Why Every AI Agent Needs Its Own Computer | Ivan Burazin (Daytona)
If AI agents are the new digital knowledge workers, where exactly do they do their work? In this episode of the MAD Podcast, Ivan Burazin joins us to unpack the emerging infrastructure stack for AI agents and explain why every agent needs its own secure, stateful "computer." We explore the technical realities of sandboxes, dive into why legacy, stateless hyperscalers weren't built for these new workloads, and break down the mechanics of microVMs and custom schedulers alongside a contrarian prediction on an impending CPU shortage. Finally, Ivan delivers an absolute masterclass on product-led growth, community building, and go-to-market strategy for technical founders.
Ivan Burazin
LinkedIn - https://www.linkedin.com/in/ivanburazin
X/Twitter - https://x.com/ivanburazin
Daytona
Website - https://www.daytona.io/
X/Twitter - https://x.com/daytonaio
Matt Turck (Managing Director)
Blog - https://mattturck.com
LinkedIn - https://www.linkedin.com/in/turck/
X/Twitter - https://x.com/mattturck
FirstMark
Website - https://firstmark.com
X/Twitter - https://x.com/FirstMarkCap
Listen on:
Spotify - https://open.spotify.com/show/7yLATDSaFvgJG80ACcRJtq
Apple - https://podcasts.apple.com/us/podcast/the-mad-podcast-with-matt-turck/id1686238724
00:00 Intro
02:13 What is an AI agent sandbox?
03:17 Security risks of running agents locally
05:17 Stateful vs. stateless hyperscalers
07:04 The history of cloud IDEs and the end of localhost
09:45 Do all AI agents need a sandbox?
12:26 Sandbox use cases: RL evals & background agents
14:10 Unpacking the emerging AI Agent Stack
16:20 The unsolved problem of agent memory and learning
19:37 Where sandboxes fit in the agent harness
21:35 OpenAI, Anthropic, and agent SDKs
23:06 Ivan's founder journey: From CodeAnywhere to Daytona
26:59 GTM strategies and building developer communities
33:48 Why customer support is your best GTM strategy
35:34 Leveraging Twitter during the AI super cycle
40:50 The technical anatomy of a sandbox
41:53 Why fast sp
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Chapters (17)
Intro
2:13
What is an AI agent sandbox?
3:17
Security risks of running agents locally
5:17
Stateful vs. stateless hyperscalers
7:04
The history of cloud IDEs and the end of localhost
9:45
Do all AI agents need a sandbox?
12:26
Sandbox use cases: RL evals & background agents
14:10
Unpacking the emerging AI Agent Stack
16:20
The unsolved problem of agent memory and learning
19:37
Where sandboxes fit in the agent harness
21:35
OpenAI, Anthropic, and agent SDKs
23:06
Ivan's founder journey: From CodeAnywhere to Daytona
26:59
GTM strategies and building developer communities
33:48
Why customer support is your best GTM strategy
35:34
Leveraging Twitter during the AI super cycle
40:50
The technical anatomy of a sandbox
41:53
Why fast sp
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