How I use ChatGPT & Claude + Carbon Voice to Supercharge Team Productivity

We recently added an MCP (Model Context Protocol) Server to access Carbon Voice and it has been a paradigm shift that has helped to unlock new workflows to boost productivity.

MCP is the way AI agents such as ChatGPT, Claude, Cursor, Windsurf, and others can connect to services to access information. With this connection, your AI agent can answers questions about Conversations and Voice Memos found in Carbon Voice.

One of the most compelling aspects of Carbon Voice is a simple fact: speaking is four times faster than typing. This fundamental efficiency unlocks tremendous potential for getting ideas out quickly and with more details, especially when working with teams. 

Sometimes it's as straightforward as having rapid back-and-forth conversations. Other times, we can literally fold time by having everyone speak simultaneously and then using AI to extract the meaningful insights from all that concurrent input.

“The real game-changer is how AI can now take all this voice-delivered content and transform it into well-structured, actionable information.”

The real game-changer is how AI can now take all this voice-delivered content and transform it into well-structured, actionable information. Now that our MCP Server is available, I thought I’d share some of the prompts I've been experimenting with to create more efficient workflows across various team processes, and the results have been awesome.

Revolutionizing Team Retrospectives

I hacked our a retrospective:

• I asked everyone to post into a Carbon Voice Conversation at the same time.

• I then asked Claude:

We have an engineering team retro with messages posted into "Retro June 27" summarizing the Sprint in Carbon Voice.  Please summarize the this in a Retro format of:

* Overall team sentiment (roll-up score)

* What's going well (Group related areas)

* What's not going well (group related areas)

* What could be done differently next Sprint (group related areas)

See the write up with a video showing the output here.

Streamlining Daily Standups

Our daily stand ups happen in Carbon Voice most days of the week, with everyone sharing their updates naturally through speech. Instead of scrambling to take notes or remember who's working on what, I can quickly key questions: 

Based on the discussion in Daily Update in Carbon Voice, what is everyone working on?Based on the discussion in Daily Update in Carbon Voice, is anyone blocked on anything?Based on the discussion in Daily Update in Carbon Voice, does anyone need me for anything?

Transforming Interview Processes

We recently ran a candidate interview process using Carbon Voice that saved the candidate 3–4 hours, saved each interviewer about 30 minutes, and helped reduce bias in our decision-making—while still getting to a faster, more confident outcome.

Here’s how it worked:

1. Async interview: I recorded the initial conversation in Carbon Voice, asking standard interview questions. The candidate listened and replied.

2. Team follow-up: I added the team so they could listen in and contribute follow-up questions—avoiding repetition while allowing deeper exploration.

3. AI review: After we made a decision, I asked Claude for a final review to surface anything we might’ve missed and validate the outcome with a more objective lens.

In the Carbon Voice Conversation with id <conversation_id> , there is a discussion interviewing <name>. If you were a hiring manager for her as a <role type> role, how would you rate this candidate?

See the writeup and details here.

Filing a JIRA bug

We’ve made bug reporting fast and effortless by combining voice messaging with AI. Instead of switching tools or writing out reports, we just talk about the bug in Carbon Voice—and let AI do the rest.

Here’s how it worked:

1. Describe the bug in a Carbon Voice thread

   Speak naturally—what’s happening, what’s expected, and any relevant context.

2. Make sure Claude is connected to JIRA as well as Carbon Voice.

   “In this conversation, a bug is being described. Please extract the relevant details and file a Jira ticket.”

3. Claude files the ticket

   Claude generates the Jira ticket and posts the link back into the Carbon Voice thread automatically.

In the Carbon Voice Conversation with id <conversation_id> (or XYZ team members) , there is a discussion about a bug. Create and file the bug in Jira and assign it to <team member>. Share a link to the Jira back to the conversation.

See the how-to video here.

Engineering Support

Leverage discussions around a bug to point you to relevant code quickly:

Travis described a bug in the Bugs conversation in Carbon Voice, can you look at the code and find where that is happening?

Enhancing Team Relationships

The applications extend beyond just operational efficiency. I've started using the system for interpersonal development and team dynamics:

Tone evaluation 

In the past month, how has my tone been with <person>?

This helps me maintain awareness of my communication style and its impact.

Continuous improvement

In the past month, when talking to <person> what are some better questions I could have added?

This prompts reflection on how to be more thoughtful and effective in my interactions and guidance.

Understanding team interests

Based on the conversations in Carbon Voice, what are the things that [team member] cares about?

This builds deeper empathy and connection within the team.

The Bigger Picture

What we're seeing here is the convergence of natural human communication with intelligent processing. By removing the friction of typing and note-taking, we can focus entirely on the conversation itself. The result is richer conversations and faster to get to them.

“What we’re seeing here is the convergence of natural human communication with intelligent processing.”

Then, AI steps in to do what it does best—processing, organizing, and extracting insights from large amounts of unstructured information.

This isn't just about saving time (though that's certainly valuable). It's about fundamentally improving the quality of our team interactions, making our processes more inclusive and unbiased, and creating space for deeper, more meaningful conversations.

The future of team collaboration isn't just faster—it's smarter, more intuitive, and more human.