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...

We ve been growing really fast (30%+ MoM ARR) at @Basedash since launching last year. Most of that growth has been the result of hard work, but we ve also had a secret weapon: an AI agent that acts as both a data analyst and a PM, working 24/7 to optimize our product s activation and conversion rates.

For decades, companies have been making product decisions based on intuition and manual data analysis. We wanted to see what would happen if AI could take the wheel completely.

We ve been growing really fast (30%+ MoM ARR) at @Basedash since launching last year. Most of that growth has been the result of hard work, but we ve also had a secret weapon: an AI agent that acts as both a data analyst and a PM, working 24/7 to optimize our product s activation and conversion rates.

For decades, companies have been making product decisions based on intuition and manual data analysis. We wanted to see what would happen if AI could take the wheel completely.

I would like to hear from data analysts or those whose primary job involves working with data irrespective of their role -

How has AI changed your role?

The Good: What's one thing you like that AI has done to make your professional life easier

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.

I was reading this recent @OpenAI article about Gartner naming OpenAI a Leader in enterprise AI coding agents: https://openai.com/index/gartner....

"Software development is becoming more agentic." This is a good summary of what is happening right now. We are moving from AI that helps you write faster, to AI that can take over tasks (actions, use tools, make changes, run tests, and bring the work back for human review). That is a very different behavior.
The article gives Cisco as an example. They used Codex for a big part of their AI Defense platform and reduced delivery time from several quarters to a few weeks.

Last week, six AI products launched on Product Hunt that share one move. None of them ask users to open a new app. They embed into surfaces people already touch.

Hardware: Dune Keypad (46 upvotes) sits next to your keyboard with Claude integration. Video calls: Mina Meeting Assistant (47 upvotes). Text threads: folk (51 upvotes). Chat windows: Databox MCP (39 upvotes) plugs business data into Claude via Model Context Protocol. Mac autocomplete: Typeahead (22 upvotes).

The pattern is clear: shipping AI as a new app is the slow path. The fast path is grafting onto a surface the user already touches. The cost of building a standalone AI app dropped 90%+. The cost of getting it noticed did not. Surface integration sidesteps the noticing problem because the surface already has users.

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?

AI agents are everywhere right now.

They help with launch copy, visuals, outreach, follow-ups basically most of what used to take days can now be done in hours.

But I keep thinking about something. Are AI agents actually improving product discovery on Product Hunt or are they just making launches look more polished?

Yes, AI speeds things up. You can test messaging faster, create better assets, prepare more efficiently.

LinkedIn officially shared the job titles that started appearing more often, and with the rise of AI, the market is restructuring.

The actual top 10 roles that have seen the biggest rise in listings (in the U.S.) are:

1. AI engineers Engineers developing and implementing AI models that perform complex tasks

2. AI consultants and strategists - Helping organisations plan and implement AI technologies to improve operations

3. New home sales specialists Which sounds like a rebranding or real estate agent

4. Data annotators Labelling and reviewing data for AI projects

5. AI/ML researchers Designing new AI models and systems

6. Healthcare reimbursement specialists Ensuring healthcare providers are getting correct and timely payments

7. Strategic advisors and independent consultants Which seems like a pretty broad-ranging segment

8. Advertising sales specialists You re reading a marketing blog, I assume you know this one

9. Founders Not sure this can be listed as a job title in itself, but LinkedIn s keen to highlight how people are shifting to their own businesses

10. Sales executives

Everyone s been talking about AI Agents over the past year.

But the real leverage doesn t come from the agent itself. It comes from the context you provide: