I built a workflow to select music for a senior fitness class that suits the participants’ general age range and meets the program’s criteria of approximately 120 BPM. I also require the music to be danceable and have a 4/4 beat. After a successful summer using AI-suggested, danceable Motown songs from the 1970s, I continued using AI to help with music selection. I don’t have a music background or the knowledge to do this myself, so I appreciate the help. Yesterday, a participant commented on how enthusiastic she was about the music. Her response was simple: “I love the music.” Step-by-step: 1. I considered the general age range of the senior fitness class participants. 2. I used the program’s target of approximately 120 BPM as a selection criterion. 3. I added my own requirements that the songs be danceable and have a 4/4 beat. 4. I used AI to suggest songs that fit those criteria, including danceable Motown songs from the 1970s during the summer. 5. I used participant feedback to confirm that the music was well received.

Mid- and end-of-year self-evaluations used to cost me a week or two of reconstructing a year of work from memory. I rarely recorded or remembered the “small things,” and I couldn’t easily explain how my daily work connected to our goals. People often forget their most impactful work months later, so I wanted continuous capture instead of annual reflection. I also wanted my work goals and development plan grounded in real evidence rather than guesswork. I built an “Achievement Collector” agent as a sub-agent of my Chief of Staff agent. When my Chief of Staff agent recognizes something important, it formats the accomplishment into an Achievement record, asks whether I want to record it, and sends it to the Achievement Collector agent. SharePoint is the system of record, with fields including Details, Business Impact, Key Insights, Related Goal, Significance, and a flag for accomplishments I’m especially proud of. A Power Automate flow lets me log an accomplishment conversationally instead of filling out a form. A Copilot Studio agent sits on top of the list and reads three work-goal documents—mine, my manager’s, and my director’s—so it can map each accomplishment up the chain. Its instructions tell it to prioritize what I’m proudest of, group work into themes, surface business impact, and never invent anything. The result is that my self-evaluation and goal-progress summaries are now queries against real records instead of writing projects. If you want to build one, start with the data-list fields: capturing impact and insight at the moment of the work is what makes everything downstream possible. The combination of my Chief of Staff agent and Achievement Collector has made work a lot more fun for me and turned me into a laser-focused employee. Step-by-step: 1. I created an “Achievement Collector” agent as a sub-agent of my Chief of Staff agent. 2. I configured the Chief of Staff agent to recognize important work, format it into an Achievement record, ask whether I want to save it, and send it to the Achievement Collector. 3. I created a SharePoint list as the system of record, with fields for Details, Business Impact, Key Insights, Related Goal, Significance, and a flag for accomplishments I’m especially proud of. 4. I used Power Automate to let me log accomplishments conversationally instead of filling out a form. 5. I placed a Copilot Studio agent over the SharePoint list and three work-goal documents: mine, my manager’s, and my director’s. 6. I instructed the Copilot Studio agent to map accomplishments up the goal hierarchy, prioritize what I’m proudest of, group work into themes, surface business impact, and never invent anything. 7. I now query the accumulated records when creating self-evaluations and goal-progress summaries instead of reconstructing my work from memory.

I submit two reports to my directors each month. Both use structured templates, but the updates come from multiple people and sources. Some information is unstructured, such as hallway conversations that are not always captured in email, so I have struggled to get the accuracy I need when using AI to build the reports. I am currently testing CoWork and Copilot Work IQ. These reports used to take me hours, so I am already saving time, but I want to refine the process further. I believe a better way to save and store the source data could improve the final outputs, although I have not worked out the right approach yet. Step-by-step: 1. I collect updates from multiple people and sources for the two monthly reports. 2. I organize the information into the structured templates required by my directors. 3. I use CoWork and Copilot Work IQ to help build the reports. 4. I account for unstructured updates, including information from hallway conversations that may not have been captured in email. 5. I am exploring better ways to save and store the source data so I can improve the accuracy of the reports while continuing to save time.