SaaS product and engineering teams are under pressure. Customers don’t just want AI features on a roadmap; they expect AI agents embedded directly into your product, capable of taking action, automating workflows, and connecting to systems they already use.
But the path forward isn’t clear. Most teams feel boxed into bad options: quick chatbots that produce fragile, low-value agents, or massive platform rebuilds that nobody has time for. The result? Stalled momentum and uncertainty about what actually matters.
This post offers a practical framework to help SaaS leaders understand where they are in their AI agent journey—and the capabilities and infrastructure typically needed at each stage.
The 3 stages of the agentic journey
Stage 1: Explorers
Explorers are SaaS teams still experimenting with AI concepts. They don’t have production agents yet, but are actively discussing copilots and other AI-powered features. The big question on their minds: How do we make AI actionable inside our product? And the follow-up: How should our product connect to customers’ systems?
“The optimists proved to be too optimistic—AI cannot do anything and everything. However, the pessimists are equally too pessimistic—AI is not just a toy or a super-search engine.” — Nam Le, Workato SVP and Head of Embed Business Unit
Explorers often get stuck in endless demos that never reach production. They’re swimming in tool overload without a clear outcome, and they can’t pinpoint a starting point for scalable agent design.
What they really need is a strong foundation:
- Clarity on early agent use cases
- Exposure to orchestration concepts
- Understanding of when managed infrastructure will outperform DIY experiments
Explorers aren’t asking about MCP yet. They’re asking what AI could do.
Stage 2: Builders
A bit further along than Explorer, Builders may already have agents deployed in production, but they’re struggling to deliver meaningful value. In short, they’ve built agents that aren’t doing enough. Meanwhile, their customers want deeper, cross-system workflows, and the early enthusiasm is meeting reality fast.
“MCP feels like the GenAI and agentic journey growing up in the most meaningful way since its release.” — Nam
This is where things can get messy. When agents deliver isolated outcomes and one-off integrations multiply, credential handling and security risk increases. So when customers demand automation across systems, Builders struggle to keep up.
Teams at this stage may turn to popular agent frameworks to move faster. In practice, those tools offer enormous flexibility, but at a cost: heavy technical overhead, slower speed to market, and accumulated tech debt that comes from building and maintaining agent infrastructure in-house.
What Builders really need is orchestration that absorbs the “gotchas” agents introduce, including rate limits, retries, MFA, compliance checks, and secure access to customer systems without hard-coding fragile logic into agents.
Builders may not mention MCP or orchestration explicitly, but they’re wrestling with the problems orchestration solves: ungoverned tool access, fragile cross-system workflows, and security risks that emerge when agents connect to multiple systems.
Stage 3: Leaders
Leaders are mature SaaS teams building AI-native products at scale, often with enterprise customers driving requirements. They’re asking: How do we build an agentic strategy that’s secure, governed, and future-proof?
Leaders are also grappling with the other side of the equation: how do they make their platform accessible to customers’ own agents—ensuring those agents can reliably connect to and take action within their product.
“Customers don’t care about the industry’s struggles—they believe, expect, and demand the hype, and that isn’t changing.” — Nam
Leaders face immense pressure from a governance, compliance, and observability standpoint. They’re focused on coordinating multiple agents across tools, scaling, and actively avoiding commoditization as agents become the interface. And their biggest constraint is a familiar one: Integrations. Integrations. Integrations.
“Now that organizations, platforms, and products can have a number of agents to carry out a host of processes, the need for deep integrations can unlock the most complex orchestration challenges—or leave any ambitious project in a lurch.” — Nam
SaaS platforms at this stage need enterprise-grade orchestration and deep cross-system agent tools—not single-vendor MCP servers that only expose one system’s capabilities. For example, Leaders need agents that can orchestrate across Salesforce and NetSuite and Slack in governed, multi-step workflows. That requires a scalable foundation that keeps their platform at the center of every customer workflow.
Why orchestration is critical
As SaaS teams move through these stages, they quickly realize that building a chatbot is very different from building an enterprise-ready agent. Complexity shows up in the form of rate limits and retries, credential and identity sprawl, and multi-step workflows that fail halfway through—all of which drive up cost and degrade reliability.
When agents can call dozens of MCP tools directly—without centralized credential management, rate limiting, or audit trails—these problems compound at scale.
This is where Workato’s Enterprise MCP for SaaS Platforms shines.
While the MCP protocol provides a standard way for agents to access tools, Workato’s Enterprise MCP adds the orchestration layer SaaS platforms need: rich multi-step skills, secure credential management, governance, and the connectivity to make agents trusted to take action.
So when that customer asks an agent to update a deal in Salesforce, notify the team in Slack, and trigger a workflow in NetSuite, Enterprise MCP handles the credentials, sequencing, error handling, and audit trail automatically—without your engineering team hard-coding fragile logic for every integration.
“No shortcuts. We all understand that the real staying power of every SaaS company is to tackle the hard problems.” — Nam
Foundation matters at every stage
Whatever stage you’re in, the key is starting with the right baseline:
- Explorers don’t need to rush
- Builders don’t need to rip and replace
- Leaders don’t need to out-innovate the ecosystem overnight
What matters is choosing an approach that lets agentic capabilities evolve alongside your product—without locking you into brittle integrations or unsustainable infrastructure.
As AI agents move from novelty to necessity, the SaaS platforms that win will be the ones that make action reliable, governance invisible, and scale a feature, not a rewrite.
Schedule a demo to learn more about Enterprise MCP for SaaS Platforms.