Empiricism: Learning Through Doing

Knowledge emerges from observation, experience, and experimentation.

"You can't learn to ride a bicycle by reading a book."

Empiricism is a foundational mindset in Agile. It is the belief that knowledge emerges through experience, and sound decisions arise from what is known through observation, not speculation. Agile teams live this principle by testing ideas through action, inspecting the results, and adapting based on what they learn.

Origins and Philosophical Roots

Empiricism originates from philosophical traditions dating back to Aristotle, who emphasized sensory experience as the basis for knowledge. The concept was later formalized during the Enlightenment by thinkers like John Locke, who argued that the mind is a blank slate (tabula rasa) shaped by experience,¹ and David Hume, who pushed the idea that all knowledge begins with impressions from the senses.²

In the scientific method, empiricism means that hypotheses must be tested through observation and repeatable experiments. It rejects the notion of unquestioned authority or theory without validation.

In Agile product development, this translates to:

• Building small increments of working software
• Gaining feedback from real users
• Observing outcomes in real-world environments
• Letting experience, not prediction, guide the next steps

Instead of relying on long planning phases or rigid upfront design, Agile teams use short, learnable loops to discover the right path.

The Three Pillars of Empiricism

Empirical process control relies on three reinforcing pillars:

1. Transparency

Information must be visible to those responsible for the outcome. Shared understanding is required to make meaningful observations. This includes visibility of the backlog, team progress, quality, goals, and impediments.

2. Inspection

Teams must frequently examine what is happening. This can include the product (through reviews), the process (through retrospectives), and flow (through metrics like cycle time and WIP aging).

3. Adaptation

When inspection reveals issues or opportunities, the team adjusts course. This could involve changing tools, refining backlog items, shifting team behavior, or pivoting on product direction.

These pillars support learning in motion. Agile teams do not pause the work to learn. They learn by doing the work, reflecting on it, and adapting continuously.

How Empiricism Appears in Agile Frameworks

Scrum

Scrum is designed as an empirical framework. Each event in Scrum supports one or more of the three pillars:

• Sprint Planning sets a hypothesis for what can be accomplished.
• Daily Scrum inspects progress and enables immediate adaptation.
• Sprint Review provides feedback on the increment and guides product direction.
• Sprint Retrospective inspects team process and performance to foster improvement.

Each Sprint is a bounded experiment. Teams plan, act, inspect, and adapt.

Kanban

Kanban is not time-boxed but deeply empirical. It relies on:

• Visualizing work in progress
• Monitoring flow metrics (e.g., cycle time, throughput)
• Adjusting WIP limits and policies based on evidence
• Observing bottlenecks and improving flow gradually

Empiricism in Kanban is decentralized, data-driven, and continuous.

Extreme Programming (XP)

XP brings empiricism to technical practices. Test-Driven Development, for instance, validates code design through automated feedback. Pair programming, continuous integration, and refactoring rely on seeing real effects quickly and adjusting based on immediate feedback from both humans and systems.

Empiricism vs. Defined Process Control

In a defined process, steps are known and repeatable. This works for stable, predictable systems like manufacturing lines where inputs and outputs are consistent.

Software development, however, is not that world. Agile teams operate in complex, adaptive systems where outcomes are uncertain, and inputs shift constantly. Requirements are unclear, and even customers don't always know what they want until they see it.

Empiricism is a better fit for this environment. It accepts uncertainty as a given and uses learning to reduce risk and increase value.

The Role of Feedback Loops

Feedback is the heartbeat of empirical practice. Without timely, relevant feedback, learning decays. Agile builds short loops everywhere:

• Planning → Doing → Reviewing (Scrum)
• Red → Green → Refactor (TDD)
• Build → Measure → Learn (Lean Startup)
• Commit → Integrate → Deploy (CI/CD)

Speed and quality of feedback determine the rate of improvement. Coaches should help teams optimize these loops, not just complete ceremonies.

Barriers to Empirical Learning

Empiricism often fails not because it is wrong but because the environment blocks it:

• Lack of transparency: Without shared visibility, teams inspect shadows, not substance.
• Delayed feedback: If it takes weeks to learn from a change, empiricism becomes theater.
• Fear of failure: Psychological safety is essential. Teams must be free to experiment.
• Over-reliance on command and control: Empiricism thrives where decisions are close to the work.

An Agile coach's job is to detect and dismantle these barriers.

Key Takeaways

• Empiricism means learning through direct experience, not prediction.
• It is grounded in centuries of philosophical and scientific thought.
• Agile applies empiricism through transparency, inspection, and adaptation.
• Scrum and other frameworks are structured to enable short, feedback-rich loops.
• Effective Agile coaching includes reinforcing empirical learning as a habit, not a ritual.

Summary

Empiricism is the Agile mindset of discovering the right path by walking it. Instead of placing trust in prediction, Agile teams trust what they can observe and learn from. Grounded in centuries of philosophical and scientific thought, empiricism in Agile appears as a disciplined cycle of doing, observing, and adjusting.

By strengthening transparency, shortening feedback loops, and embracing adaptation, Agile teams can thrive even in the face of uncertainty. Coaches play a vital role in cultivating these habits and protecting the conditions that allow empirical learning to flourish.