as possible mitigations. Engine-out analysis during Starship ascent: Andrew and Bryce look at the engine diagram and infer that debris may have knocked engines offline during ascent, while noting that some of the on-screen failures could be sensor data rather than actual engine loss. Why spaceflight devel

Listener David asks for advice on how to portion out time for longer-term projects? Our advice and tips for getting things done with momentum and phases. Send your project questions/ideas to [email protected], subject line “After Things.”

The episode opens with discussion of ULA's Vulcan test article exploding on the test stand and what that means for the planned launch. The hosts compare ULA's one-off test hardware with SpaceX's factory-style approach, where repeated explosions are less disruptive because another vehicle is already being built and the program is designed for rapid iteration. The conversation then moves into broader transportation speculation: rockets for very long trips, autonomous or electric aircraft for regional travel, and various VTOL or drone concepts that might solve the 'two vehicle problem.' The hosts also discuss Hyperloop and tunneling, emphasizing that regulation, eminent domain, and especially cheaper boring technology are the real constraints on new infrastructure. Key topics Rocket test failures and operational implications: Andrew describes the Vulcan center-stage test article exploding on the test stand and says it may or may not indicate a design flaw, noting the possibility of delays or additional testing. SpaceX's production-and-iteration model: The hosts contrast ULA's approach with SpaceX building a factory and iterating rapidly, making failed prototypes less consequential because replacements are already being produced. Future transportation layers: The discussion imagines rockets for long-distance travel, electric or autonomous aircraft for shorter regional hops, VTOL-style systems, and other speculative transit concepts. The 'two vehicle problem': Justin cites the pro

Professional podcasters Justin and Brian give some dirt on the upcoming third season of World’s Greatest Con and talk openly about their vantage point on ads in the podcasting space. Send your project questions/ideas to [email protected], subject line “After Things.” World’s Greatest Con

The episode opens with a long, playful discussion of the old TV show Manimal, with the hosts joking about its simple premise of a man who turns into animals to solve crimes and comparing it to other 1980s transformation or action shows. That flows into a broader chat about actors and roles that surprised them, including Harrison Ford de-aging in the new Indiana Jones trailer, Phoebe Waller-Bridge, Simon Pegg, Jason Statham, Bradley Cooper, and Steven Lang. A major middle section focuses on AI tools and their practical uses. Andrew describes transcribing and searching a podcast with Whisper/MacWhisper, while the group also discusses Bing inside Skype, a voice-based ChatGPT service called Call Samantha, AI at CES, job-loss headlines, and uses like help bots, show notes, formatting lists, and contractor bids. The episode then shifts to recurring segment material: a Starship betting update, news about Virgin Orbit bankruptcy and the difficulty of space ventures, and the pick segment featuring a Dungeons & Dragons movie recommendation, World's Greatest Con promotion, Star Trek documentaries, and Dave Not Coming Back. Key topics Manimal as an 80s high-concept TV premise: The hosts repeatedly explain Manimal as a man who can transform into animals to help solve crimes, and they joke about how quintessentially 1980s and high-concept the show feels. De-aging CGI in the new Indiana Jones trailer: Justin comments that the de-aged Harrison Ford footage looks surprisingly good and may be