My favorite usage of AI currently is helping me prototype and bring to life internal tools that help me with my daily life.

I am preparing for job interviews so I built a tool to help prepare for technical questions.

I am networking so I built a tool to help break the ice at events.

If you're building a product with AI tools, here's how your morning probably looks:

• Open ChatGPT. Paste your project context. Ask your question. Get a decent answer.

• Switch to Claude for something else. Paste your context again. Different tool, same briefing.

• Hop into your codebase with Codex. Paste context again.

You're not just a builder anymore. You're a context delivery system.

The indie hackers I've talked to who use AI most effectively have one thing in common: they've figured out how to stop babysitting their tools and just use them.

A lot of teams already manage work inside Gmail and Google Workspace. Customer conversations happen in email threads, follow-ups come out of meetings, and project coordination lives across tasks and boards throughout the day.

Keeping CRM records and project workflows aligned with all of that activity still takes a surprising amount of manual updating afterward.

We've been getting the same request over and over from our users: "My AI gives great answers, but it can't actually do anything."

It got us thinking most AI integrations today are still essentially fancy search boxes. The AI talks, the human acts. But the real unlock is when the AI can close the loop itself query the database, send the email, update the record without a human in the middle.

The hard part isn't the action itself. It's the non-determinism. How do you build a system where the AI decides when to act, which action to take, and what parameters to pass based purely on context without it going off the rails?

A few things we've learned building this:

We just wrapped the Orbit Awards for AI Dictation and now we re moving to the next category: AI Automation.

This one is for the tools that actually do work for you clearing chores, running workflows in the background, or quietly taking over a chunk of your week without turning into another dashboard you have to babysit.

We've been getting the same request over and over from our users: "My AI gives great answers, but it can't actually do anything."

It got us thinking most AI integrations today are still essentially fancy search boxes. The AI talks, the human acts. But the real unlock is when the AI can close the loop itself query the database, send the email, update the record without a human in the middle.

The hard part isn't the action itself. It's the non-determinism. How do you build a system where the AI decides when to act, which action to take, and what parameters to pass based purely on context without it going off the rails?

A few things we've learned building this:

We re officially in nominees season for the Orbit Awards: AI Workflow Automation.

Teams aren t just adding AI into existing workflows.
They re reshaping the workflows themselves with the AI agent in the loop.

Steps get removed.
Objectives become clearer.
Old constraints disappear.
Processes reorganize around what the system can now do natively.

The real productivity gain isn t automation.
It s rethinking the architecture entirely.

Curious to hear from this crowd:
What s one workflow you rebuilt because AI made the old version irrelevant?