GC AI Innovation & Technology Culture

What’s your rule for releasing fast — and what KPI proves it works?

The rule for releasing fast is: release fast. Release based on customer input. Release knowing you will iterate on most things, though occasionally you're going to have to be sure you've got the perfect solution the first time. 

The KPI that proves it works is sales. If you're not making something that people want, they're not going to buy it. Ultimately business is driven by people's willingness to buy what you have made.

Which standard or metric defines “quality” in your stack?

There is not just one quality metric. We have all the standards: linting, type checks, unit tests, integration tests and end-to-end tests. We have standards that we follow for consistency. We have AI perform scans on what we build. We have peers review what we've built. We have internal testing, alpha testing, beta testing. After something is deployed we have monitoring to be sure things are running well. We have an external third party test our functionality and another third party test for security.

The need for quality permeates all aspects of our development process... because quality is what establishes trust with the customer. Building that trust is critical.

Name one recent AI/automation shipped and its impact on the team or business.

For internal use, a big level up was a skill we call "transcript to triage." The skill is used by an AI agent and integrates with the Granola MCP and the Linear MCP. The agent grabs the transcript from Granola, breaks each request into tasks, then searches Linear for those tasks. If there's a duplicate then the agent logs the ticket that this idea was mentioned again. If not, then the agent makes a new ticket.

Converting calls to tickets a few years ago was such a pain. It would take a long time and things would always fall through the cracks. This feels like magic.