Following our initial announcement on June 16th, where we launched AI-Native SAFe as the operating model designed for the Age of AI, we promised to guide our community through this evolution step by step.
On July 28th, we took the next step with Session 4 of our virtual event series: Reimagining PI Planning and SAFe Events for the Age of AI, and released a new set of Framework guidance circled below.
An overview of the key themes covered in session 4 is summarized below.
Proving Product Value with Customer Demos
AI accelerates product development, but using AI without collaborative customer feedback risks building flawed products. Implementing an effective customer feedback process, gathering insights from various sources to understand what customers need and how they use the product once released, must be the goal for every AI-Native organization.
A key element of feedback design is determining how feedback will be collected. Customer Demos carry significant importance by engaging customers directly to validate desirability and real-world application.
In AI-Native SAFe, Customer Demos are held regularly. When selecting the right customer demo format, two considerations guide the choice:
- Purpose: Is the demo to drive learning, or is it to persuade the customer of the value of the product?
- Reach: Is the demo required to collect feedback from a large group of customers, or is it a more personal demo?
This approach helps select the best format for customer demo, yielding appropriate responses and avoiding falling back on the same approach every time.
PI Outcome Planning Event
Once we have this feedback from Customer Demos, the next step is to incorporate it into the outcomes that we are committing to for the upcoming PI. This is where the brand new PI Outcome Planning event plays a critical role. The PI Outcome Planning event is a 1-day event for everyone on the AI-Native ART, replacing the 2-day PI Planning event.
PI Outcome Planning serves three core purposes:
- Aligning and committing to the PI Outcomes that will best advance the ART’s long-term strategy
- Formulating and committing to Team Outcomes that will progressively achieve the PI Outcomes
- Identifying the milestones that create an executable plan
The 1-day PI Outcome Planning agenda, shown below, begins with the Business Context, where leadership shares the Product Vision, ART Outcomes, and draft PI Outcomes. The event then alternates between two breakout types:
- Outcome Breakouts: These bring together cross-team representatives to plan the work needed to deliver a specific PI Outcome and identify the key milestones.
- Team Breakouts: These provide the time and space for individual teams to test their ability to balance commitments across multiple PI outcomes they are contributing to, as well as to refine their team outcomes.
The morning then concludes with a draft plan presentation, followed by a management review and problem-solving meeting. The afternoon starts with planning adjustments followed by a second breakout cycle, before getting to the final plan presentation and a commitment vote.
The central artifact in a PI Outcome Planning event is the PI Outcome Planning Board, shown below. It visualizes the emerging plan and illustrates how the PI Outcomes are realized via the Team Outcomes and the key milestones that the ART commits to during the PI to execute the plan.
ART Sense and Respond Event
Between the PI Outcome Planning events, the teams use regular Sense and Respond events to align and adjust the plans as needed. The AI-Native ART Sense and Respond is a 2-hour event held every iteration to drive accelerated learning. It replaces the SAFe Inspect and Adapt event and incorporates System Demo activities. The Sense and Respond event serves three core purposes:
- Managing Variability: Addressing changes in product context, AI models, and customer needs.
- Intentionally Discarding Work: Exercising discipline to stop pursuing exploratory areas that fail to drive outcomes.
- Sharing Learning Across the ART: Providing space for ART-level systemic learning.
The event is split into two halves. The first half is focused on four ‘sensing’ activities, ensuring that key insights are shared across the ART. The second half includes three activities that focus on determining how we will ‘respond’ to these insights. An example agenda, below, shows these specific activities.
The Release Train Engineer (RTE) facilitates Sense and Respond events. While facilitating the event, the RTE should have three perspectives in mind, which can be illustrated using three key questions:
- Objective Outcome Progress: Are we evaluating progress against ART and PI outcomes using objective data?
- Listening to Customer Feedback: Are we reviewing how outputs have been received by customers using product performance metrics and direct feedback from customer demos?
- Prioritizing Workflow Improvements: Are we identifying workflows that can be optimized based on evidence, and are these the most important workflows to improve?
AI-Native SAFe Virtual Event Session 4
If you missed the live broadcast of Session 4, watch the full recording below to learn how to modernize your planning cadences, gather actionable customer feedback, and execute high-alignment AI-Native ART events.
To dive deeper into these topics, we encourage you to access the new guidance articles directly from the AI-Native SAFe Big Picture and explore the details at your own pace.
And join us for our next session, ‘Building AI-Empowered Products with continuous innovation and governance’. To secure your spot and participate in the live Q&A, visit our registration page. This virtual event series runs over 12 weeks and culminates in a full reveal at the SAFe Summit San Diego on September 14-18.
We are excited to be on this journey with you and build the future together.
Stay SAFe,
Andrew Sales, SAFe Chief Methodologist