Activities
historical
- Early career in quantitative finance and trading, building data pipelines and quantitative portfolio systems. This background informs his analytical approach to developer tools and AI infrastructure.
- Transitioned into developer experience and developer relations roles at prominent technology companies and startups, including stints at Netlify, temporal (Head of Developer Experience), and other developer-tools-focused companies.
- Long history of community-building: founded or led communities/projects such as Svelte Society, contributed to /r/reactjs, and co-maintained the React + TypeScript Cheatsheet.
- Prolific writer and educator: authored the “Coding Career Handbook” and influential essays such as “The Rise of the AI Engineer,” which helped crystallize an emerging professional role.
present
- Editor and principal curator of Latent Space — a media platform (podcast, newsletter, and other formats) focused on AI engineering and the systems, people, and practices that enable production AI.
- Founder of Smol AI (smol.ai), a company focused on LLM data pipelines and automation for research and content workflows.
- Host of the Latent Space podcast and curator of AI News / AI-focused newsletters and research digests.
- Active angel investor and advisor in developer tools and AI startups; runs or participates in DevTools/Angels networks.
- Organizer/curator of community events targeted at AI engineers, including the AI Engineer World’s Fair and AI Engineer Summit.
Connections to other people and companies
- Deeply connected across the developer tools and AI ecosystems; notable companies in his network include Netlify, temporal, Airbyte, Railway, Supabase, Replay.io, Stackblitz, and others he has invested in or collaborated with.
- Engages with a broad community of practitioners through Latent Space channels, Paper Club, conferences, and social platforms (Twitter/X, GitHub, YouTube).
- Frequently collaborates with researchers, founders, and developer advocates to surface practical workflows for shipping AI systems.
Expectations for the future
- Likely to continue shaping the AI engineering discipline by: curating high-signal research; building and evangelizing tooling and best practices for LLM/data pipelines; and organizing community touchpoints for practitioners.
- His mix of product/infra experience and community reach suggests continued influence on how organizations staff and structure AI engineering teams (e.g., roles, career ladders, operational practices).
- Continued investment and advisory activity in early-stage developer tooling and AI infrastructure companies.
Interests
- Developer experience (DX): improving tooling, docs, onboarding, and long-term DX for teams shipping large-scale systems.
- AI engineering: productionizing models, data pipeline reliability, observability, and automation for the LLM era.
- Community-building: creating shared learning spaces (podcasts, clubs, conferences) to accelerate practitioner knowledge exchange.
- Career development and mentoring: writing and teaching materials to help engineers grow their careers.
Practical pointers (how to follow his work)
- Subscribe to Latent Space (podcast & newsletter) for curated interviews and analysis on AI engineering topics.
- Follow Shawn on social platforms: Twitter/X (@swyx), GitHub (github.com/swyx), and his personal site (swyx.dev) for writings and links to talks.
- Explore Smol AI for projects related to LLM data pipelines and automation tools he is building.
Sources
- Latent Space (podcast & platform) — primary outlet for interviews and curator content about AI engineering.
- Smol AI — startup founded by Shawn focusing on LLM/data pipeline products and automation.
- Public writing and essays by Shawn (e.g., “The Rise of the AI Engineer”, Coding Career Handbook).
- Public profiles and social accounts (Twitter/X: @swyx, GitHub: swyx) and conference pages/listings for AI Engineer events.