Podcst generated by NotebookLM
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Let’s be real for a second. We’ve all been there. That weekly team meeting where everyone rattles off their updates, you try to keep up, and by the end, you’re not entirely sure what just happened. Or maybe it’s the feedback cycle that feels a bit… lopsided. We’re great at remembering what went wrong, but what about celebrating what went right?
My brain’s been buzzing lately with some thoughts on how we can flip the script on this, especially with the help of those ever-evolving Language Models (LLMs) – you know, the tech behind things like ChatGPT. And it’s not just about productivity hacks; it’s about making us better communicators, better teammates, and ultimately, better at what we do.
The Meeting Maze: Less Talk, More Action
Think about it: we’re all busy. Yet, a significant chunk of our week can vanish into meetings. Imagine a team of 20, each giving a quick update. Even at a fast speaking pace, that’s a lot of time. And how much of that is truly engaging?
What if we could drastically cut down on the “what I’m working on” monologue and instead focus on the good stuff: discussion, problem-solving, and genuine collaboration?
The key? Data. And a little help from our AI friends.
Instead of spoken updates, what if we shifted to super-short, written updates (think 50-75 words)? Tools like Google Forms, Microsoft Forms, or even a simple shared document can make this painless. The beauty is, everyone can quickly jot down their status, successes, problems, and pending items.
Then, when we gather, the updates are already there, in writing. We can quickly read what’s essential (we read faster than we speak, after all!) and then use our precious meeting time for what really matters: diving into discussions, tackling roadblocks, and strategizing. Less “What’s Bennett doing this week?” and more “How can we collectively solve X problem?”
The Power of Positive: Let LLMs Be Your Cheerleader
Here’s where LLMs really shine. As project managers (or anyone leading a team), we’re wired to identify issues and offer constructive criticism. It’s vital, yes. But we often forget to champion the successes, the “wins,” big and small.
Why? Because humans are surprisingly good at remembering the struggles. We focus on the challenges. But that means a lot of great work can go unnoticed.
This is where LLMs can become our secret weapon for positive reinforcement. Imagine this: you collect those short weekly updates. An LLM can then sift through them and, with the right prompt, generate genuinely positive, specific feedback for individuals or the team.
Think about sending an email that says, “Hey Alice, remember a few months ago when you were grappling with X? You totally nailed it and now you’re crushing Y! That shows incredible growth and resilience. We value you!”
This isn’t just about fluff. It’s about acknowledging effort, celebrating learning, and reminding people of their inherent value to the team. It builds morale, reinforces good habits, and fosters a more supportive environment.
A crucial caveat: When it comes to negative feedback, always, always let that be your human voice. LLMs, trained on the vast (and often negative) expanse of the internet, can go dark fast. Use them as a sounding board, an AI coach, perhaps – but the tough conversations? Those need your empathy, nuance, and personal touch.
Turning the Lens Inward: AI for Managerial Growth
So, we’re using LLMs to celebrate our teams. But what about us, the managers? This is where it gets really interesting.
Instead of just tracking team progress, what if we used LLMs to reflect on our own performance? We have the data from those weekly updates, the problems faced, the successes achieved. We know the biases in our data.
Why not ask the LLM:
- “How am I doing as a project manager?”
- “What common challenges has the team faced that might reflect on our processes?”
- “What trends can be identified in our team’s struggles?”
- “How can our processes be improved?”
Imagine getting insights like: “Several instances show a need for more structured support and training,” or “Feedback mechanisms could be enhanced.” This isn’t about the AI criticizing your team; it’s about the AI helping you see patterns and areas for your own growth as a leader.
You can then take these insights back to your team, open up the discussion, and collectively figure out solutions. It transforms feedback from a top-down assessment to a collaborative improvement journey.
The Scrum Connection: Retrospectives Reimagined
And this brings me to a thought that’s been bubbling up: Scrum retrospectives. This whole approach – reducing meeting noise, focusing on discussion, amplifying positive feedback, and using data to improve management – is precisely what retrospectives are designed for!
Imagine layering LLMs onto your retro process:
- Pre-Retro Input: Team members fill out those short forms with blockers, successes, shout-outs, pain points.
- LLM-Powered Synthesis: The LLM summarizes patterns, surfaces recurring themes, or even auto-generates “start/stop/continue” clusters from the data.
- Tone-Adjusted Kudos: The LLM helps you craft specific, positive feedback examples for the “What went well?” part.
- Reflective Prompts for You: The LLM can suggest questions for the Scrum Master to ask the team, based on the data, to uncover hidden process problems.
Prompt Engineering Example: “Based on this list of weekly team updates, generate three themes of concern, two areas of improvement, and one major success to highlight during our next sprint retrospective.”
See? It’s not just a productivity hack. It’s about empowering us to foster truly collaborative, supportive, and effective teams.
So, let’s embrace the power of LLMs not just to transform information, but to transform our human interactions. Let’s be positive outwards, constructive inwards, and keep learning and growing together.
What are your thoughts on using AI to make our team interactions better? Share in the comments below!
