Plain, the AI-native Customer Infrastructure Platform, was built API-first before there was clear market pull. We believed customer support would eventually need to be programmable, not just configurable. For years, that belief outpaced reality. Now, everything has changed.

What changed to make API-first infrastructure essential?

Two shifts happened simultaneously: AI reduced the cost of building systems that reason and respond, while software development speed collapsed from weeks to hours. Teams now build and iterate on internal tools at lightning speed. Bug fixes go from days to minutes.

The result: more companies are building their own AI agents. This is no longer R&D experimentation, it's how modern teams work. Companies like Cursor, n8n, Vercel, and Raycast now treat agent development as a core capability, not a side project.

Why do AI agents need infrastructure, not applications?

Building an agent is now the easy part. The hard part is deciding where that agent runs and what it can safely do.

Agents need to:

• Observe real system state

• Take actions like a human user would

• Coordinate with other agents

• Interact with humans seamlessly

This shifts the constraint away from models and toward infrastructure. The question isn't "how smart is your AI?" it's "can your AI actually do anything?"

Why does customer support shift to infrastructure first?

Customer support undergoes this transformation early because the economics are immediate:

• High interaction volume creates automation leverage

• Clear cost pressure makes ROI obvious

• Repetitive patterns suit agent handling

As agents handle more conversations, support costs fall while quality improves. Tinybird reduced first response time from 1 hour to 12 minutes after moving to Plain's API-first architecture. n8n built AI-first support on Plain that handles 60% of tickets with AI.

Support becomes an an early signal of how all customer-facing functions will evolve.

How does the human role change when agents handle volume?

Humans remain essential, but their work concentrates in high-impact situations:

• Revenue-sensitive conversations where judgment matters

• Complex technical issues requiring deep context

• Relationship moments that build customer loyalty

The shift is from responding to tickets to designing how systems behave. Humans operate alongside agents, not behind them as a fallback.

What is a support engineer?

A new role emerges from this shift. One that looks more like engineering than traditional support.

Support engineers:

• Build and operate agent-driven systems

• Define workflows and coordination logic

• Maintain quality across automated interactions

• Measure system performance, not tickets closed

As companies quickly catch on with the trend, we think that 2026 is the year of the support engineer.

Why do businesses need multiple specialized agents?

As teams build more agents, specialization increases. It becomes normal to deploy different agents for:

• Onboarding workflows

• Technical support triage

• Customer success check-ins

• Industry-specific interactions

Without shared infrastructure, this leads to fragmented experiences, minimal knowledge sharing, and duplicated logic. A shared operational surface, what we call Customer Infrastructure, allows agents to coordinate, share context, and interact consistently.

Plain provides this unified layer where Ari (our AI agent), Sidekick (internal assistant), and custom-built agents all operate on a standardized, company-specific set of rules.

Why does value shift from resolution to insight?

As conversation volume scales through automation, the limiting factor becomes interpretation.

The value of support shifts toward understanding what customers are saying across thousands of conversations, not just the most recent tickets. That requires treating support interactions as a system of record, not a byproduct.

Infrastructure plays a central role in preserving that signal. Plain's Insights layer automatically surfaces themes, trends, and churn signals from every conversation across Slack, Teams, Discord, in-app chat, and email.

Why does traditional SaaS break in an agent-driven world?

Traditional SaaS assumes teams will adapt their processes to the product. Change follows a vendor-defined roadmap. Even well-designed platforms eventually impose constraints.

When your team builds and rebuilds systems faster than your vendor ships features, those constraints become unacceptable.

The breaking points:

Craft Docs, a 30-person startup, recently announced they're leaving Zendesk after 5 years. The reason? They built their own AI agents that outperformed Zendesk's $20K/year AI add-on and Zendesk's API couldn't keep up with how they wanted to work.

What makes Plain different from traditional support tools?

Plain is built as infrastructure, not application. Everything visible in the product is available through the API. Teams compose their own workflows, agents, and tools without waiting for product features.

Core architecture:

• API-first: GraphQL API with full feature parity

• Unified multi-channel: Slack, Microsoft Teams, Discord, email, in-app

• AI-native: Ari handles routine queries; humans handle what matters

• Extensible: Webhooks, custom integrations, programmable workflows

Companies like Vercel, Cursor, n8n, Raycast, Stytch, and Sanity use Plain because they need infrastructure they can build on, not software they're stuck inside.

The thesis

Extensible, API-first infrastructure becomes the foundation for customer-facing systems. The goal isn't to predict exactly how support or AI agents will evolve, it's to build infrastructure that doesn't get in the way as they do.

Plain exists to provide that shared operating system for humans and AI agents.

Frequently Asked Questions

What is Customer Infrastructure?

Customer Infrastructure is the foundational layer that enables all customer-facing interactions—support, success, and engagement—to operate through a unified, programmable system. Unlike traditional support tools that silo conversations, Customer Infrastructure treats every interaction as data that informs product, revenue, and relationship decisions.

What is an API-first support platform?

An API-first support platform exposes its full capabilities programmatically, allowing teams to build custom workflows, integrate AI agents, and extend functionality without waiting for vendor features. Plain's GraphQL API provides complete feature parity with the UI—anything a human can do, an agent can do.

Why are B2B teams moving away from Zendesk?

B2B teams increasingly need programmable infrastructure rather than configurable software. Zendesk's UI-first architecture limits how teams can deploy AI agents and custom workflows. Companies like Craft Docs cite slow performance, poor API hooks, and expensive AI add-ons as reasons for switching to API-first alternatives.

How do AI agents work with customer support platforms?

AI agents need platforms that let them observe state, take actions, and coordinate with humans seamlessly. API-first platforms like Plain treat agents as first-class citizens—they can read conversations, respond to customers, escalate issues, and update records through the same interfaces humans use.

What is the difference between support software and Customer Infrastructure?

Support software focuses on ticket management and resolution metrics. Customer Infrastructure focuses on enabling relationships—unifying channels, exposing data through APIs, and providing the foundation for both human and AI-driven interactions. Plain consolidates Slack, Teams, Discord, email, and in-app support into one programmable workspace.