Argos, the AI agent driving Neodigit's growth: our own use case

For the past few weeks, I’ve been building my own autonomous agents to drive Neodigit’s growth. The latest one: Argos.

A growth strategist that runs on its own every morning

Specifically, every morning, Argos:

• reads our current priorities,
• suggests the day’s actions, sized to fit into a short window,
• drafts ready-to-copy content,
• sends me a message with the plan.

While I drink my coffee, the prep work is already done. All I have to do is validate and execute.

Why I’m documenting this publicly

This isn’t a communication exercise. It’s exactly what we build at Neodigit for our clients: AI agents that take on real, measurable tasks, not gadgets that put on an impressive demo and stop there.

Argos is our own use case. We’re testing it on our own business, with our real constraints (tight time budget, cash budget close to zero at the start), before offering this type of agent to our clients.

What’s next: the failures as much as the wins

An autonomous agent is built through iteration, not in one go. The next posts in this series will also document what doesn’t work on the first try, not just the wins.

Have a similar use case?

If a repetitive task in your organization could be handled by an AI agent (reporting, sales follow-up, customer support, monitoring), let’s talk.