Why Agile Teams Must Analyze and Make Adjustments

The Importance of Self-Learning

This is not a question from an outside source, such as a member of your staff or someone authorized to evaluate your performance. This is a question you should be asking yourself. Most of us can write a bulleted list of three to five things we can do to help, such as reading, completing training programs, talking with team members, issue-solving, and attending webinars. When we do this, we must question ourselves, "Did I do any of these in the last six or twelve months?" "Is this merely a wish list, or is this something that happened a long time ago?" It is necessary since it allows you to validate and amend the things on your list. Put this into practice at your next staff meeting or coaching session. Learning is an ongoing process. We place ourselves on the path to success when we understand our primary and secondary learning strategies and apply them to improve ourselves again and again. This is true for everyone working in agile development, but especially for team members.

According to my own experience as someone who is motivated to learn every day and has been transferring knowledge for over a decade, self-knowledge is crucial as it enables you to understand your way of learning. It means that you will know what type of learning will work best for you. Some of us learn by attending training sessions, and formal training programs, observing the happening around us, experimenting, or simply having on-the-job experience.

Key Takeaway: Checking whether you actually did the learning activities you listed for yourself over the past six to twelve months turns a wish list into a plan you can act on.

Walking the Talk

The way you and the rest of your agile team learn and practice what you learn at regular intervals determines if you and the rest of your agile team are "talking the talk." To ask questions, discuss ideas, and comprehend different points of view from all team members, an agile endeavor requires appropriate comfort and boldness. It does not encourage or give extended periods of seclusion. It is founded on cooperation and teamwork. Continuous learning in a group context is essential for agile team success. Agile teams may learn effectively through group and collaborative learning. What enhances learning and translates information into action is action orientation.

Key Takeaway: Agile teams learn as a group, so the team needs enough comfort and boldness for every member to ask questions, discuss ideas, and share a different point of view.

A Learning Opportunity

We no longer work under the conventional waterfall model, where we wait until the completion of each project to reflect and learn. We live in an iterative and incremental environment with numerous opportunities to learn, apply what we learn, improve, and ensure that the lessons gained are put into practice to provide meaningful solutions to our clients. This is an opportunity that we have never taken advantage of systematically in the past.

We can now learn from our daily work, team retrospectives, and consumer feedback. We can get the most out of this opportunity if each of us answers the question "How do I learn?" with conviction.

The Scrum Guide gives this loop a definition you can hold a team to. It describes inspection as checking the artifacts and the progress toward agreed goals frequently enough to detect undesirable variances, and adaptation as adjusting the process or the product when something drifts outside acceptable limits. It also says the most impactful improvements are addressed as soon as possible, and that they may be added to the Sprint Backlog for the next Sprint. An improvement that stays in a retrospective document is not an adaptation.

Key Takeaway: An improvement that stays written in a retrospective document is not an adaptation, so an agile team should move the most impactful improvements into the next Sprint Backlog.

Orientation to Action

The first stage is to learn from your day-to-day interactions, team interactions, and retrospectives. The next stage is to put what you've learned into practice as soon as possible. This is what allows you to progress. This necessitates group decision-making and action orientation, which is simply getting things done. This is another collaborative team task. A delicate combination of people-orientation and task orientation is what allows agile teams to put what they learn from iteration to iteration into practice. It's simpler stated than done. It necessitates a great deal of cooperation and coordination.

Positive reinforcement is ensured in agile teams through action orientation and rapid course correction. Positive reinforcement increases team engagement, which translates into increased throughput and quality. This leads to satisfied customers. When learning is ineffective or action direction is lacking, agile teams find moving from iteration to iteration unsatisfying or demotivating. That is not a promising indication. It has a declining effect. Agile teams struggle to retain their agility in the absence of good retrospectives.

Agile teams now inspect a different kind of work. Code and test drafts often arrive from an AI coding assistant, so a team can raise its output without raising its understanding. The code review step is where the learning happens, and it is the step a team skips when the generated code looks correct. Put it on the retrospective agenda. Ask which assistant-drafted changes shipped without rework and which ones came back, then change how the team reviews that work in the next iteration.

Key Takeaway: Agile teams keep their momentum by acting on retrospective lessons in the next iteration, including reviewing which AI-assistant-drafted changes shipped without rework and which ones came back.

Delivering Working Software

Delivering usable software in small increments at a sustainable pace is difficult in your first one or two projects since you and your team members or business users are in uncharted territory. Allow me to tell you a story. One of my project teams decided to deliver in short iterations a few years ago.

We took on more than we could handle in order to display our good intentions. We were always willing to make adjustments. "That's insane!" you say. "That's not agility!" Our product manager was suffering from "feature-itis." We wanted to show ourselves by making our PO happy. We were afraid of saying no. We never stopped to think. We never followed up to seek feedback from corporate users. You can predict what occurred next.

Of course, our team members were stressed and burned out. It was a clear indication of an extraordinary pace. To cut a long tale short, our methodology did not take into account learning and the ability to "observe and adjust." We had to take a moment to contemplate. We organized an offsite one-day team gathering to envision the future of our project. To enhance our strategy, we needed to make a significant course correction or overhaul. That's when we discovered the need for continuous team learning, team retrospectives, and learning from consumer feedback.

Agile teams must be disciplined in order to produce in short iterations while still ensuring positive encouragement as they progress. This is attainable if iteration actions are carried out meticulously. Iteration planning, for example, offers a good foundation for the remainder of the iteration by including user stories, and estimates, developing a work breakdown structure, identifying dependencies, making a commitment based on the team's capabilities, and many other processes. Furthermore, the efficacy of iteration end activities like review, Planning, and retrospective allows for continuous improvement in subsequent iterations.

Key Takeaway: Committing to more work than a team can sustain, without stopping to collect feedback from business users, burns the team out and forces a much larger course correction later.

What Should Agile Teams Analyze Before They Adjust?

Agile teams should analyze agile metrics next to their retrospective notes, because opinion on its own does not show where the work stalls. DORA publishes five software delivery metrics that give a team numbers to inspect: change lead time, deployment frequency, failed deployment recovery time, change fail rate, and deployment rework rate. DORA defines change lead time as the time a change takes to go from committed to version control to deployed in production, and change fail rate as the ratio of deployments that require immediate intervention. Bring each number into the retrospective and let the discussion explain it.

The adjustment is the harder half. Easy Agile surveyed 419 engineers, product managers, and project managers across the US, UK, Germany, Canada, and Australia for its State of Team Alignment 2026 research. It found that the median share of retrospective action items fully implemented before the next retrospective was around 50 percent, and that nearly 70 percent of teams implement less than 60 percent of the improvements they identify. Measure your own completion rate for action items. It is the one number that separates a team that adapts from a team that only reflects.

AI has changed which numbers matter. Google reports that 90 percent of respondents in the 2025 DORA study use AI at work, and that AI adoption now shows a positive relationship with software delivery throughput but a continuing negative relationship with software delivery stability. The report's own reading is that AI amplifies what a team already has rather than fixing it. For a team that inspects and adapts, the practical step is to watch change fail rate and rework alongside output. Volume that rises while failed changes also rise is a signal to adjust your review and testing steps, not your delivery target.

Key Takeaway: Agile teams should read delivery metrics such as change lead time and change fail rate next to their retrospective notes, and measure what share of retrospective action items the team actually completes.

How Does AI Change What Agile Teams Analyze and Adjust?

AI changes the inspect step more than the adjust step. A team now reviews work it did not fully write, so the retrospective has to cover how that work was checked, not only how much of it shipped.

The 2025 DORA study surveyed nearly 5,000 technology professionals. DORA reports that 90 percent of them use AI at work and more than 80 percent believe it increased their productivity, while 30 percent report little or no trust in the code AI generates. A team that leans on generated output and distrusts it at the same time is carrying a review cost it has probably never measured. Measure it. Count how many assistant-drafted changes needed rework before they shipped, and bring that count to the retrospective next to your change fail rate.

Agentic tooling has also moved into the retrospective itself. AI agents inside issue trackers can assemble a sprint summary from issue history, list what was completed and what carried over, and surface recurring bug patterns without anyone reading the board by hand. That saves preparation time. It does not replace the meeting.

Two limits are worth stating plainly. A generated summary reports only what the tracker holds, so a team that closes stories without notes or leaves epics unlinked gets a clean-looking summary that hides its real problems. And a summary describes what happened, not why the team let it happen. The why still comes from people talking. Treat an AI summary as the input to the discussion and keep the decision, the action item, and the owner with the team.

Key Takeaway: AI raises how much work an agile team produces without raising how well the team understands it, so count the assistant-drafted changes that needed rework and read that count next to your change fail rate.

Discover, Adapt, and Keep Improving

I now begin my coaching sessions with the basic question presented earlier: "How do we learn?" This is not a random question. I invite the participants to think about it. I inspire team members to engage in self-inquiry and look for answers. This is accomplished in a group environment. When I begin this activity, the participants gradually open up, share their responses, and begin discussing. This allows them to see how they learn as individuals and grasp the similarities in order to optimize team learning. I believe this is where agility begins.

In your organization, you must go through the "learn-apply-improve" process. You learn primarily from two sources: team retrospectives and feedback from business users. Collective choices and action items based on what you learned contribute to the improvement of your business, which leads to positive reinforcement. This is because you went through the learning process and came to a consensus on what to do next. Nobody outside of your team stepped in and told you what to do. Isn't it an easy task to begin with?

Key Takeaway: Starting a coaching session by asking every member how they learn lets an agile team see the similarities between individual learning styles and build team learning on them.