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IT Manager with a proven ability to manage IT resources, maintain secure systems, and support digital transformation initiatives. Known for problem-solving, effective communication, and delivering high-quality IT services.

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The hidden problem with AI agents: they don't just answer, they act

For a long time, most AI conversations were about answers.

Could a chatbot write a better email? Summarize a document? Explain a concept? Even when the output was wrong, the result was usually a suggestion that a person could accept, reject, or ignore.

Agents change that dynamic a bit.

An AI agent might update a CRM, approve a workflow, modify a database record, send a message to a customer, or trigger actions across multiple systems. At that point, the conversation is no longer just about the quality of the answer. It's also about the consequences of the action.

We built the wrong feature for 3 months. Our most-requested feature told us.

For three months, the #1 feature request in Murror was "let me share my journal entries with my partner."

It made perfect sense. Murror helps you understand your emotions and relationships. Sharing seemed like the obvious next step. Our roadmap was built around it. We designed the UI, built the sharing flow, even wrote the notification copy.

21d ago

How do you prioritize inbound messages after launching?

Hey PH,

After launching, I noticed a big increase in inbound messages - agencies, tools, consultants, AI assistants, and more. Some of it is genuinely useful, some of it is unexpected, but I'm curious how other Makers approach this!

Do you have a system for prioritizing what to respond to? Do you categorize outreach, set filters, or use any tools to manage it?

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