Story points are an estimation technique used in Agile project management methodologies to help your team scope the effort required to complete a task. Story points account for factors like task complexity and uncertainty, which makes them more accurate than other estimation techniques such as time-based estimation. Estimating story points may sound complicated, but we’ve got you covered—we’ve broken down the process into six simple steps.

Outsourcing has been an important part of many big businesses’ plans since the 1990s. Many businesses have moved operations to places like Brazil, the Philippines, and India in the past to save money on labor costs. These countries now have inexpensive call centers and IT services. Because of this setup, which was made possible by fast data networks, work could be done almost as quickly as if it were done in person, but for a lot less money.

Are you struggling to find ways to be productive? You’re not alone. Productivity is something that most people struggle with at some point or another. But don’t worry – you can do several activities and strategies to be more productive in your day-to-day life. This guide will get you more out of your day by setting achievable goals, organizing your time and workspace, and using productivity tools and techniques. Let’s get started!

If you work in a fast-paced business, it’s not hard to see why real-time analytics might be valuable. Being able to analyze live (or near-live) data can help you and your team react faster, and make more informed decisions in the moment. Setting up analytics and reporting systems always has the potential to cause a headache – this is especially true when it comes to working with real-time data.

Finding the right DevOps talent to accomplish a seemingly endless series of complex technical tasks has become a top priority for organisations. As businesses strive to increase agility and scalability with the use of enterprise-grade cloud architecture, adopting practices like continuous integration and continuous delivery (CI/CD) become highly sought-after.

The way companies track and manage workforce productivity is changing. The change is more frequent for companies with teams working from home or in different places. The tools and methods used before to track productivity do not work well now. Most businesses are switching to web-based trackers for productivity monitoring. Many business leaders feel pressure from management to make teams more productive. A report says 71% of business leaders feel this pressure.

We recently heard from some in the Slack community that our published privacy principles weren’t clear enough and could create misunderstandings about how we use customer data in Slack. We value the feedback, and as we looked at the language on our website, we realised that they were right. We could have done a better job of explaining our approach, especially regarding the differences in how data is used for traditional machine learning (ML) models and in generative AI.

For non-developers, AI can seem like a black box. The concept of AI prompting sends a chill down our spines, especially when we’re bombarded with complicated examples and techniques. Multi-agent prompting? Prompt chaining? ReAct prompting? Sounds too much like the CompSci 101 course we failed in college. But according to Ethan DeWaal, Asana’s AI Program Manager, AI prompting doesn’t have to be complicated.