The new AI app stack
from Practical AI Hosted by Daniel Whitenack and Chris Benson
Recently a16z released a diagram showing the “Emerging Architectures for LLM Applications.” In this episode, we expand on things covered in that diagram to a more general mental model for the new AI app stack. We cover a variety of things from model “middleware” for caching and control to app orchestration. 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.com 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. Typesense – Lightning fast, globally distributed Search-as-a-Service that runs in memory. You literally can’t get any faster! Changelog News – A podcast+newsletter combo that’s brief, entertaining & always on-point. Subscribe today. Featuring: Chris Benson – Website, GitHub, LinkedIn, X Daniel Whitenack – Website, GitHub, X Show Notes: Emerging Architectures for LLM Applications Upcoming Events: Register for upcoming webinars here!
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Chapters
- 0:07 Welcome to Practical AI
- 0:43 Deep dive into LLMs
- 2:24 Emerging LLM app stack
- 4:35 Playgrounds
- 8:06 App Hosting
- 10:45 Stack orchestration
- 15:50 Maintenance breakdown
- 19:08 Sponsor: Changelog News
- 20:43 Vector databases
- 22:36 Embedding models
- 24:27 Benchmarks and measurements
- 26:59 Data & poor architecture
- 29:41 LLM logging
- 33:00 Middleware Caching
- 37:31 Validation
- 40:53 Key takeaways
- 42:35 Closing thoughts
- 44:22 Outro
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