Propel26 · San Francisco · May 2026

Design Before You Automate

Most implementation functions weren't designed for the customer. They were designed for the team running them. That's where it breaks — and it's also where AI adoption stalls. These were the three principles I used to fix it.

30 → 15 Time to first value (days)
9/10 Customer experience score
30% Time to live: reduced

These didn't come from adding AI. They came from fixing the design before touching automation.

Resource 1
Are you removing customer burden, or just managing it?

Principle 2: Lead with Expertise

Step 1: Who is this step actually designed for?

Pull up any step in your implementation process. Run it through these questions.

  • Is the customer being asked to figure something out you already know?
  • Are they waiting on guidance that should have been given proactively?
  • If this step failed, who would feel it most: you or them?

If the honest answer is that the step protects your execution more than it delivers their outcome, that's your first signal. All the right effort, wrong starting point.

Step 2: What outcome is this step responsible for?
The question we asked every single piece of our process: What's the customer outcome we're driving for?

Not what the step produces internally. Not what gets checked off. What does the customer feel, know, or become able to do because this step happened? If you can't answer that clearly, the step isn't designed for the customer yet.

Step 3: Apply the 100% burden test

Assume you have to absorb everything currently sitting with the customer. All of it. Then ask:

  • How would we solve this if it was entirely our responsibility?
  • Where could we pre-build, pre-answer, or pre-solve instead of waiting?
  • Where are we project managing when we should be advising?

Walk it back only where you genuinely can't solve it yet. That gap is your build list.

Step 4: Check your stance

In your kickoffs and touchpoints, which describes how you show up?

→"What do you want to do?" / "Here’s this cool feature, how do you want to use it?" / "Can you fill out this spreadsheet?" You’re waiting. The customer is carrying the burden of direction.
→"We recommend…" / "Based on your use-case, you should…" / "Here is the next step for you." You're leading. The expertise is yours to give.

That shift, from coordinator to advisor, is the whole game. It changes what customers expect, and what they trust you with.

Resource 2
Before you automate anything, place it.

Principle 3: Let Automation follow Clarity

Most teams introduce AI before they understand what their processes are actually doing. The result isn't efficiency; it's faster confusion. AI didn’t find its home in our implementation until we knew our process well enough to know where it didn’t belong. Here’s the filter we used.

START HERE: Is it customer-facing?

→If not, it’s a candidate for automation.
→If yes, keep it human for now.

THEN ASK: Is it high effort and repeated?

→If yes, assist with AI. Avoid direct automation.

LAST: Is it accurately defined?

→If yes, it’s ready for automation.
→If no, design first.
AI Driven
Operational. Repeatable. Internal.
Consistency matters more than judgment. The human executing this isn’t adding value; they’re running a pattern AI can run better.
ExamplesHandoff documentation. Automated customer program V1 builds. Milestone update generation.
AI Assistance
Multiplying expertise.
Human judgment drives the outcome. AI extends the reach or quality of that judgment. The human stays accountable for the output.
ExamplesAuto-building tailored worksheets. Processing customer documentation. Expanding expertise recommendations.
Human Only
Presence is the point.
The human is the product. The customer needs to feel the expertise, not just receive it.
ExamplesLive training sessions. Validating customer decisions. Building confidence at critical moments.
Run this with your team

List your top 10 implementation activities. Place each one: AI Driven, AI Assistance, or Human Only?

  • →Where humans are doing AI Driven work: that’s your first automation opportunity
  • →Where Human Only work has already been automated: that’s your first quality risk
  • →Where AI Assistance could extend your team but hasn’t: that’s your next build priority

Efficiency followed. We didn’t chase it. We earned it.

AI amplifies what you give it. If your process isn’t clear, you’re just making the confusion faster.

This came from 18 months of rebuilding Zappi’s implementation function from scratch — starting with customer outcomes, not internal efficiency. If you want to go deeper or talk through how this applies to your team, find me on LinkedIn.

See how I think about AI Connect on LinkedIn ← Back to merlin-komenda.com