Join Rohit Krishnan, author of Strange Loop Canon, Shawn Wang, editor of Latent Space, and Dean Ball, contributor to Mercatus, as they dive into the AI sensation Manus. They discuss Manus's capabilities and its potential to outshine existing competitors. The conversation explores the political and economic implications of AI autonomy, the shift toward practical applications over theoretical models, and the future landscape of AI ethics. With engaging insights, they highlight the importance of innovation intertwined with user safety in the rapidly evolving tech world.

Daniel had the chance to sit down with @swyx and Alessio from the Latent Space pod in SF to talk about current AI trends and to highlight some key learnings from past episodes. The discussion covers open access LLMs, smol models, model controls, prompt engineering, and LLMOps. This mashup is magical. Don’t miss it!Join the discussionChangelog++ members save 1 minute on this episode because they made the ads disappear. Join today!Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.comFly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. Typesense – Lightning fast, globally distributed Search-as-a-Service that runs in memory. You literally can’t get any faster! Featuring:Shawn Wang – Website, GitHub, XAlessio Fanelli – Website, GitHub, XDaniel Whitenack – Website, GitHub, XShow Notes:Latent Space podcastFeatured Latent Space episodes: BenchmarksReza ShabaniMosaicML and MPTSegment AnythingMike ConoverFeatured Practical AI episodes: From notebooks to Netflix scale with MetaflowCapabilities of LLMs 🤯 ML at small organizationsPrediction GuardData DanSomething missing or broken? PRs welcome! ★ Support this podcast ★

Your career is more than just a way to earn a living—it's a foundation for leading the kind of life you want. Shawn joins Mark and Adam to talk about navigating the non-linear course of a career; whether to correct weaknesses vs investing in strengths; salary negotiation; brag documents; and how to create luck. Plus: the Spinal Tap scale for rating software engineers. Discuss this episode in the Muse community Follow @MuseAppHQ on Twitter Show notes Shawn Wang @swyx Temporal VBA, Haskell Fullstack Academy Two Sigma, Netlify rough notes on what’s missing in serverless Build in public, Personal brand Learn In Public zero-sum Elasticsearch, Typesense cron job Descript The Coding Career Handbook “You can’t connect the dots looking forward; you can only connect them looking backward” Maslow’s hierarchy of needs Never Split The Difference a leak in your poker game brag documents, Julia Evans recency bias Adam’s pitch to Berlin startups in 2014 How to Create Luck luck surface area closed-form solution indie games, Braid So Good They Can’t Ignore You lifestyle design Kevin Kwok, P/E ratio, gravitas as a P/E ratio 10x developer Jeff Dean and Sanjay Ghemawat and their coding productivity “these go to eleven”

Shawn Wang discusses the essence of an AI engineer post his viral essay 'Rise of the AI Engineer', emphasizing skills, team structures, and trends in AI research. Topics include vertical vs. horizontal AI startups, advice for AI product creators, tools for AI products, and key AI trends. The conversation explores the evolution of roles in AI engineering, the AI Engineering World Fair, vertical AI startups, trends in AI capabilities and costs, and the creativity in AI models.

To wrap up the year we’re talking about what’s breaking the internet, again. Yes, we’re talking about ChatGPT and we’re joined by our good friend Shawn “swyx” Wang. Between his writings on L-Space Diaries and his AI notes repo on GitHub, we had a lot to cover around the world of AI and what might be coming in 2023. Also, we have one more show coming out before the end of the year — our 5th annual “State of the log” episode where Adam and Jerod look back at the year and talk through their favorite episodes of the year and feature voices from the community. So, stay tuned for that next week. Join the discussionChangelog++ members get a bonus 12 minutes at the end of this episode and zero ads. Join today!Sponsors:Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. InfluxData – With its data collectors and scripting languages, a common API across the entire platform, and highly performant time series engine and storage, InfluxDB makes it easy to build once and deploy across multiple products and environments. InfluxDB’s new storage engine allows developers to build real-time applications even faster and with less code. Sign up for the InfluxDB Beta program to give it a try. Retool – The low-code platform for developers to build internal tools — Some of the best teams out there trust Retool…Brex, Coinbase, Plaid, Doordash, LegalGenius, Amazon, Allbirds, Peloton, and so many more – the developers at these teams trust Retool as the platform to build their internal tools. Try it free at retool.com/changelog Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com Featuring:Shawn Wang – Website, GitHub, XAdam Stacoviak – Website, GitHub, LinkedIn, Mastodon, XJerod Santo – GitHub, LinkedIn, Mastodon, XShow Notes: AI Notes Why “Prompt Engineering” and “Generative AI” are overhyped Multiverse, not Metaverse The Particle/Wave Duality Theory of Knowledge OpenRAIL: Towards open and responsible AI licensing frameworks Open-ish from Luis Villa ChatGPT for Google The Myth of The Infrastructure Phase ChatGPT examples in the wild Debugging code TypeScript answer is wrong Fix code and explain fix dynamic programming Translating/refactoring Wasplang DSL AWS IAM policies Code that combines multiple cloud services Solving a code problem Explain computer networks homework Rewriting code from elixir to PHP Turning ChatGPT into an interpreter for a custom language, and then generating code and executing it, and solving Advent of Code correctly Including getting #1 place “I haven’t done a single google search or consulted any external documentation to do it and I was able to progress faster than I have ever did before when learning a new thing.” Build holy grail website and followup with framework, copy, repsonsiveness For ++ subscribers Getting Senpai To Notice You Moving to Obsidian as a Public Second Brain Something missing or broken? PRs welcome!

Shawn Wang discusses the AI Engineer role, team composition, trends in AI research, and advice for product creators with a focus on AI Engineer World Fair.

Shawn Wang, an AI engineer and developer advocate known for his insightful podcast 'Latent Space', dives into the evolving world of AI. He discusses why prompt engineering shouldn't be the main focus for developers and highlights how AI's scope surpasses individual understanding. Wang guides listeners through integrating AI tools like GitHub Copilot into development workflows, emphasizing the balance between AI productivity and human oversight. He also explores practical applications for web developers, showcasing the potential of AI across various modalities.

Shawn Wang discusses Software 3.0, the role of AI engineers, and the impact of foundation models on AI product creation. They explore model architectures, the challenges of putting foundation models into production, and the evolving landscape of AI developers. They also highlight the role of an AI engineer, OpenAI's recent innovations, and the potential of AI technology.

Shawn Wang, the coined term 'AI Engineer,' talks about the evolution of software development, the rise of AI engineers, AGI, and his 'smol-developer' project that facilitates quick project bootstrapping using prompt engineering.

Shawn Wang, an AI Engineer and angel investor known for his influential essay "Rise of the AI Engineer," dives into the evolving landscape of developer tools. He discusses the importance of intentionality in career and community building, alongside insights from organizing AI engineer conferences. Topics include the impact of AI on developer roles, angel investing strategies in emerging technologies like Supabase, and the significance of developer relations. Shawn also addresses concerns about developer obsolescence while championing human oversight in AI advancements.