---
title: "How we secure Figma’s internal systems with agents"
url: https://daily.dev/posts/how-we-secure-figma-s-internal-systems-with-agents-0csav3m0f
source_url: https://www.figma.com/blog/how-we-secure-figmas-internal-systems-with-agents
type: article
source: "Figma"
published: 2026-07-29T21:19:05.798Z
updated: 2026-07-29T21:30:06.967Z
tags: ["security", "ai-agents", "rag", "snowflake"]
reading_time: 21
upvotes: 0
comments: 0
language: en
---

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# How we secure Figma’s internal systems with agents

**[Figma](https://daily.dev/sources/figma)** · 21 min read · 0 upvotes · 0 comments

## Summary

Figma's security engineering team built an AI-powered agentic system to handle internal security alert triage, reducing time-to-resolution by 71% and on-call pages by 20%. The system layers a RAG-based alert memory (using AWS Bedrock and Amazon Kendra) with an agentic investigation layer (via Tines and Claude models) that can query a Snowflake security data lake, look up Okta/Wiz/Santa data, and automatically open PRs to fix false positives. Key design decisions include separating memory into case memory (historical alerts), steering memory (behavioral rules), and procedural memory (self-built schema knowledge), plus deterministic guardrails like auto-drafting all agent-created PRs. The agent now handles all initial security response, shifting on-call engineers from investigation to review and judgment.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.figma.com/blog/how-we-secure-figmas-internal-systems-with-agents>

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---

Tags: [#security](https://daily.dev/tags/security), [#ai-agents](https://daily.dev/tags/ai-agents), [#rag](https://daily.dev/tags/rag), [#snowflake](https://daily.dev/tags/snowflake)

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