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It’s not easy to plan right now. AI is reshaping how markets behave, how buyers decide, and how organizations execute. That means our plans are only ever as good as the knowledge we have at the time. By the time execution is underway, new information, new capabilities, and new dynamics often make the original goal feel outdated.
When I began building Revenue Funnel in 2020, I found myself leaning — unknowingly — on principles of effectuation. Strategy felt scrappy, messy, and constantly in motion. I wasn’t following a polished playbook. I was adapting, reframing, and reimagining goals based on what emerged along the way. Only later did I realize this approach echoed Saras Sarasvathy’s work on effectuation: starting with the means at hand, acting, and letting outcomes evolve.
Recursive Outcomes Thinking™ is my attempt to make that scrappy reality more explicit. It’s not polished theory. It’s me thinking out loud, trying to capture how strategy actually unfolds in an AI-driven, fast-shifting environment.
Why Traditional Goals Break in the AI Era
Traditional strategy assumes a static endpoint. You define the destination, then work backward (Champy’s right-to-left thinking). That works in stable markets. But in AI-driven GTM environments:
New ICP segments emerge mid-cycle
Execution uncovers new data that reshapes ambition
Autonomous tools create capabilities you didn’t plan for.
Clayton Christensen taught us that disruption often blindsides incumbents because they optimized toward the wrong goal. Rita McGrath argued that competitive advantage is now transient. AI accelerates both realities. The danger today isn’t poor execution — it’s chasing yesterday’s goals. Where we begin to normalize underachievement because we aren’t adapting fast enough.
From Right-to-Left to Right-to-Right Thinking
Jim Champy flipped linear planning by starting from the outcome and reasoning backward. That mindset is still critical. But what happens when the “perfect outcome” isn’t knowable upfront?
I’ve been calling this shift Right-to-Right Thinking™. Instead of anchoring on one final outcome:
- You define an initial goal
- AI reveals adjacent or better outcomes
- Those outcomes reshape the goal itself
- You cycle back and forth between execution and redefinition
It’s recursive, not linear. Execution changes ambition. Goals are not endpoints; they’re stepping stones.
The Recursive Outcomes Loop
Before diving into the mechanics, let’s define what Recursive Outcomes Thinking™ really is – at least in my head. It’s a strategy mindset where outcomes themselves are treated as evolving assets. Rather than a fixed target, a goal is a launchpad that can (and should) be upgraded as execution unfolds. You don’t just move from A to Z. You move from A to X, then realize Z is possible, and reframe your ambition in motion.
Here’s the simple model I’ve been sketching:
- Define: Start with a worthy goal. Not just any target — something that, if achieved, would genuinely move the revenue needle or transform buyer experience. For a CRO, that might be “increase lead conversion by 30% in 6 months.” It’s ambitious, measurable, and anchored in business reality.
- Deploy: Act toward it using today’s tools, people, and processes. This isn’t blind execution — it’s an intentional first step. A sales org might roll out AI-enabled lead scoring to speed qualification. At this point, you’re pursuing the goal with discipline.
- Discover: This is where recursion kicks in. Execution itself surfaces new insights. Perhaps the AI tool doesn’t just qualify leads faster — it also uncovers a new buyer segment you never considered. Suddenly, the original 30% lift looks small compared to the unlocked potential. Discovery reframes the strategic landscape.
- Redefine: Take what you’ve discovered and reshape the outcome. Instead of settling for incremental lift, you might ask: “What if we rebuild the buyer journey entirely to double velocity?” The goal evolves, not because you failed, but because you uncovered something better.
- Repeat: Re-enter the loop with sharper ambition. Recursive outcomes strategy isn’t a one-time pivot; it’s an ongoing cycle of defining, deploying, discovering, and redefining. Over time, it compounds into outsized results.
This loop is different from iterative execution because the target itself evolves. It’s not about hitting the bullseye faster — it’s about realizing there are bigger, better targets on the board.
What This Means for CROs and GTM Leaders
For CROs, Recursive Outcomes Thinking changes the very nature of leadership. It’s not just about running tighter playbooks — it’s about leading teams into a mode where ambition expands in motion.
Shifts in Leadership
- Decision-making: Traditional CROs forecast against fixed targets. Recursive CROs reframe targets mid-flight, balancing stability with adaptability.
- Team enablement: Instead of only teaching sellers how to hit KPIs, recursive leaders coach them to spot signals of expanded possibility. “You hit quota — but what new opportunity did that unlock?”
- Metrics: Static KPIs are necessary but insufficient. CROs must layer in adaptive metrics: signals of discovery, new ICP traction, or unexpected buyer behaviors.
- Cadence: Quarterly business reviews evolve into quarterly recursive reviews. The question isn’t just “did we achieve?” but “what better goal did we uncover?”
In Symbiotic I/O™, we talk about evolutionary fitness — the ability to adapt as conditions change. Recursive Outcomes Thinking operationalizes that by embedding adaptability into the goals themselves. Instead of waiting for market disruption, CROs proactively evolve ambition.
You May Be Thinking… Isn’t This Just Agile?
It’s a fair challenge. On the surface, Recursive Outcomes Thinking sounds like agile or lean startup. But here’s the distinction:
- Agile iterates on execution. You break work into sprints, improving delivery. The goal (e.g., ship a product feature) doesn’t change — the process does.
- Lean Startup iterates on product-market fit. You test assumptions, pivot if wrong, and refine until the product resonates. Again, the goal is relatively stable (find fit), even if the path zigzags.
- OODA Loops (Observe–Orient–Decide–Act) are tactical, designed for real-time decisions in fast-moving contexts like the military.
Recursive Outcomes Thinking is different. It assumes the goal itself will evolve as execution unfolds. The CRO’s job isn’t only to optimize delivery or fit — it’s to recognize when execution unlocks ambition that wasn’t visible at the start.
In other words: Agile helps you run faster. Recursive Outcomes helps you decide if you’re running toward the right mountain.
Open Questions for Debate
Because this is early thinking, I want to leave the questions open:
- How do you avoid goal sprawl if ambition keeps evolving?
- How do you balance stability for teams with recursive shifts?
- What metrics make sense when outcomes themselves are fluid?
I don’t have final answers yet. I’m testing the idea that recursive goals might be a better fit for AI-era GTM. If you’re seeing similar dynamics in your org, I’d love to compare notes.
Where To Go Next
You don’t need a bigger playbook. You need a recursive strategy engine.
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This is early thinking, and I’m still testing and refining it in real time. If Recursive Outcomes Thinking™ sparks something for you, I’d love to hear what you’re seeing in your own GTM.
In the meantime, the fastest way to put this into practice is to take the GTM Health Check or download the Symbiotic.io GTM Workbook. Both will help you spot where your system needs to evolve next.
Let’s keep pushing the edges of go-to-market together,
Hannah Ajikawo
