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

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?

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:

Meow world, welcome back to The Breakpoint, a weekly thread on all things dev tools on Product Hunt.

The latest

Recent dev-first products launched on the site.

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?

Being an engineer myself, I see that many people are outputting more code than ever. Some of it being generated vs. written, the volume of code being outputted has definitely risen. 
There seems to be a shift from "is this something we can build?" to "should we build this and ship it?"
For people who have been recruiting or looking to recruit recently, what roles are you hiring for? 

1. Role title (I've seen a rise in PM's and Designers personally)

2. What exactly can they do that AI can't (yet)

3. Specific signal that you look for when hiring

Are you moving headcount from one type of role to another? 
Would be interested to hear from other growing teams! 

Hi everyone

We re launching Needle AI Agents tomorrow!

Our goal is to help teams automate processes and build AI Agents with context of their own data sources (Google Drive, Notion, Slack, etc.).

I am attempting to observe what you use for coding. I have come across many tools on Product Hunt + Web, but I am fairly certain I have missed quite a bit.
I divided them into "traditional" and "specialised".

Traditional AI models:

DeepSeek

At this point, all of the AI coding assistants are in the same neighborhood. Decent at "advanced autocomplete", OK at code generation sometimes, and most are somewhere in the process of incorporating code context mechanisms. But what's next? Agentic behavior? Something else?
My pet prediction is that we will see the emergence of a new programming language that's designed for use with AI and can be translated to a variety of popular languages. (Or if we're cursed, just javascript )

A few years ago, AI at work meant smarter autocomplete or a chatbot on your website.

Now, I m seeing something different.

Companies are experimenting with AI agents as teammates - not just tools. They schedule meetings, file reports, analyze data, and even handle parts of customer support.

I was recently talking with a group of founders, and we went around sharing tools we're using now. Posting my notes for our community here - would love to know what else people are using!

Voice AI toolkit:

- Vapi

For years, "learn to code" was a golden rule for career growth. But with AI assistants writing entire functions, debugging code, and even generating full applications, is traditional coding knowledge still essential?

Will the future of development be prompt engineering rather than coding?

Will AI make deep knowledge of algorithms and system design more important, while reducing the need for syntax memorization?

If AI does the coding, what skills will become most valuable for future developers?

ICYMI: @levelsio shipped a flight simulator game last week. It's pretty fun, it's got some low poly / minecraft-esque graphics, pretty good physics, a turbo boost, and even PvP. The kicker is he built it, at least the version one anyway entirely by prompting @Cursor.

It got me thinking about a question that a ton of people have tried to answer in the past few years; What does the future look like for someone getting into development?