2027.dev is a foundational piece of infrastructure for the AI agent ecosystem, specifically addressing the interface between agents and the tools they use. While many companies focus on building the agents themselves, 2027 focuses on the environment the agents inhabit. They define the standards for "Agent Experience" (AX), ensuring that software, APIs, and documentation are compatible with autonomous machine logic.
By providing a public leaderboard and a certification framework, 2027 acts as a bridge between agent developers and software providers. For those building agents, 2027 identifies which tools are safest and easiest for agents to integrate. For software providers, it provides a roadmap for becoming a preferred tool in an agent-led development cycle. They are effectively championing the shift toward machine-readable software ecosystems.
2027.dev operates on the thesis that by 2027, autonomous agents will write and maintain the majority of all software. If this prediction holds, the way companies think about their users must change. While the last decade focused on Developer Experience (DX)—prioritizing readable fonts, intuitive dashboards, and clear prose for humans—2027 argues that these metrics are irrelevant to the new power users: AI agents. Agents do not read documentation to learn; they parse it to execute tasks. If they hit a confusing error message or a missing API parameter, they stall. 2027 is building the measurement infrastructure to identify and fix these specific failure modes.
The company describes its platform as the "SOC 2 for agent readiness." This is a calculated piece of positioning. SOC 2 is the standard that software companies use to prove their security posture to enterprise buyers. By adopting this language, 2027 aims to make agent-compatibility a similar gatekeeper for adoption. The idea is that in the near future, an agentic IDE or a coding assistant like Cursor or Claude Code will check a product's agent-readiness score before deciding whether to use it in a build. A low score becomes a distribution bottleneck.
The core of the platform is AX Evals, an automated testing system that uses real AI agents to interact with software. Instead of synthetic tests, 2027 gives an agent a task—such as "set up a hello-world project with this email provider"—and records the interaction. The platform measures five primary metrics:
These metrics aggregate into a score that appears on the Agent Arena, a public leaderboard. This creates a transparent ranking of devtools and APIs, allowing companies to see where they sit relative to competitors.
2027 highlights a shift in distribution channels. As tools move from copilots (offering suggestions) to autonomous agents (executing code), they become the primary deciders of which libraries or APIs are included in a project. If a product’s documentation is only legible to humans, it is effectively invisible to autonomous agents. To address this, the company offers 2027 Track, an open-source npm package that detects AI agent traffic on documentation sites. This gives product managers data on how much of their traffic is already machine-driven, helping them justify the investment in agent-readiness before it becomes a critical failure point.
Automated evaluation platform with agent traces and waterfall timelines.
2027.Dev is hiring.