Today Quincy Larson interviews Shawn Wang. He's a software engineer, founder of the AI Engineer conference, and host of the Latent Space podcast focused on applying the latest models toward getting work done.

We talk about:
- How even if LLMs plateau, there will be still paths to better output through surrounding harness code
- And three big areas researchers are exploring to further improve model performance: World Models, Multi-modality, and Embodied AI
- Which skills Shawn thinks are most important for developers going forward
- And why Shawn thinks you should switch your own self teaching from "just-in-time learning" to "just-in-case learning"

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Links from our discussion:
- Shawn's Tiny Teams Playbook: https://www.latent.space/p/tiny
- Shawn's interview with FeiFei Li: https://www.latent.space/p/after-llms-spatial-intelligence-and?utm_source=publication-search
- Boots Theory: https://en.wikipedia.org/wiki/Boots_theory
- Wirth's Law: https://en.wikipedia.org/wiki/Wirth%27s_law
- Adversarial Reasoning: https://www.latent.space/p/adversarial-reasoning

Community news section:

1. freeCodeCamp just published a comprehensive course that will teach you how to use the security-focused Kali Linux operating system. You’ll learn how to identify, exploit, and defend against real-world vulnerabilities. You'll also build a solid foundation in penetration testing, network security, and vulnerability assessment. Most importantly, you'll learn how to think like a security engineer and leverage tools of the trade like Nmap and Wireshark. (4 hour YouTube course): https://www.freecodecamp.org/news/learn-cybersecurity-and-ethical-hacking-using-kali-linux/

2. freeCodeCamp also published a guide to passing the Certified Kubernetes Administrator Exam. Beau Carnes teaches this course, which will walk you through key DevOps concepts. You'll start by setting up your K8s practice environment. Then you'll bootstrap a multi-node cluster and your control plane. You'll learn about Helm, High Availability Autoscaling, CoreDNS, and more. (2 hour YouTube course): https://www.freecodecamp.org/news/prepare-for-the-kubernetes-administrator-certification-and-pass/

3. We also just published a full-length handbook on freeCodeCamp Press that you can read right in your browser. It will teach you modern React data fetching best practices. You'll learn how to leverage Suspense, ErrorBoundary, and the new Use API. If you're interested in web development, this is well worth bookmarking. (full length handbook): https://www.freecodecamp.org/news/the-modern-react-data-fetching-handbook-suspense-use-and-errorboundary-explained/

5. Finally, I'm proud to share this new DevOps course that freeCodeCamp instructor Gavin Lon just published. You'll learn how to take a full stack app on your local machine and ship it to a fully containerized production environment. Along the way, you'll learn about CI/CD pipelines, Docker images, launching containers, and more. By the end of the course, you'll have a professional-grade pipeline that automatically builds and deploys updates with every push. (4 hour YouTube course): https://www.freecodecamp.org/news/build-a-production-ready-pipeline-with-docker-cicd-and-hostinger/

5. Today's song of the week is the 1980 classic "Turn me Loose" by Canadian band Loverboy. Build on top of a super catchy syncopated bassline, this song has some super expressive vocals, buzzing synths, percussive piano, and the guitar solo is top shelf. https://www.youtube.com/watch?v=TnHm4ro_l8s

Chapters
00:00 Welcome & Intro: Sean Wang (Swyx)
00:42 freeCodeCamp News: Kali Linux, Kubernetes & React
02:12 Full Stack DevOps Course
02:50 Song: "Turn Me Loose" by Loverboy
03:49 Interview: AI Engineer Conference & Latent Space
04:24 Future AI: World Models & Embodied AI
04:53 Just-in-Time vs. Just-in-Case Learning
05:27 Judging 1,000 Devs at Stanford TreeHacks
06:05 Top Project: Reverse Engineering with AI
07:52 The "AI Wrapper" Debate
08:34 How LLMs Changed Hackathons
09:20 Addressing AI Cheating & "Blank Slate" Spirit
10:26 Non-Technical Founders Building with AI
11:13 AI's Impact on the Software Labor Market
14:30 High-Perf Wrappers vs. Deep AI Engineering
18:45 Importance of Evaluation & Benchmarking
22:15 Is Model Performance Plateauing?
27:50 Agentic Workflows & Multi-Step Reasoners
33:10 Open vs. Closed Source: Llama & Mistral
39:05 Transitioning to an AI Engineer Role
45:20 From Prompt Engineering to System Design
51:40 Speculating on GPT-5 & Next-Gen Models
58:10 Robotics & Physical (Embodied) AI
1:04:30 Building AI Communities
1:10:15 Career Advice for the AI Era
1:15:26 Closing Remarks & Resources

freeCodeCamp is a nonprofit organization offering free online coding courses and programming tutorials, covering topics such as web development, data science, and machine learning. Learners can gain practical coding skills, build real-world projects, and earn certifications to advance their careers in tech.

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Shawn Wang (swyx), who coined the term 'AI engineer', discusses the future of AI with freeCodeCamp's Quincy Larson. Key topics include: observations from judging Stanford's TreeHacks hackathon, the shift from 'just-in-case' to 'just-in-time' learning strategies for developers, and three major research directions beyond reasoning models — memory/continual learning, world models (video-based, JEPA-style, and adversarial/theory-of-mind), and multimodality including embodied AI in robotics. Swyx also touches on the economic risks of waiting to adopt AI tools, the limits of context window scaling, and a fourth frontier: AI for science.

The three paths AI could take from here - Shawn Wang SWYX interview [Podcast #208]