For years I made the canvas easier to draw on. Then agents arrived — and the canvas wasn’t holding flows you draw anymore, it was holding things that act on their own. This was the net-new product where I redesigned the canvas around that shift, authored the framework behind it, and made one call against the whole field: I turned the flow top to bottom. Shown at the Informatica World 2025 CEO and CPO keynotes.
Agents changed what a canvas is for. I started from a question nobody had a clean answer to — when the canvas holds agents that act, not flows you draw, what should it look like? I authored CHESS to answer it, and made the keystone bet: flip the orientation top-to-bottom, backed by research. A net-new product — 347 → 1,938 preview registrations in 30 days, 630+ weekly active users. Here’s the whole thing — jump in anywhere.
Process Diagrammer made the canvas usable at scale — the surface where people draw enterprise workflows, from loan approvals to real-time fraud detection. Then agentic AI arrived. Agents could reason, call tools, and act on their own, not just sit as nodes you wire by hand. Being agentic means more than wrapping APIs in an MCP — it means applying agentic principles across an asset’s whole lifecycle.
What changed is capability: agents got good enough to plan, reason, and call tools on their own — so the canvas’s job moved from drawing a flow to orchestrating agents. This was the net-new product built for that shift.
The stakes and scale are real: these workflows run regulated, high-volume processes — from loan approvals to fraud detection, scaling to 10,000 runs a minute. Designing a canvas where a human stays in command of agents that act on their own is the problem I set out to solve.
↑ back to the debriefI led UX end to end on the net-new agentic builder — the research, the CHESS framework I authored, the interaction model, and the narrative shown at the IW’25 CEO and CPO keynotes. Product and engineering owned scope, feasibility, and delivery. I name the split plainly because an honest account is more useful than a flattering one.
The CHESS framework · the top-to-bottom orientation decision · the structure-and-delegation interaction model · the IW’25 keynote narrative · prior ownership of the Process Diagrammer canvas this built on.
No precedent — no one had designed an agentic canvas · a convention (left-to-right) I chose to break · a net-new 0→1 carrying a hard keynote date.
Three moves: a framework to reason by, the one orientation call that defined the canvas, and a structure for how humans and agents share the work.
I needed a way to reason about agentic interaction before drawing a single node. So I wrote one. CHESS gave the team a shared language for every decision that followed.
Every node canvas I knew ran left to right. I turned this one top to bottom — the riskiest call in the project, and the one I’m most sure of. The reasons stacked up: horizontal scrolling is disliked; large processes stay linear downward instead of sprawling sideways; left-to-right hits a width wall and wraps, breaking focus; and top-to-bottom mimics how real work reads — code, docs, and configs all run down the page.
| Tool | Orientation | Read |
|---|---|---|
| ServiceNow | Left-to-right (BPMN) | Standardized, but stagnated — lacks structure |
| Flowise AI | Multi-directional | Anywhere & everywhere — messy at scale |
| n8n | Left-to-right | Automation engineers |
| OnDemand.io | Left-to-right | RAG / LLM teams |
| BuildShip | Top-to-bottom ★ | Enterprise product teams — the match |
A planning agent is the orchestration brain: it runs at least once and, from the prompt, decides which tool or inline agent to invoke. Tools and inline agents sit on the right — pure delegation for execution. Supplemental text sits on the left — prompts, parameters, and course corrections that enrich the agent’s reasoning. A co-pilot surfaces suggestions and error-handling right where the user needs them. Two entry points keep the user in command: drop a tool on the main flow for a deterministic A→B→C, or delegate it to the planning agent and let the prompt decide the sequence.
What surprised me: breaking the left-to-right convention felt reckless — until the data backed it. Only 10% wanted to keep it. The lesson stuck: a strong convention isn’t the same as a strong preference.
↑ back to the debriefThe model lets a person build, connect, and govern agentic workflows without thinking in code — and stay in command of agents that act on their own. Five parts, at a glance:
This one has numbers, and they’re verifiable — a net-new product, launched at a global keynote, that grew quickly in preview.
This is where the canvas I’d specialized in grew a mind. Design’s job moved from drawing flows to orchestrating trust between a person and the agents acting on their behalf — and it set up the headless work that followed, when the canvas disappeared entirely.
What I’d do differently: V1 capped at three levels of execution to make the keynote date — I’d push for deeper nesting sooner. And I’d put the orientation flip in front of more enterprise hands before the launch, not just after.