EventStorming for Agentic AI: From Alignment to Action

The shift to agentic systems isn’t theoretical anymore. Brands are experimenting with autonomous workflows, adaptive experiences, and multi-agent collaboration to relieve pressure on teams and unlock growth. But the toughest part isn’t the technology— it’s knowing where to start. EventStorming is the quickest path to that answer. It pulls cross-functional knowledge onto the table and gives teams a shared view of where human effort is carrying unnecessary weight and where intelligent agents can take the load.

EventStorming was built to reveal the truth about how work actually flows, not the polished version captured in process diagrams. It’s fast, messy, and incredibly effective at breaking down silos.

When a room of merchandisers, content leaders, engineers, operators, and analysts map their world event-by-event, the gaps show up immediately: stalled handoffs, manual steps, inconsistent inputs, dependency bottlenecks. These friction points make perfect candidates for agent intervention because they're already felt by the people who live them every day.

For organizations just starting their agentic journey, this matters. You’re not trying to create sci-fi automation. You’re looking for places where agents can observe, decide, or act in ways that remove existing pain. EventStorming surfaces those spots on its own, and builds buy-in in real time.

First and foremost: keep the scope tight and the group small. Eight to twelve people who collectively own a discrete journey is ideal: content from idea to publication, merchandising from planning to go-live, fulfillment from cart to doorstep. Too broad and you lose the momentum that makes the format valuable.

Next up you’ll need four simple note types to keep things organized as you power through each piece in rapid succession. Orange is for domain events; blue is for systems, commands, or policies; purple is for pain points; and green is for agent opportunities.

With those, you’ll move through three fast passes:

Pass 1: Raw Events Everyone adds orange notes for every action within the flow. Don’t debate. Don’t refine. Capture the reality as quickly as you can and then add the next event you can think of.

Pass 2: Structure and Systems Organize the timeline by grouping all your events into a sequence, then layer in blue notes to identify systems and points of dependency. This is where missing context or awkward handoffs start to stand out.

Pass 3: Pain Points and Agent Opportunities Have participants mark purple notes where things break, slow down, or require judgment calls no one has documented. Then ask: Could an agent reasonably observe this, make a decision, or take action here? Those become green notes, aka your future intelligent agents.

Because today’s agents can reason across systems using plain-language instructions, even non-technical participants can describe handoffs without feeling out of their depth. The result is shared understanding and a list of opportunities the whole team believes in.

By the end of the workshop, you’ll see clusters of purple notes. Those are your first backlog items— the real, high-friction problems that agents can solve.

Capture each cluster with a simple structure:

• Proposed agent role (e.g., “auto-enrichment assistant” or “availability signal monitor”)
• Success metric (e.g., “reduce content lead time by 30%”)
• Governance requirement (e.g., “human approval for SKUs with margin above X%”)

Pick one to start. Our recommendation is to look for something meaningful but low-risk. (A quick win builds trust far faster than a massive, multi-quarter initiative.)

You don’t need a full enterprise blueprint to explore intelligent agents, you just need clarity. Translate your sticky note clusters into a simple architectural snapshot:

• What triggers this workflow?
• Where does context need to persist?
• Which APIs, tools, or data sources does the agent rely on?
• Where is human oversight required?
• What is the ideal handoff between human and agent?

This “architecture on a page” becomes the fastest way to get engineers, product managers, and business owners aligned around what you’re actually building. The goal here is to gain clarity, not to attain perfection.

The first version of any agent should be intentionally small. Ship it to a limited team and then evaluate, pairing hard data with qualitative feedback. Ask the people using it every day: When does the agent help? When does it get in the way? Where do you trust it and where do you not?

Build light guardrails—permissions, fallback logic, approval steps—and revisit them as confidence grows. Every four weeks, review your data, tune the prompts, and update your assumptions. This iterative cycle is how agentic systems become reliable, scalable tools instead of disconnected experiments, and you can leverage tools like LangSmith to help track agents and support outcome evaluation.

Things won’t always be perfect, but you can sidestep some of the biggest challenges with a little foreknowledge and smart planning. A few troublesome patterns show up again and again:

1. Trying to automate everything at once. You’ll move slowly and lose momentum.
2. Skipping ownership. Every agent needs a champion who understands its purpose and its boundaries.
3. Ignoring governance until it’s too late. Bring risk and compliance into the process early, not as a late-stage gate.

Momentum comes from clarity and focus, not scope.

You don’t need a massive transformation plan to get started. You just need a path that keeps moving:

Align: Run the EventStorming session. Pull in the right voices and build a shared view of the work.

Prioritize: Turn friction points into a backlog. Choose one pilot with high impact and low risk.

Design: Define the agent’s role, KPIs, guardrails, and human/agent collaboration model.

Build: Ship something lightweight with observability built in from day one.

Iterate: Refine based on data and feedback. Scale what works, sunset what doesn’t.

Sticky notes don’t just reveal the story, they build momentum. When teams co-create the path forward, the case for intelligent agents stops being hypothetical. It becomes obvious.

And once your organization has a pilot running in production, you’re no longer “exploring what agents could do.” You’re delivering agentic experiences that make life easier for your teams and more seamless for your customers.