I might be missing some but I've been pretty much in love with @Lovable, @Cursor, @bolt.new and have been trying to use @Replit more and I honestly haven't touched @BASE44 too much but have heard good things. @chrismessina has nudged me to use @Windsurf for whenever I build another Raycast Extension! Currently I use: - @bolt.new / @Lovable - @Cursor - @Warp Curious what everyone thinks is the top one so far!
Product Hunt is great for discovery , but sometimes there are concerns about authenticity and trust when products are submitted by people not affiliated with them.
Would verifying domain ownership (e.g., via email or DNS) help ensure that only legitimate makers or teams can submit a product? Or would it add too much friction to the launch process?
Ever tried recording a quick video message or chatting with ChatGPT and suddenly your AI note-taker like Granola, or Notion pops up saying: Meeting detected!
I m building a startup and reaching the point where I need to better understand the early-stage funding landscape especially around pre-seed and first checks.
There s a lot of theory online, but I d love to hear your real stories and practical tips:
With improved generative models now being widely available, we re reaching a point where we can get full front-end code and simple functioning code for apps from a single prompt. What are the factors that determine whether development roles can be replaced by models? What s our added value as humans?
I made my first chrome extension using solely Chatgpt. I wanted to see if it was really possible for a non-technical person like me. I was really proud of myself, it inspired me to want to build more! But when I tried to add more features to it, I think the code got too bloated and messy and it just blew up so I just continue to use the extension for the basic need I have to save and organize notes I make on products that are interesting to me without all the bells and whistles I would have wanted. I wasn t trying to make money on it, just something to prove I could do it, and I got to feel what it was like to launch something on Product Hunt - yay!
But I ve also seen alot of posts/comments from more technical folks around the web hating on non technical people for believing that you can go from 0-1 and that these new tools are best to speed up work for technical people who already know how to code, not for newbies who end up with something that works by copying and pasting crappy code spit out by LLMs of their choice.
With improved generative models now being widely available, we re reaching a point where we can get full front-end code and simple functioning code for apps from a single prompt. What are the factors that determine whether development roles can be replaced by models? What s our added value as humans?
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.
Common Sense Media published a report on this topic, and it reminded me of how big a bubble I live in.
When Meta announced back in 2024/2025 that they wanted to create AI avatars to boost engagement, I was skeptic, but data speaks clearly young people enjoy AI interaction.
Hey everyone, We are doing everything we can to gain insights and get feedback on our app. The people that trial our app do not seem open to discussing their experience or providing feedback so I thought I would ask fellow founders how you overcame this and where you go to get insights and feedback on your app.
I often see the media sharing articles about layoffs due to AI, how junior programmer positions are less in demand, how there is also a decreased interest in copywriters and graphic designers, etc.
About 2 weeks ago, Teammates launched a tool (AI HR-ist), and right now I came across a post from a local marketer who shared interesting data about Ask AI (an internal AI/chatbot system), which today handles almost 94% of all routine HR requests, such as:
vacation requests
onboarding new employees
payroll information and attendance records
benefit selection and answers to basic employment questions
Results of AI implementation at IBM
94% of the HR agenda is automated
Payroll, vacation, administration even terminations have been automated
$3.5 billion saved
40% drop in HR costs
IBM also claims that employees are happier. The HR department s internal NPS score increased from -35 to +74 after the implementation of AskHR (source: HR Asia). 6% of questions are still directed at people AI has not yet completely replaced complex or emotionally sensitive situations.
Big AI news in Europe: Meta just said no thanks to the EU s voluntary AI Code of Practice.
This framework was designed to help companies align with the upcoming EU AI Act, one of the most ambitious AI regulations we've seen globally. It s not legally binding (yet), but signing could give companies a head start on compliance and reduce legal friction down the road.
Meta's stance? They say the EU is "overreaching" and creating legal uncertainty that could choke innovation.
Their Global Affairs Chief, Joel Kaplan, didn t hold back: "Europe is heading down the wrong path on AI."
