I ve been working on some AI projects recently things like scheduled agents, API responders, and multi-agent systems that need to run continuously. One of the biggest headaches I ve run into is deployment.

Most cloud platforms (AWS, GCP, etc.) are built for stateless apps or short-lived functions. But for long-running, stateful agents, the kind that need to persist data, auto-recover from crashes, and expose custom endpoints it gets surprisingly messy. I ve spent so much time setting up VMs, Docker configs, and recovery logic than actually writing agent behavior logic.

I've been primarily using @Cursor as I like how it operates, enjoy that it's visual, and I am getting very comfortable with using it and being able to easily select different code bits and modify what I need....however....
I recently started using Gemini CLI in @Warp and I must say... I'm kinda liking it. I feel that it's able to do a lot more, faster without needing me to jump in. When I do jump in, it's simply to provide it guidence and direction.
I haven't done much with it yet, but I can see myslef now doing a combination of CLI and IDE development. I'm curious what everyone elses experience is! Or if you haven't used a CLI or IDE AI tool, why?
A bit of additional background, I'm not a develpoer but more of a "vibe coder" I can kinda understand different languages and don't mind diving into tech docs but I prefer AI do more of the coding than me :)

Hey Product Hunt Narayan here, builder of Metaflow

I ve worn two hats for most of my career.

Hat #1: engineer the one who loves clean abstractions and reliable systems.

Hat #2: growth marketer the one elbow-deep in campaigns, funnels, and dashboards, trying to find signal in the noise.

Hey everyone,

I m Salah, a solo dev who drinks way too much "tea" (sorry not coffe) and talks to his laptop like it s a colleague. After spending far too many late nights buried in spreadsheets, I decided to automate my pain away.

Enter Overstakes, an chaine of AI agent that takes the three things you actually know (your niche, your skills, and your vague business idea) and spits out a clear, no fluff opportunity report in minutes.

Why you might care (a concise list for busy humans):

I've been primarily using @Cursor as I like how it operates, enjoy that it's visual, and I am getting very comfortable with using it and being able to easily select different code bits and modify what I need....however....
I recently started using Gemini CLI in @Warp and I must say... I'm kinda liking it. I feel that it's able to do a lot more, faster without needing me to jump in. When I do jump in, it's simply to provide it guidence and direction.
I haven't done much with it yet, but I can see myslef now doing a combination of CLI and IDE development. I'm curious what everyone elses experience is! Or if you haven't used a CLI or IDE AI tool, why?
A bit of additional background, I'm not a develpoer but more of a "vibe coder" I can kinda understand different languages and don't mind diving into tech docs but I prefer AI do more of the coding than me :)

I built a tiny tool wfpage.com.

Paste your webhook get a public form + result page, no code or backend.

It s beta.

What s missing?

Anyone else grinding on a Saturday?

I just wrapped up planning for the next version of my SaaS....

...and how to add 500 more active users in the next 6 months.

Check out this Gantt chart. Looks like a real plan now, right?

Maybe this post will help makers understand how much people are willing to spend, what products are useful to them, and what the main motive for buying is.

I personally try to keep track of how much and what I spend. Before I invest in something, I consider:

• what will be the return on it (i.e. whether I will earn something by buying/investing in a product),

• whether it will be profitable for me in the long term,

• whether it will save me time.

Things can get chaotic, so many moving pieces and zero time to breathe.

I m curious: what s the one tool or automation trick you ve found that really cuts down your workload?

Bonus points if it s easy to set up and doesn t break the bank.

I built something to make job hunting easier.

My bot frequently scrapes jobs from 70,000+ company sites, summarizes them with ChatGPT, and an AI agent (built with Gemini) can auto-apply to the ones that match your profile.

Check it out: www.applyquick.ai

Would love your feedback!

We all have that one tool - the unsung hero quietly doing its job and saving you hours every single week.

For me (no surprise ), it s @Clueso

here to share a little about me. i started my journey in marketing and growth hacking, but lately i've been diving deeper into building things myself.

what i'm up to now: currently building apps and ai agents that solve real problems. mageresume is my latest obsession - using ai to bridge the gap between what job seekers write and what hiring systems actually want to see.

my toolkit: i live in the intersection of marketing automation and ai - combining tools like n8n, apollo.io, factors.ai, google analytics, and hubspot to build workflows and agents that actually move the needle. it's not just about using these tools individually, but creating systems where they work together seamlessly.

how i learn: pure experimentation. i'm a self-learner who believes the best way to understand something is to break it, fix it, and build something new with it. whether it's trying new libraries or testing out the latest automation tool, i'm always tinkering.

Why does it feel like every developer in the bay area announces ANOTHER MCP library to write client/servers for AI...the USB-C of AI they say, it feels to me like the nightmare of AI, because everything moves so fast and everyone is building more stuff (and barely maintaining it)

There are a lot of AI frameworks to begin with: LangChain. LlamaIndex. AutoGen. CrewAI. DSPy. OpenDevin. Semantic Kernel... They re all trying to answer one basic question:

'The best way to reliably interact with an LLM so that you can bolt things like memory, tools, and MCP to your AI agent'

I remember once discussing that intellectual property should be abolished (a quote by Jack Dorsey).

However, it seems that there is also a friendlier option that promotes more benefits for data owners:

Hey everyone,

We're the team building the LinkedIn Data API. Our whole focus is on solving a problem we've seen stall too many good ideas: the data bottleneck.

Whether it's for building a sales pipeline, a recruiting tool, or doing market research, getting structured data from LinkedIn is often a huge headache.
We believe developers should be building features, not wrestling with scrapers.

We're currently in beta and looking to connect with people who feel this pain. If you're building a project that relies on LinkedIn data, we'd love to chat and see if we can help.

Hey

We re super excited to introduce you to BrowserAI a powerful, serverless platform for AI-driven browser automation, web scraping, and data extraction at scale. Whether you're a developer, data scientist, or growth hacker, BrowserAI is designed to make your life easier when dealing with complex websites and anti-bot systems.

What is BrowserAI?

A lot of people I come across who are considering agents worry about the stochastic nature of LLMs. They don't want to trust them with complex tasks that require several steps because they might miss one or get it wrong. They worry that the agent will go off topic, access apps or generally do things they shouldn't. Even worse for regulated industries, you need to produce evidence of how you comply with different laws. Humans leave a natural audit trail of SOPs they follow, tasks they complete etc. so you can easily work with an auditor but what do you do when it's AI doing the work?

At Portia AI, we built an open source SDK from the ground up to address this challenge and we'd love to know if you think it meets the need and if there's something we can learn from others in this space. Agents built with Portia plan transparently, execute statefully, can be interrupted for human input and auth deterministically.

Let me know what you think if you have a moment? Your feedback would be super helpful

Your Voice. Your Brand. Now On Autopilot.

AI can talk, but can it sell like a real agent?

Just tested VoiceGenie AI and this one s different. Most AI voice tools sound robotic, cost a fortune, or take forever to set up.

It's been a while and I wanted to introduce my experience with AI agents.
After building with n8n I wanted to share some cheat sheets :
1. Pin Data During Testing

Cheat Sheet: Right-click Pin Data

When to use:

Imagine you are building a workflow where your AI agent gets information either from an API or scrapes articles from a blog, then summarizes them using an LLM. During testing, you don t want to hammer the website 20 times or burn through API calls every time you tweak a node. Instead you want to pin the nodes.

Hey Product Hunt community! I m Archit Jain (@architjn), and I m thrilled to share my passion for building AI-powered workflows that supercharge businesses by automating employee tasks.
Visit architjn.com to learn more!

What I Do

I craft custom AI workflows using tools like n8n, Gemini, and OpenAI to streamline repetitive tasks and empower teams. From automating social media posts to deep research for blog content, my solutions help companies save time and boost efficiency.

Examples of My Work