What we've learned scaling AI coding agents at Spotify

Every CTO I speak with has moved past the adoption question. Their engineering organizations are using AI coding agents daily. But the landscape beneath them is in constant motion with new models, new agents, rising costs, pricing structures that shift quarter to quarter, and capabilities that advance overnight.

The real challenge is no longer velocity alone. It is ensuring teams have the flexibility to adopt whatever maximizes value at any given moment, without accumulating vendor dependency or compounding costs as you scale.

At Spotify, with thousands of engineers operating across hundreds of teams, this tension defines how we approach our development infrastructure. Our engineers require the autonomy to adopt the best available tool for their work, and what qualifies as best evolves rapidly. But autonomy without structure produces fragmentation, duplicated effort, and inconsistent outcomes. Reconciling that tension is what has driven our approach.

#From one agent to thousands of sessions

The progression was predictable in hindsight. Teams began with a single agent. One session, one developer, one task. Then adoption accelerated.

Engineers, and later on non-engineers, started orchestrating multiple agents in parallel, across different sessions and tools, repositories, and branches. Context accumulated in one session but was needed in another. Institutional knowledge fragmented into individual configurations — CLAUDE.md files, bespoke MCP setups, personal prompt libraries — making it harder to carry that context across teams and workflows.

The resulting entropy impacted productivity. PRs increased, but so did rework, inconsistency, and wasted tokens. Agents in one session would expend cycles rediscovering what another session had already resolved.

Moreover, engineers were investing as much effort reconstructing context as they were on building new capabilities. And at the organizational level, creating greater visibility across thousands of concurrent sessions became an increasingly important priority.

This was not a new class of problem for us. A decade ago, the complexity of thousands of engineers operating across thousands of services produced the same category of fragmentation. That is why we built Backstage, a unified, structured source of truth for how our systems interconnect: dependency maps, component metadata, ownership, architectural decisions. Backstage became the foundation of our internal developer platform, and we subsequently built Portal, so any organization can get the same benefits without managing the infrastructure themselves.

AI coding agents have introduced an entirely new dimension of that same organizational complexity. It requires its own solution.

#Enter Xirp

Xirp is a vendor-neutral agentic development environment born out of a concrete engineering need.

Xirp was built to help our developers manage dozens of concurrent agent sessions across multiple harnesses (Claude Code, Gemini CLI, Codex, etc.), making it tenable to coordinate 50+ parallel sessions. Every session operates in its own worktree, enabling dozens of agents to work concurrently on the same codebase without interference. Context is decoupled from any single agent or harness; switch tools mid-project, and the full working state carries over. Vendor neutrality is an architectural requirement that emerged directly from how our engineers work.

From a strategic perspective, this is precisely the capability needed across our organization: the freedom to leverage the best available tool at any given moment, without incurring a migration cost every time the ecosystem evolves. Xirp lets our engineers switch models mid-task and route every job to the best available price performance, including open source models that we host ourselves, so that we are never locked in.

When a new model emerges, our engineers transition without reconstructing their environment. They are able to move fluidly between coding agents, preserve context across sessions, and orchestrate parallel workstreams.

We're seeing good validation internally: thousands of Spotify engineers have organically adopted Xirp across more than 36,000 sessions, resulting in faster context switching and cost efficiencies.

#Xirp + Portal: the multiplier effect

Xirp on its own addresses the multi-agent orchestration challenge, and when paired with Portal, it becomes a true agent command center.

When Xirp connects to Portal, every agent session initializes with organizational context drawn from your software catalog: component architecture, dependency graphs, ownership topology, and the architectural decisions that govern how systems interrelate.

The result is a shared institutional baseline your entire engineering organization operates from. The same structured knowledge that made Backstage transformative for human engineers now makes AI agents dramatically more effective.

The value compounds in both directions. After each session, transcripts and metadata flow back into Portal, providing comprehensive visibility across the organization: what has been accomplished, who is working on what, and where to resume. Any engineer or agent can pick up where another left off, because the full working context is preserved in Portal.

Work becomes interchangeable across the team. Duplicate effort is eliminated. The institutional knowledge that one engineer's agent session produces becomes immediately available to every subsequent session across the team.

Consider the skills, rules, plugins, and MCP configurations that every team develops independently. Portal consolidates it into a curated marketplace where teams contribute, discover, and build upon each other's work. For teams that prefer to operate directly within their agent of choice, Portal's MCP tools surface the same organizational context natively within any coding session.

#Build, experiment, and ship like Spotify

Spotify's engineering culture was built on a conviction: give teams the autonomy to move fast, but invest in the shared infrastructure that makes that speed sustainable. We applied that principle to developer experience with Backstage and Portal, to product development with Confidence, our experimentation platform, and now to agentic software development with Xirp and Portal.

The organizations that learn fastest, that compound their engineering knowledge into shared, structured systems rather than leaving it scattered across individuals, will be the ones that capture the full value of AI-assisted development. We have proven that pattern at scale. Now we're shipping that expertise to you.

Xirp delivers value as a standalone agentic development environment today. Connect it to Portal, and organizational context becomes the multiplier, compounding the effectiveness of every agent, every session, every team.

To learn more or try it for free, visit xirp.spotify.com.