Просмотр новости
Найдите то, что Вас интересует
Спутники
РН
SpaceX
Роскосмос
NASA
СпутникиРНSpaceXРоскосмосNASAAI Transformation is inevitable. So, I created a series to give you a guideline on how to start and go through your AI Transformation journey as a Scrum Team. Let's continue with step 4: Incorporating AI into Scrum.
Image
Product Delivery LifecycleIncorporating AI into Scrum means how you can leverage AI in each step of the product delivery lifecycle.
Image
JobNext Team Way
JobNext is a job listing platform that helps candidates find their desired jobs easily. These are the JobNext Scrum Team members:
Image
After using AI as a personal assistant for a while, the JobNext team gathered and discussed how they can incorporate AI into their Scrum way of working as the next step of their AI Transformation journey. This is their conversation:
Jack: “Well done, team. It has been around one month since we have been using AI as our personal assistant. I think we have learned a lot. So, this is the time to think of the next step.”Ted: “I agree. Now that we have the fundamental AI literacy and have used AI as a personal assistant, we should go to the next step.”Kate: “Let’s think of the whole Product Delivery Lifecycle.”Brayan: “That’s a good idea. In the product delivery lifecycle, we have five steps: Product Discovery, Refinement & Planning, Development, Delivery, and Value Verification. So, should we think of all of them?”Sara: “I don’t think so. Because it creates chaos, I believe, we should start with one of those steps.”Jack: “Yes, confidence is important. If we start with all steps of the product delivery lifecycle, we will encounter a lot of unpredictable things. So, let’s choose one step.”Ted: “Then I think it is better we start with a step that sometimes we have some problems with. But now we want to improve it with the help of AI. I mean the Refinement and Planning. What do you think, guys?”Kate: “Nice. We always have this process. So, that would be great if we could start with this step. But, how?”Ted: “I will research it and create a proposal to improve our refinement and planning process. At the beginning of the next Sprint Planning, I will present it to tune and finalize it.”Sara: “Wonderful. Looking forward to hearing from you, Ted. Thanks” Improving Refinement & Planning with AI
Sprint Planning InputsTo get prepared for Sprint Planning, you need to prepare several inputs. For most of them, AI can help you a lot.
Image
Levels of GoalsWhatever you plan to implement should support your goals. This is the relation between 3 levels of goals.
Image
Product Goal
Bring a concrete Product Goal to the Sprint Planning. Product Goal is the future state of your product. Although the duration of the Product Goal depends on your context, using a quarterly Product Goal is a good choice. Leverage AI with the following instructions to create your Product Goal.
Copy this prompt, paste it into an AI system like ChatGPT, fill in the brackets with the specific data of your product, and create your Product Goal:
We are building [Your Product]. The Product Vision is [Your Product Vision].
[Give it a little bit of context by explaining the high-level concept of your product and how it is going to create value].
We use Product Goals as the mid-term goals. So, break down the Product Vision into several smaller mid-term goals and create the first Product Goal (mid-term goal) within the SMART model boundaries as follows:
Specific: The goal should be clear and specific, avoiding any ambiguity about what is to be achieved.
Measurable: The goal should have criteria for measuring progress and success, so you can track your achievements.
Achievable: The goal should be realistic and attainable.
Relevant: The goal should matter to you and your stakeholders and align with other relevant objectives, ensuring it is worthwhile.
Time-bound: The goal should have a clearly defined deadline to create a sense of urgency and focus. Product Backlog Content
You can leverage AI as a thought partner to help you manage your Product Backlog by creating PBIs.
As an example, I used Miro AI to initiate a Product Backlog for an Electric Vehicle product. The prompt is: Create 6 User Stories for an Electric Vehicle car product from the Driver actor’s point of view.
Image
Create an AI Agent to watch the incoming support emails from customers on Outlook, Gmail, Zoho, etc., to discover new features and add them to the Product Backlog on Jira, Azure DevOps, Trello, etc.
Image
Actionable Product Backlog
A Product Backlog is actionable when it has the following characteristics:The PBIs on top of the Backlog are related and coherent. They follow a shared objective that guides your Sprint Goal.The PBIs on top of the Backlog are refined.The Product Owner has consciously ordered the PBIs on top of the Backlog to follow one shared objective.The PBIs should support achieving your current Product Goal.Keeping the Product Backlog in the Actionable state is the Product Owner’s accountability.
Image
Product Backlog Refinement
It gives the team enough understanding of a PBI to start the implementation.The bare minimum refinement for a typical software product includes preparing two things:
Visual DesignAcceptance Criteria
Image
Product Backlog Refinement - Visual DesignA great AI tool to create visual designs (Sketch, Mockup, Prototype) is Visily.
Just with prompting, create polished designs. It increases your productivity dramatically.If you want to learn how to use Visily, watch my free short video course, Precise Specs Handover with AI for Product Owners.
Image
Product Backlog Refinement – Visual Design Sample
I used this prompt with Visily, and it created this outstanding result:Create a website for an Italian restaurant that just cooks original pizza with a homepage, menu, reservation form, and contact. Use a modern olive green color palette.
Image
Product Backlog Refinement – Acceptance Criteria
Acceptance Criteria is a set of test scenarios that a feature must pass to be considered complete and work as intended. It is a non-negotiable mechanism for creating quality features.
You can use Given-When-Then (GWT) format, to write effective test scenarios.
See this example:
Image
You can leverage AI to generate Acceptance Criteria for PBIs.
Copy this prompt, paste it into an AI system like ChatGPT, fill in the brackets with the specific data of your PBI, and create a draft version of the Acceptance Criteria and then tune it:
We are building [your product high-level concept].
One of the features of this product is [your feature]. Create Acceptance Criteria for this feature based on the Gherkin language with the Given-When-Then (GWT) format and show the result in a table with these columns: Scenario Title, Given, When, Then.
This is an example prompt to create Acceptance Criteria for a feature of an online banking system. See the result on the next page:
We are building an online banking system.
One of the features of this product is that a user can transfer money from one bank account to someone else's bank account. Create Acceptance Criteria for this feature based on the Gherkin language with the Given-When-Then (GWT) format and show the result in a table with these columns: Scenario Title, Given, When, Then.
Image
A draft suggestion of a Sprint Goal
It is better to bring a draft suggestion of the Sprint Goal to the Sprint Planning. It pushes the Product Owner to order PBIs on top of the Product Backlog in a way that they follow a shared objective, making the Product Backlog actionable.
Copy this prompt, paste it into an AI system like ChatGPT, fill in the brackets with the specific data of your product, and use the result as the draft suggestion of your Sprint Goal:
We use [Sprint duration like two-week] Sprints to build [Your Product]. The Product Vision is to [Your Product Vision]. We use [Product Goal duration like quarterly] Product Goals as the mid-term goals. The current Product Goal is to [Your current Product Goal]. This is the [Sprint number like first] Sprint of the current Product Goal. So, break down the current Product Goal into smaller short-term goals and use them as the base to create a Sprint Goal for the [Sprint number] Sprint aligned with the Product Vision and the current Product Goal through the FOCUS model as follows:
Fun: come up with a memorable title and try to inject an element of fun.
Outcome-oriented: The goal should achieve a common understanding of what you are trying to accomplish.
Collaborative: The whole Scrum Team creates the Sprint Goal together.
Ultimate: The Sprint Goal should include a why, the ultimate reason behind what we are trying to achieve.
Singular: The Sprint Goal should consist of a single common objective instead of multiple competing objectives.
Definition of Done
The DoD is the shared clear understanding of what Done means. The more stringent the Definition of Done, the more quality product. It should include expectations from the following 6 main categories:
Image
You can leverage AI to create and enhance your Definition of Done.
Copy this prompt, paste it into an AI system like ChatGPT, fill in the brackets with the specific data of your product and create the Definition of Done:
We are building an application for [The high-level concept of your Product]. The product name is [Your Product name].
The Definition of Done is the common shared understanding of the criteria that must be met for an Increment to be considered complete. It is the commitment of the Increment artifact to enhancing transparency and focus.
Create a Definition of Done document containing all required expectations for the [Your Product name] product.
The Definition of Done should be like a checklist including the following main categories of expectations:
1- Process expectations
2- Technical expectations
3- Delivery expectations
4- Industry standards & expectations
5- Organization expectations
6- Non-Functional Requirements
After improving the Refinement & Planning step, the JobNext team continued improving other steps of the Product Delivery Lifecycle.
Download the PDF of all steps of the free playbook here. I will publish the next step of the AI Transformation in a couple of days. So, wait for the next step. ---------------------------------------------------------------------------If you want to go further and prepare yourself as a Scrum Master to lead your team in their AI Transformation journey, join my upcoming advanced “AI Transformation for Scrum Teams” class.
This is an advanced class for experienced Scrum Masters who not only want to secure their future but also want to deliver a completely new value to their teams.
| # | Наименование новости | Тональность | Информативность | Дата публикации |
|---|---|---|---|---|
| 1 | [Vlog] AI-native Scrum Team Specifications | 0 | 5 | 22-06-2026 |
| 2 | [Episode 1] How to Start the Team AI Journey | 0 | 5 | 23-06-2026 |
| 3 | [Episode 3] Start Using AI as a Personal Assistant | 0 | 5 | 08-07-2026 |
| 4 | Four Main Ways to Learn AI for Scrum Masters | 5 | 7 | 06-07-2026 |
| 5 | [Episode 2] AI Basic Literacy for Scrum Team | 0 | 7 | 29-06-2026 |
| 6 | The New AI Operating Model. Start By Using Scrum | 0 | 6 | 07-07-2026 |
| 7 | What Will Happen to You in Two Years if You Don’t Learn AI as a Scrum Master? | -2 | 5 | 10-07-2026 |
| 8 | The AI Definition of Done | 0 | 7 | 21-06-2026 |
| 9 | From Dependency Loops to Delivery Flow | 5 | 7 | 07-07-2026 |
| 10 | Die KI-Definition of Done: Human in the Loop ist kein Qualitätsstandard 🇩🇪 | -2 | 6 | 25-06-2026 |