Everything discussed in AI Labs content is experimental, in progress, and not guaranteed to become part of the Degreed product suite.
I had to give some difficult feedback to a teammate. It was a conversation I was dreading. Then, because I saw the upcoming meeting on my calendar, my Invisible coach Slacked me. Instead of a refresher on how to give feedback, it checked in and walked me through the specifics of preparing for that particular conversation. It addressed what I was nervous about, where my skill gaps were, how I could improve, and an interactive role play to practice the exact conversation I needed to have.
The situation is hypothetical, but the personalized coaching prototype I just described isn’t. That’s Invisible, an AI Labs experiment. It’s a coach that brings learning into existing work, inside the tools you already use, providing relevant, task-based learning when you need it.
Organizations now run about 10 planned change programs a year, five times more than the number they ran a decade ago, according to McKinsey. People don’t need another place to go to keep up, another interface or tool they need to navigate to. Coaching should come to them with the context, the expertise, and the learning opportunities that pop up during everyday work.
Embed Learning Anywhere and Everywhere
The first layer of this prototype is simple. Meet people where they already are: Slack, Teams, a text message, Gmail, or directly inside Claude, Gemini, or ChatGPT. No separate login or single-purpose destination.
This sounds like no big deal until you consider it in practice. A manager with a question about giving tough feedback likely isn’t going to open a random learning portal to find the answer. They might just ask Claude, though, and what if Claude already knows how to help and has the context to offer personalized coaching? Context is the background information on the user and the organization, like their role, existing skills and proficiencies, which skills are prioritized in the business, and even employee performance data.
So this would be a coach that works wherever you do (and knows what you know), meaning learning opportunities are everywhere, even in real work.
Trigger Development Opportunities From Real Experiences
The other thing about coaching is that it works best if you get it when you need it most. Coaching that passively waits for you to find it during downtime will usually miss the moments that matter most.
So the second layer to Invisible is event-based triggers. Maybe it’s a calendar invite for a performance review or a program milestone that is coming due. Invisible watches for these moments across various connected platforms and offers coaching in advance, turning a lesson into an essential dress rehearsal. I don’t have to wing it because I didn’t have time to prepare. My coach saw it coming and proactively offered assistance. That’s a natural learning-in-the-flow-of-work moment.
Tailor Coaching to Individual Needs
Invisible builds what it calls a program: a sequenced set of steps generated for one person, based on their goal, their last session, and a scenario that fits their situation. It reads a profile, uses the need to build the scenario, and tunes the difficulty before a session even starts, the way a great manager would if they had perfect memory and infinite time.
Let’s revisit my feedback conversation as an example. I didn’t get a lesson on how to give tough feedback in general. Instead, I got help with the one conversation I actually needed to have. I learned to address the task, not the topic. Suddenly, everything the coach offers is applicable.
You can even use this to develop better AI fluency. We’ve been using Invisible to teach people Claude inside of Claude, for example. Invisible can run these coaching sessions inside Claude, pulling in real context from the tools someone already has connected to their AI agent ecosystem. It means people learn how to work with AI through the actual task in front of them, instead of in a separate, generic course.
Make Upskilling More Visible with Invisible AI Coaching
The coaching may be “invisible,” but the outcomes are more evident than ever. Employees show up to hard conversations better prepared. Teams actually use the AI tools they have, because the coaching meets them inside those tools.
Change isn’t slowing down, so learning can’t either. Coaching that shows up on its own and adjusts to the moment, the situation, and the individual is a much better fit for a workplace that won’t hold still long enough to schedule a course around it.
As a reminder, a lot of what comes out of AI Labs stays in AI Labs, and Invisible is still an experiment. We’re iterating on it every day, but that means you still have an opportunity to be part of the journey.
If you want to see where this goes, follow or message me on LinkedIn. I’m happy to share the process and get your input.
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