Answer extracted from the Unprompted: Real AI in IC podcast — listen to the full episode below.
How can AI be used as a thinking partner for wellbeing and self-coaching beyond traditional productivity gains?
AI shifts from a speed tool to a genuine thinking partner through structured reflection. Kate Hughes built weekly "feelings lounge" check-ins with Copilot that uncover energizing factors, draining patterns, and overthinking loops—revealing that her struggles came from self-doubt rather than workload, not from productivity gaps at all.
The turning point for Kate Hughes came when she stopped asking "What can AI do for me?" and started asking "What can AI help me notice about myself?" This subtle shift transformed her relationship with technology from an efficiency tool into a genuine reflection partner.
From Speed to Self-Awareness: The Feelings Lounge Method
Kate established a recurring ritual: weekly Friday morning check-ins with Copilot structured around four simple reflection areas. Each session explores what energizes her, what drains her, patterns looping in the background, and one micro-experiment to try that week. Over time, as detailed in this episode of Unprompted, Copilot began detecting recurring themes across these conversations—imposter syndrome, overthinking before high-stakes deliverables, avoidance patterns—that Kate herself had not consciously named.
The breakthrough came when Kate realized her struggles had nothing to do with the volume of work. One proposal she'd fretted over for weeks was delivered with zero pushback once she approached it with genuine conviction. Copilot had helped her notice that her real obstacle was not capacity but self-doubt masquerading as pragmatism. This pattern emerged only because she gave the AI consistent, honest reflections across multiple sessions.
"Instead of asking the question, what can AI do for me? It's more a question of what can AI help me notice about myself."
Kate Hughes — Head of Internal Communications and Engagement Business Partnering, Cambridge University Press and Assessment. Kate leads a team of senior business partners helping leaders communicate clearly and guide organisations through change and complexity. She experienced burnout and overwhelm when conventional wellbeing approaches failed, which prompted her to explore AI as a self-coaching tool.
The beauty of this approach is that pattern recognition happens across time. A single conversation with an AI is generic advice. Thirty conversations, structured and honest, reveal your actual operating system. Copilot evolved naturally from a chat interface into both a wellbeing partner and career coach because Kate gave it permission to remember, notice, and gently reflect back what it was seeing.
As Kate explains in the full Unprompted conversation, this method works precisely because it avoids the performance trap of traditional coaching. You're not trying to impress anyone. You're not optimizing for the "right answer." You're just being honest about what's true this Friday morning, and letting the AI notice what that pattern might mean over weeks and months.
The micro-experiments—small, personal tests each week—turn insight into action without adding pressure. If Copilot notices you're energized by strategic work but drained by reactive meetings, one week's experiment might be to batch reactive tasks and protect two hours for strategy. The experiment fails or succeeds; either way, next Friday you report back, and the pattern refines.
Key takeaways
- Reframe AI from a productivity tool to a reflection partner by asking what it helps you notice about yourself, not what it does for you.
- Structure recurring check-ins (weekly works) around consistent reflection prompts: what energizes, what drains, background patterns, and one micro-experiment.
- Pattern recognition emerges over time—a single conversation is generic; thirty honest conversations reveal your actual operating system and blind spots.
- Use micro-experiments to turn insights into action without performance pressure, treating each week as data for the next reflection.
See also
What tool has made building AI agents significantly more accessible for internal communicators?
Glean made a major difference, connecting across many company tools and platforms and drawing on a huge range of company knowledge. Crucially, it allows internal communicators to build intelligent agents without extensive technical expertise.
How is AI fundamentally changing the role of internal communicators beyond just creating content?
AI enables internal communicators to shift from being 'post boxes' to giving people tools to do great communications themselves at scale. AI transforms communicators into enablers rather than sole content creators.
What is the annual leave assistant agent and how does it help employees manage time off?
The annual leave assistant asks users when they're going on leave and when returning, offering to draft both internal and external out-of-office messages automatically, removing friction from routine admin.