The End of “Good Enough Agile”

TL; DR: The End of “Good Enough Agile”

“Good Enough Agile” is ending as AI automates mere ceremonial tasks and Product Operating Models demand outcome-focused teams. Agile professionals must evolve from process facilitators to strategic product thinkers or risk obsolescence as organizations adopt AI-native approaches that embody Agile values without ritual overhead.

The Perfect Storm Coming After Good Enough Agile

For two decades, many of us have participated in, or at least witnessed, a prolonged performance of “Agile-as-theater.” Now, the curtain is falling. Mechanical Scrum, stand-ups — or Daily Scrum, if you prefer that term — without tangible purpose, estimation rituals that pretend to forecast the future, Jira-as-performance-art; we’ve normalized Agile as a checklist. Useful, perhaps, if you blinked hard enough and never dared ask about the return on investment.

That era is ending, not with a dramatic bang, but with a slow, irrevocable drift toward irrelevance for those who don’t adapt.

What’s forcing this change? Two converging forces that aren’t just disruptive but existential threats to “Good Enough Agile:” Artificial intelligence and the Product Operating Model.

Let’s be brutally honest: If your primary Agile practice revolves around facilitating meetings, meticulously documenting progress, and shepherding tickets from “To Do” to “Done,” you are now officially redundant. AI can, and already does, perform these tasks. It’s faster and cheaper and doesn’t need a “Servant Leader” to guide a Retrospective summary and its follow-up communication.

Mechanical Agile: Already Obsolete

The uncomfortable truth is that most Agile implementations never graduated beyond the delivery phase. Strategy? That was deemed someone else’s problem. Discovery? Often skipped, outsourced, or diluted into a Product Backlog of unvalidated ideas. Empowerment remained a popular keynote topic, not an operational reality.

Agile teams became efficient delivery machines: tactical, often fast, but fundamentally disconnected from actual business and customer outcomes. That’s not agility; that’s a feature factory wearing a lanyard that says “Scrum.”

The 2020 Scrum Guide states, “The Scrum Team is responsible for all product-related activities from stakeholder collaboration, verification, maintenance, operation, experimentation, research, and development…”. Yet, in practice, how many Scrum Teams are truly empowered to this extent? Most are boxed into building what someone else, somewhere else, decided.

And AI is going to eat that box.

Consider what generative AI achieves today:

• Summarizes Sprint Reviews and Retrospectives,
• Clusters customer feedback into actionable themes,
• Highlights potential blockers by scanning Jira, Slack, and Confluence,
• Prepares release notes and offers data-informed team improvement suggestions.

If your role primarily focuses on these facilitation, coordination, or status-tracking aspects, you’re no longer competing with other humans. You’re competing with code and tokens. AI doesn’t need psychological safety or emotional labor. It needs inputs and patterns. It doesn’t coach, it completes.

Product Operating Models: The New Baseline for Value Creation

If AI relentlessly attacks the how of mechanical Agile, Product Operating Models fundamentally redefine the why and what. The Product Operating Model, as championed by Marty Cagan, isn’t just a new practice; it’s a shift in how effective companies build, deliver, and iterate on value. It demands teams solve real customer problems aligned with tangible business outcomes, not just dutifully executing on stakeholder wish lists or pre-defined feature roadmaps.

This model requires:

• Empowered teams assigned meaningful problems to solve, not just features to build. They are accountable for outcomes.
• Decision-making that spans product strategy, discovery, and delivery, with teams deeply involved in determining what is valuable, usable, feasible, and viable.
• A culture of trust over control, principles over rigid processes, innovation over mere predictability, and learning over fear of failure.

It’s not that the Product Model dismisses Agile principles. Instead, it subsumes them. Think of it as an evolved organism that has internalized Agile’s most useful DNA, like continuous delivery and cross-functional collaboration, and discarded the empty rituals.

This shift exposes how shallow many Agile adoptions are. Recent survey data highlights that 12% identify a lack of product vision as leading to “Feature Factory” waste, while another 33% pointed to a leadership gap, not necessarily micromanagement, but a disconnect between professing Agile values and actually empowering teams to achieve outcomes. Poor Agile implementation was cited by 10%, showing that process obsession often hurts more than it helps, and 12% highlighted cultural resistance, where psychological safety and a learning environment are absent.

Old Agile vs. New Reality

Here’s what the paradigm shift demands:

• Stand-ups vs. Outcomes: Are you syncing or solving?
• Estimates vs. Telemetry: Are you gambling with guesses or learning in real time?
• Belief vs. Evidence: Does your Product Backlog reflect strategy — or stakeholder fantasy?
• Mechanical Rituals vs. Market Results: Is your Agile a safety blanket or a value engine?

This is not a theoretical debate. It’s a fork in the road.

The Agile Industrial Complex Is on Notice

Agile didn’t die because it wasn’t valuable. It’s struggling because when agility became a product, it lost its edge.

The monetization of the Agile Manifesto. The transformation theater. The armies of consultants selling templates for self-organization. The playbook peddlers. Organizations wanted change but settled for frameworks instead. They got stand-ups instead of strategy. They got rituals instead of results.

The Agile industrial complex mistook adoption for impact. It sold belief over evidence. And the reckoning is here.

“But Our Agile Transformation Is Working!”

I know what you’re thinking. Perhaps your teams genuinely feel empowered. Maybe your Retrospectives drive real change. Your Product Owner might truly represent customer needs rather than stakeholder demands.

Congratulations! If that’s your reality, you’re already practicing what I’m advocating for. You’ve transcended mechanical Agile and built something that actually works. You’re not the target of this critique; you’re proof that it’s possible.

But here’s the uncomfortable question: Are you sure you’re not confusing efficient delivery with effective outcomes? Many teams that feel “empowered” are still fundamentally executing someone else’s strategy, with more autonomy in building features.

The test is simple: Can your team pivot the entire product direction based on what you’re learning? Or do you need permission?

Acknowledging the Loss

If you’re feeling defensive or unsettled right now, that’s completely understandable. Many of us have invested years mastering practices that felt meaningful and valuable. We’ve built our professional identities around frameworks that promise humanizing work and unleashing creativity.

The events that once felt revolutionary now risk becoming ritual. The frameworks that once liberated teams have calcified into the process. This isn’t your failure; it’s a natural evolution that happens to every successful practice.

Letting go of what once worked doesn’t diminish its past value or your expertise in applying it. It takes courage to evolve beyond what made you successful. (And I do include myself here, believe me.)

What Happens Next: The Rise of Post-Agile Organizations

Product-led organizations that fully embrace AI and outcome-driven Product Models will likely skip past traditional, ceremonial Agile entirely. They will:

• Use real-time telemetry (or data) to understand what users do, not just guess what they might want
• Leverage AI to generate tests, documentation, and even first-pass UIs in minutes, not Sprints
• Focus on learning velocity — how quickly they can validate hypotheses and adapt, not just delivery velocity
• Reallocate human intellect to the highest-leverage work: deep customer insight, ethical considerations, strategic judgment, and genuine invention

These organizations won’t be hiring legions of Agile Coaches. They’ll seek Product Strategists and Product Coaches who understand the full value creation lifecycle. They won’t need Scrum Masters to run meetings. They’ll have empowered, cross-functional teams with live telemetry dashboards and a clear mandate to ship value, not just track velocity.

And they will outcompete traditional organizations decisively.

A Vision of What’s Possible

Imagine working on a team where AI handles the administrative overhead, where real-time data tells you immediately if you’re solving the right problem, and where psychological safety comes from shared accountability for outcomes rather than adherence to process.

Picture teams that spend their energy on deep customer research, ethical considerations, and creative problem-solving rather than estimation poker and Sprint Planning. Envision organizations where “empowerment” isn’t a buzzword but an operational reality: Teams that can pivot strategies based on evidence, not just tactics based on backlog priorities.

This isn’t about losing the human element of work. It’s about elevating it. When AI handles coordination and data analysis, humans become free to do what we do best: Understand nuanced problems, navigate complex stakeholder dynamics, and create innovative solutions.

This future isn’t dystopian; it’s energizing. But only for those willing to evolve toward it.

Scrum Can Survive — By Going Back to Its Roots and Becoming Invisible

There’s still a place for Scrum, but only if it’s stripped back to its original, minimalist intent: a lightweight framework enabling a small, autonomous team to inspect, adapt, and solve complex problems while delivering valuable increments. It should be the near-invisible scaffolding that supports the team’s functionality, not the focus of their work.

The second you start optimizing your Scrum process instead of your product and its outcomes, you’ve already lost the plot.

How to Stay Relevant: A Survival Guide

This article isn’t about fear-mongering; it’s about a clear-eyed assessment of a fundamental shift. (And I have been struggling to formulate it for months.) If you’re sensing this transition is real and inevitable, here’s how to navigate it:

1. Become Radically Product-Literate

Stop facilitating. Start understanding. Learn product strategy. Immerse in discovery. Study customer behavior. Know how the business makes money and how your work contributes to it. If AI can do a significant part of your current job, immediately pivot your development towards uniquely human strengths: Coaching for critical thinking, systems thinking, complex problem framing, and outcome-oriented product strategy.

2. Shift from Output to Outcome Obsession

Shipping fast is not valuable in and of itself. Don’t be satisfied with being a world-class delivery facilitator. Insist on understanding and contributing to why anything is being built. Push for access to the strategic context and the discovery process; your value multiplies when you connect delivery excellence to strategic intent.

3. Partner with AI, Don’t Compete

AI is not your enemy. It’s your amplifier. Automate coordination. Use LLMs for sense-making. Audit your rituals mercilessly: If a meeting or artifact doesn’t directly drive a measurable, valuable outcome, kill it. Free yourself to do the one thing AI can’t: Frame the right problems and align humans to solve them.

Conclusion: This Isn’t a Fad. It’s Evolution.

We are not just weathering the storm but witnessing evolution in real-time. You are living through a paradigm shift defining the next two decades of product development. “Agile” isn’t “broken” simply because of poor adoption or choosing the “wrong” framework. It’s transforming because the world has changed technologically, strategically, and economically, and our practices must also change.

There’s a delicious irony here: A practice built on rapid learning and continuous adaptation has become remarkably bad at eating its own dog food. We’ve spent years teaching organizations to inspect, adapt, and embrace change over following a plan. Yet, when faced with the most significant technological and strategic shifts in decades, much of the Agile community has chosen to double down on familiar practices rather than inspect and adapt them.

The very principles we’ve evangelized, I refer to empiricism, experimentation, and pivoting based on evidence, should have prepared us for this moment. Instead, we’ve often responded like any other established industry: Defending the status quo, questioning the data, and hoping the disruption will somehow pass us by.

We’re entering an era of AI-native, outcome-obsessed, telemetry-driven organizations. They don’t need Agile frameworks. They embody the values.

The fundamental question is no longer about doing Agile right but being effective in a world increasingly shaped by intelligent automation and a relentless focus on demonstrable product outcomes.

Are you ready to help shape what comes next? The future belongs to those who can bridge the gap between Agile’s foundational values and tomorrow’s technological reality. The question isn’t whether change is coming — it’s whether you’ll lead it or be swept along.

What will you choose to build?