Shawn Wang

Shawn “swyx” Wang, AI engineer, writer, and AI community builder, returns for a fast-moving tour of what matters now. They dive into conference signals, agent infrastructure, vertical vs. horizontal startups, and the rise of the agent lab playbook. Plus: coding wars, memory systems, open models, custom chips, security risks, and why small startups may still have room to win.

Shawn Wang (Swyx), AI engineer and operator at Cognition who organizes AI engineering events, joins to map current trends. He discusses whether AI infrastructure has stabilized. He dives into coding agents, the stickiness of Claude Code versus Codex, the rise of open models, and why memory and personalization are the next frontiers.

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.

Morgan Housel, a financial writer known for his investing insights, joins AI researcher Shawn Wang, Honey co-founder Ryan Hudson, and other industry leaders to discuss the potential for an AI takeover by 2027. They explore the implications of AI advancements, contrasting U.S. and Chinese approaches. Kirsten Green shares insights on consumer trends, while Virgílio Bento highlights AI's impact on healthcare. The guests also dive into the challenges of modern communication and the journey behind Ryan's Honey, blending personal stories with professional insights.

Shawn Wang (swyx), AI practitioner and writer who builds coding agents and developer tools. He discusses integrating AI into IDEs, building browser agents and RAG systems, and the tradeoffs between agentic search and semantic indexing. Conversations cover subscription economics, software eras (1.0/2.0/1+2), and engineering challenges like memory, continual learning, and product quality.

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, a writer and editor at Latent Space, joins Alessio Fanelli, CTO at Decibel Partners, for an insightful discussion. They delve into open access LLMs and the evolution of model control techniques, alongside the emerging field of LLMOps. The conversation highlights the importance of prompt engineering and shares reflections from past episodes, including grassroots AI efforts in Africa. Expect a blend of practical insights and challenges that shape the future of AI technology in a rapidly changing landscape.

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.

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.