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

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.

I have been looking at what is actually getting traction on Product Hunt right now. The pattern is clear.

In March, OpenClaw products dominated the leaderboard. Anything with "Claw" in the name got votes. That was a land grab new space, everyone rushing in to claim a spot .

In April, that stopped. The "just build an agent" strategy stopped working. What replaced it? Products that do specific tasks inside workflows you already have .

Here is what the data shows.

One of the more interesting things we have learned while building Causo is that people ask for automation, but what they really want is productivity. Those sound like the same thing but actually aren't.

Ask someone what they want from an AI sales tool and the answer is usually:

Just find the leads, write the emails and run the outreach for me.

But the moment the tool actually tries to do that, the questions start: where did this company come from; why does it match my ICP, is this person still working there; where did you find this information; can I change the email; has anything been sent yet?

I spent years watching talented people waste hours moving information between

emails, spreadsheets, CRMs, documents, calendars, and internal systems.

That s when I started developing Lynx OS.

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?

@Zapier, @Make, @Relay.app , @n8n , @Activepieces, @Pabbly
So many automation tools in 2025!

I cannot decide what to choose for beginners but with a wish to become a pro user
From my recent research, quick insights

• @Zapier still wins for ease-of-use and integrations, but might be expensive and has low free limitations

• @Relay.app is amazing for beginners due to built-in AI workflows

• @Make remains top for complex automation

My takeaways for new users from my one day research

last week, I shared an update on everything Inr has shipped over the last 20 months in automation, CRM, and integrations.

today I am doing a final update on the bigger shift coming this Saturday 25th: Inr is now an AI-first platform, and here's what that actually means.

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.

Six years ago I got into Y Combinator and built the first version of @Basedash: AI data analyst. It was a simple tool that let you edit data in your database.
Now, six years later, we have a whole new product, and again we're shipping... database editing. But this time it's a look into the future of how companies are going to be run.
At the surface, this feature is kinda neat but nothing new. You can ask the Basedash AI to edit things in your database or call MCP servers to take action in other tools.
But, being a BI product, Basedash has a super deep understanding of your business. Probably better than you do yourself.
Soon, Basedash will proactively start suggesting ways to make your business better.
"If you extend this user's trial, they'll have a 50% higher chance of converting"
"If you tweak your ad sequence with this copy, it'll increase conversion rate by 20%"
One click to approve and run the experiment.
This is how we transition to AI-run companies.

Please check out our PH launch for actions and give us any support or feedback: https://www.producthunt.com/prod...

What AI Dictation Tools Actually Are

What AI Dictation Tools Actually Are

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.

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:

There are so many new AI agent platforms ( @Wordware @Lindy @CrewAI @zapier and so on) that I'm finding myself curious how everyone is using them.

What AI agents are you using in production? What do they do? Are they working and reliable? What would make them better? Are they replacing roles? Augmenting existing ones?

Hey PH Kshitij here from Inr .

We launched here back in 2024, which gave us a real platform to kickstart our journey, and the feedback from this community has genuinely shaped how we built Inr .

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:

With AI agents and assistants are becoming more advanced, we're seeing them handle everything from scheduling meetings to managing entire workflows.

But here s the big question would you fully trust an AI to run tasks autonomously, or would you prefer keeping an eye on things just in case?

Hello Product Hunt friends!

Juan checking in from the community team. Hope your week is off to a great start!