Best Practices for Agile Software Teams: Estimating Tasks for Non-Full Stack Developers

Best Practices for Agile Software Teams: Estimating Tasks for Non-Full Stack Developers

Best Practices for Agile Software Teams: Estimating Tasks for Non-Full Stack Developers


Agile software development has revolutionized the way teams work together to deliver software projects. However, in agile teams that are not full stack, estimating tasks can pose unique challenges. In this blog post, we will explore the best practices for estimating tasks in such teams and discuss the potential difficulties they may face. We will also propose a hybrid approach that involves team collaboration while granting the final estimation authority to the person working on the task or the one with core competency.

Challenges of Estimating as a Non-Full Stack Team:

  1. Specialization: Non-full stack teams typically consist of members with specialized skills in specific areas, such as front-end development, back-end development, or database management. Estimating tasks collectively becomes challenging because each team member may have limited knowledge or expertise in other areas.
  2. Communication Gaps: Estimation requires effective communication and shared understanding among team members. In non-full stack teams, where individuals may lack familiarity with certain technical aspects, miscommunication can lead to inaccurate estimations.
  3. Over/Underestimation: In the absence of full stack knowledge, team members may tend to overestimate tasks to compensate for potential challenges or underestimate them due to a lack of awareness of underlying complexities. This can result in unrealistic deadlines or inefficient resource allocation.

Best Practices for Estimating Tasks in Non-Full Stack Teams:

  1. Collaborative Grooming Sessions: Conduct grooming sessions where team members can collectively discuss and refine tasks. These sessions enable knowledge sharing, help identify dependencies, and foster collaboration. Encourage team members to ask questions and gain a better understanding of the task at hand.
  2. Task Breakdown: Break tasks into smaller, manageable subtasks. This approach allows team members to estimate individual components they are familiar with, reducing the risk of overlooking potential challenges in unfamiliar areas. It also promotes transparency and accountability within the team.
  3. Peer Consultation: During the estimation process, encourage team members to seek advice and opinions from colleagues with relevant expertise. By leveraging the knowledge of others, team members can make more informed estimations and mitigate the risks associated with specialized knowledge gaps.
  4. Iterative Refinement: Recognize that initial estimations may not always be accurate, especially when dealing with unfamiliar domains. Embrace an iterative approach, where estimations are refined based on feedback from the team, retrospectives, and previous project data. This allows the team to improve their estimation accuracy over time.

Hybrid Approach: Final Say on Estimation:

While collaborative estimation is valuable, it is crucial to acknowledge the importance of specialized knowledge and individual expertise. In non-full stack teams, it can be beneficial to give the person working on the task or the individual with core competency the final authority on the estimate.

This approach ensures that the estimate aligns with the person’s understanding of the task and their expertise in the relevant area. However, it is essential to establish open channels of communication, allowing team members to challenge or discuss estimates constructively.


Estimating tasks in non-full stack agile teams comes with its own set of challenges. By following best practices such as collaborative grooming sessions, task breakdown, peer consultation, and iterative refinement, teams can overcome these challenges and improve estimation accuracy.

Adopting a hybrid approach, where the person working on the task or the one with core competency has the final say on the estimate, strikes a balance between collective collaboration and specialized knowledge. By implementing these practices, non-full stack teams can enhance their estimation process, leading to more realistic timelines, better resource allocation, and improved project success.