Cover Image for Built with Moss: How Aside Gives AI Agents Memory
Cover Image for Built with Moss: How Aside Gives AI Agents Memory
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The retrieval layer for production AI. Sub-10ms search without vector databases or bottlenecks.
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Built with Moss: How Aside Gives AI Agents Memory

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​AI agents are getting better at completing tasks, but they still struggle with one fundamental problem: remembering what happened before.

​In the next session of our Built with Moss series, we're joined by Jun Kim, Co-Founder & CEO of Aside, to go behind the scenes of how they built memory for AI agents using Moss.

​Aside turns your browsing history and past tasks into persistent memory, so your agent can remember the sites you use, the work you've already done, and the context behind previous tasks. Instead of starting from scratch every time, your agent can pick up where you left off.

​We'll talk about:

  • ​Why memory is becoming such an important part of building useful AI agents

  • ​How Aside turns browsing history and past tasks into useful context

  • ​How memory learns from each task and gets better over time

  • ​How Aside built and deployed memory in production with Moss

  • ​The technical challenges of storing, retrieving, and maintaining agent context

  • ​What they've learned from building agents that need to remember your work

  • ​Where they see agent memory going next

​We'll also get a look at Aside's memory experience and how it works in practice.

​Who should attend?

  • ​AI founders building agentic products

  • ​AI engineers working on agents and memory

  • ​Engineers building browser agents or computer use systems

  • ​Product engineers working on AI powered workflows

  • ​Teams thinking about long term context and personalization for agents

​We'll wrap up with live Q&A, so bring your questions.

​Built with Moss is a series featuring teams building and shipping real AI products in production with Moss.

Avatar for Moss
Presented by
Moss
The retrieval layer for production AI. Sub-10ms search without vector databases or bottlenecks.
175 Went