Laura Dansbury
SVP of Product and Content at Candova
Laura has spent more than 15 years building and scaling products across consumer and B2B, with product and UX leadership roles at LinkedIn, Ancestry, and Movoto before Study.com and Candova. Her work has consistently centered on the same thing: turning a strategy into a product real people actually use, and getting the conversion and growth numbers to prove it.
At Candova her remit spans product, content, B2B product marketing, design, and user research, and she closely oversees the engineering scrum teams. That cross-functional vantage point shapes how she thinks about AI: not as a feature to bolt on, but as something a team has to adopt into the daily work, with editorial and design quality intact and the scrum teams actually shipping with it. She is most interested in the gap between an AI tool existing and people building real capability with it.
She writes here about AI in product, content, and delivery: how to build with AI without losing craft, how to get a team to genuinely adopt it, prompting and agent patterns that hold up in real work, and what enablement looks like when the goal is leveling people up rather than watching them.
Latest from Laura
Claude for Teams: what it is and whether it's worth it
Claude for Teams brings Anthropic's plans to your business, with shared projects, admin controls, and security. Here's what's included, what it costs, and when the seats pay off.
June 21, 2026 · 5 min read
AI toolsWhen to use a reasoning model, and when a fast one wins
Reasoning models think before they answer, which helps on hard, multi-step work and wastes time on everything else. Here's how to tell which one a task needs.
June 20, 2026 · 5 min read
AI tools10 custom GPT use cases that actually save time at work
The custom GPT use cases that save real time share two traits: a repeated task with a fixed output, and context a generic model can't know. Here are ten worth building.
June 19, 2026 · 6 min read
AI toolsHow to build agentic workflows that hold up on real work
An agentic workflow lets an AI plan and adapt instead of following a fixed script. Here's how to build one that's reliable, and how to know when you don't need one at all.
June 18, 2026 · 6 min read
AI transformationAI training doesn't fail in the classroom, it fails on Monday
You trained everyone and the AI is still idle. Training is the input; adoption is where it dies, on the Monday when nobody reinforces what was taught.
June 17, 2026 · 5 min read
AI toolsHow to build a custom GPT that your team actually uses
Building a custom GPT takes about ten minutes of clicking. The part that decides whether it's useful is picking one real task and writing the instructions, and that's the skill worth learning.
June 16, 2026 · 6 min read
AI transformationAI experimentation beats the mandate, without the free-for-all
Mandates trigger resistance and free-for-alls stay shallow. The real choice isn't mandate versus experiment, it's supported versus unsupported.
June 15, 2026 · 6 min read
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