From Two Ladders to a Platform

The Orchestration Era started with a simple observation: engineering competency frameworks were built for a world where engineers write code. That world is ending. So we built two new ladders (one for ICs, one for people leaders) and published them for free. Then something interesting happened.

The Conversations We Didn't Expect

We expected engineering leaders to engage with the frameworks. They did. But the conversations that surprised us came from product leaders, design directors, and heads of data science, all saying some version of the same thing:

“This is exactly what's happening to my team too. Do you have anything for us?”

At first we thought these were adjacent problems with different solutions. But the more we listened, the more we realized: the abstraction line doesn't respect functional boundaries. It's rising everywhere that AI can absorb production work. And that's everywhere.

The Framework Explosion

So we built more. The AI-Native Product Manager Ladder. The Product Designer Ladder. The Data Scientist Ladder. A condensed 4-level Software Developer Ladder for flatter organizations. Test Engineering ladders. A Sysadmin/SRE ladder.

Each architecture follows the same methodology: take the traditional competency dimensions for a function, evaluate each one through the lens of “what happens when AI handles the production?”, and rebuild the framework around the competencies that remain uniquely human.

The dimensions are different for each function. A data scientist needs Statistical Reasoning & AI Foundations. A product designer needs Design Vision & AI Strategy. A product manager needs Discovery & Insight Generation. But the structural shift is identical: from producing artifacts to orchestrating outcomes.

From Frameworks to Platform

Publishing frameworks was the first step. But organizations don't just need to read about new competency standards. They need to operationalize them. That meant building tooling: org setup, guided assessments with detailed expectations, growth plans with radar profiles, 9-box talent grids, competency heatmaps, and team analytics. The core assessment platform.

But as we used the platform ourselves and talked to early users, we realized that assessing people against frameworks, even great frameworks, was only one part of what leaders need. The AI transformation isn't just about individual competencies. It's about organizational readiness. And it's about staying current when the ground is shifting weekly.

Three Pillars, Not One

That insight reshaped the product. Today the platform is built around three pillars:

• •Know your people. The original core, now expanded with AI coaching plans that generate personalized development guidance, review cycles with submissions and overrides for calibration season, and delegation for multi-manager organizations.
• •Know your organization. An AI Maturity Assessment that measures readiness across 10 business domains: software development, code review, testing, deployment, product decision-making, customer support, sales operations, content, security, and organizational change. The AI generates a coaching report with maturity scores, quick wins, and a phased roadmap.
• •Act on what's changing. Weekly AI intelligence briefings with coaching on every development: what it means for your business, how difficult it is to implement, and how long until you see value. Not a newsletter. Actionable advice for leaders.

AI Woven Throughout

We also realized AI shouldn't just be in the content of the frameworks. It should be in the platform itself. So we built four AI capabilities into the product: coaching plans that turn assessment data into development guidance, architecture generation that creates complete frameworks from a role description, the maturity assessment, and the weekly briefings.

And we couldn't build every architecture ourselves. Organizations have unique roles and domain-specific needs. So we built an architecture editor, an architecture marketplace where the community shares what they've built, and AI-powered generation that creates a complete framework from a plain-language description of a role.

What Stays the Same

The thesis hasn't changed. The abstraction line is still rising. Roles are still shifting from production to orchestration. And organizations still need frameworks that measure the competencies that matter in this new world.

What changed is the scope. It's not just engineering. It's not just two ladders. It's a leadership platform for organizations navigating the AI transformation: know your people, know your organization, act on what's changing.