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Instagram has modernized its user interface with a native AI architecture, reducing token costs by 33%.

Instagram Direct migrated its Android user interface from the legacy Android View system to Jetpack Compose, thereby creating an AI-native UI codebase that makes it easier for AI coding agents to understand, modify, and maintain.

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Instagram Direct migrated its Android user interface from the legacy Android View system to Jetpack Compose, creating an AI-native UI codebase that makes it easier for AI coding agents to understand, modify, and maintain. According to Instagram engineers, this migration reduced the UI codebase by 50% and lowered token costs per AI agent session by 33%.

A key insight shared by Instagram engineers is: “Designing an AI-native architecture delivers significant benefits.” Rather than adopting a piecemeal approach—requiring developers to migrate components one by one—they focused on evaluating whether the underlying architecture would facilitate generating correct implementation solutions. In fact, as they pointed out, “AI tools often choose the path of least resistance,” which can easily lead to hidden bugs, technical debt, and performance degradation.

Instagram engineers explained that optimizing the codebase for AI means establishing appropriate architectural boundaries in state management, predictable behavior, and development patterns, thereby turning the AI agent’s “path of least resistance” into the route toward optimal transformation outcomes. Their goal isn’t simply to let AI compensate for design flaws; instead, they aim to design the codebase based on an understanding of how AI agents actually modify code:

AI agents naturally gravitate toward the path of least resistance. Therefore, during design, it’s crucial to ensure that this path ultimately produces correct, high-quality code while making poor design decisions both difficult to implement and costly.

Another key principle is minimizing contextual dependencies. In other words, AI agents should no longer rely on knowledge specific to a particular codebase but instead prioritize proven best practices and familiar patterns, helping them generate more reliable results.

This migration was completed smoothly without disrupting the team’s regular workflow, allowing engineers to continue releasing new features throughout the process. AI-assisted workflows have been standardized, promoting consistency and ensuring alignment with the team’s established architectural guidelines and best practices.

By adopting this approach, migrating to Jetpack Compose reduced the UI codebase by 50%, while also cutting AI agent execution time by 35%, lowering token costs per agent session by 33%, and decreasing the number of interactions between engineers and agents by 32%.

A major challenge was ensuring that the migration would not result in performance degradation. The team focused on three key production metrics: interaction response time—the time from opening a screen until it becomes usable; full load time—the time required for all screen content to finish loading; and scroll performance—measuring how smoothly screen content scrolls.

In production, these metrics are tracked via runtime monitoring, enabling A/B testing to compare the migrated Compose UI against the legacy UI and assess the migration’s impact on performance.

An important finding by Instagram engineers was that reliable performance evaluation could only be achieved once the entire screen had been migrated to Compose, thereby eliminating any legacy View components that might distort performance measurements.

This meant abstracting Compose UI components from their underlying framework while maintaining compatibility with RecyclerView and LazyColumn. Equally important was the ability to toggle between the two at runtime using feature flags, facilitating A/B testing.

Ultimately, the team replaced the traditional RecyclerView—which had initially been retained as a container for new Compose composables—with LazyColumn, the native Compose solution designed for efficiently rendering scrollable lists.

Finally, it’s worth noting that this migration also improved the startup performance of other parts of the app. Part of the reason is that Compose’s runtime warm-up overhead needs to be borne only once per app session, allowing other Compose-based interfaces to leverage the already-initialized runtime environment without incurring that cost again.

Original article link: https://www.infoq.com/news/2026/10/instagram-compose-migration/

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