Join LitheSpeed’s VP of Consulting, John Halberstadt for an insightful session that will help you start, or continue on, your journey of using GenAI in your approach to Agile practices.
Whether you’re an Agile Coach, Scrum Master, Project Manager, or other business or technology leader, this livestream can provide you with some actionable insights and tools to get started in leveraging the power of GenAI effectively and immediately for your team and organization.
Date: Thursday, August 29, 2024
Time: 12pm ET (1 Hour)
Link to Register for the Livestream: https://www.meetup.com/dc-lean-agile/events/301156807/
Let’s Get Beyond the Hype
Generative AI (GenAI) is perhaps the most (over) talked-about buzzword these days, and it’s easy to understand why anyone might be skeptical when encountering yet another LinkedIn post or livestream on this topic.
However, like other buzzwords before it – Cloud, Big Data, even Agile – AI in general, and Generative AI in particular, offers numerous real-world benefits. This is especially true for those who are passionate advocates and practitioners of Agile Ways of Working.
As with previous “hyped” technologies, the key is to look beyond the hype and understand how these technologies function and how they can be utilized effectively for teams and organizations – today, in the real-world. When used thoughtfully, GenAI tools align well with Agile principles and values, and can be used daily as a key technology to enhance and amplify agility.
GenAI offers opportunities to streamline processes, enhance—not replace—creativity, and drive better outcomes, making it a valuable tool for Agile practitioners. This blog post shares perspectives on why GenAI is so impactful, how it aligns with Agile frameworks, and some cautionary tales.
Why GenAI Matters
GenAI has changed the landscape – personal and professional areas alike – for several compelling reasons:
Efficiency and Speed
- Rapid Content Generation: GenAI can produce high-quality content quickly, automating tasks that traditionally required significant manual effort, such as documentation and data analysis.
- Automated Processes: This automation frees up team members to focus on higher-value activities, leading to faster delivery times and improved efficiency.
Enhanced Decision-Making
- Data-Driven Insights: AI-driven analytics provide deep insights into customer behavior, team performance, and market trends, enabling informed decision-making.
- Predictive Capabilities: Machine learning models forecast future trends, helping teams anticipate changes and adapt strategies proactively.
Creativity and Innovation
- Ideation Support: GenAI can assist in brainstorming sessions, offering new perspectives and ideas. This is useful in planning and retrospective meetings.
- Continuous Improvement: By refining user stories, sprint goals, and other Agile artifacts, GenAI ensures teams work with the best possible information.
Real-World Applications of GenAI in Agile
Generative AI tools can provide valuable help to advocates and practitioners of Agile Ways of Working immediately. Not to replace these individuals and the exceptional work they do, but to augment, accelerate and improve their work and contributions.
The following are some great examples of how GenAI tools can work in the real world, past the hype:
- Generating and Refining User Stories: Creating effective user stories is a challenge for many teams, especially those getting started. GenAI can analyze existing stories, understand user needs, and generate refined versions that are clearer and more actionable. Inputting one’s team’s initial user stories into a GenAI tool like ChatGPT can help with generating improved versions, including ensuring essential information like acceptance criteria are included and well-defined.
- Enhancing Agile Events and Activities: Agile events, such as sprint planning and retrospectives, are essential for team collaboration and improvement. They also can get boring, stale or otherwise ineffective. GenAI can introduce new techniques, keeping these events fresh and engaging. For example, AI can suggest different formats for retrospectives to keep things interesting and help provide new perspectives and reclaim “the beginner’s mind”.
- Optimizing Team Performance: By analyzing data from tools like Jira, GenAI can identify performance trends and suggest areas for improvement. This can be helpful for any team, coach or Scrum Master, but is especially useful for new teams, new Scrum Masters and other areas where one doesn’t necessarily have the data and contextual knowledge that would help best assess and address areas to improve as a team.
Horror Stories: When AI Goes Wrong
While GenAI has immense potential, there are also cautionary tales as these technologies are applied and fail in the real world, including:
- Biases (and attempts to mitigate them) in AI Models: An AI recruitment tool developed by a major tech company was found to be biased against women, favoring male candidates due to biased training data. The corollary to these biases now has become the “overcorrection” to preempt bias resulting in snafu’s like Google’s Gemini providing historically inaccurate representations of people. This problem is not easily solved, and requires vigilance in the use of AI technologies and ensuring they’re applied appropriately knowing these inherent biases.
- Security Vulnerabilities: AI-generated code can introduce security vulnerabilities if not properly vetted. In one case, an AI system used for automated code generation produced insecure code snippets, exposing applications to potential attacks. Rigorous validation and testing are crucial, but these are areas where organizations often already have challenges and may amplify issues like limited test automation, security validation and overall technical expertise. GenAI can make it easier to solve problems by generating code that functions but has underlying issues.
- Misinformation and Fake Content: As we have likely all already seen given the current election season in the US, there are countless AI tools capable of generating realistic text and images that are actively being used to create deepfakes and spread misinformation. As these tools improve their overall quality and lower the cost, this issue is likely to continue accelerating rapidly.
Get ready for a deeper, interactive dive into GenAI’s practical applications in Agile practices and aligning to Agile values. We’ll cover real-world examples like those above, explore overcoming challenges, and answer your questions about integrating this powerful technology.
