Let me start from the creator s perspective: I personally don t have a product (apart from hiring people for creative work or offering personal consultations).
But as a creator, I constantly share content, insights, and information, value that helps me build trust (for free). Based on that perceived expertise, people eventually decide to work with me (a paid service).
tldr: yes. Shoutouts are one of the simplest distribution levers on Product Hunt.
Shoutouts are meant to pay it forward and highlight the tools that helped you build. But beyond goodwill, they create durable distribution for your product on Product Hunt and across LLM driven discovery.
When you shout out a product during launch, it becomes a founder review on that product s page. Founder reviews sit above regular reviews and include a link to both your profile and your product. That means your product is now attached to every future visit to that product s review page, long after launch day. For example, check out @timliao s shoutout of @Framer or @guymanzur s shoutout of @Base44
I recently saw a marketer with 10k+ followers launch and finish 6th with 348 upvotes. They followed a proper pre-launch and post-launch plan, did everything right, and still the outcome felt unpredictable.
Now I m launching @Curatora next week.
I m not a marketer. I have a little over 1k followers. Of course, asking for support helps. But I also keep hearing that a large part of the Product Hunt community shows up mainly for their own launch, then goes quiet until the next one.
That makes me wonder: how much of success here is strategy, and how much is timing and network effect?
I just fixed and rebuilt an entire AI automation flow without opening the flow editor once. Here's what happened: We have a YouTube script generation pipeline on Serenities. It takes a keyword (or YouTube URLs), generates an outline, then writes each section with precise word counts. Two branches one for URLs, one for direct topics. The URL branch was broken. Not obviously broken. Subtly broken it was jumping straight from transcript cleansing to a single Claude call with no outline step, no section iteration, no word count targeting. Just a raw prompt that guessed at length every time. I asked Claude to check it via MCP. Within seconds it had read the entire flow every node, every edge, every config. It found: - A broken template variable resolving to [undefined] instead of the word count - Extended thinking enabled on a cleansing node (pointless, just burning tokens) - The URL branch missing 7 nodes that the keyword branch had - The MCP help guide serving 5 thin topics with almost no real documentation Then still without me touching the UI it: Added 7 new nodes to the URL branch (outline prompt, Claude outline generate, JSON cleaner, iterator, section prompt, section writer, text aggregator) Rewired all the edges correctly Updated the webhook response to pull from the new pipeline Rewrote all 5 MCP help topics with complete documentation utility node configs, template variable syntax, Claude toolInputJson templates, debugging guides, everything One conversation. Zero UI clicks. The flow went from broken to production-ready. This is what MCP actually unlocks. Not just "ask AI to explain your code." Ask AI to read your live infrastructure, reason about what's wrong, and fix it programmatically, precisely, at the API level. We built MCP support into Serenities so AI agents can build and manage flows on behalf of users. Today I used it on our own platform. It worked exactly as intended. The future of automation isn't drag-and-drop. It's conversational.
There s a lot of discussion on X and other places about the future of software development. As with many things in life, the reality is both complex and in the middle of the extreme viewpoints. What we re seeing at Tonkotsu:
Agents are fast and powerful, but make mistakes. They can t operate unsupervised. We think they re like unreliable compilers.
That means developers are as critical as ever, but their role shifts to being managers of coding agents.
This transformation means developers need to be focused on planning and verification, while delegating coding. The role has become barbell-shaped, and the industry needs new tools and workflows to accommodate this.
New AI models pop up every week. Some developer tools like @Cursor, @Zed, and @Kilo Code let you choose between different models, while more opinionated products like @Amp and @Tonkotsu default to 1 model.
Curious what the community recommends for coding tasks? Any preferences?
This community helped turn a scrappy weekend project into something used by 25,000+ people from all around the world. So it felt right to share this here first:
On Jan 31, we are launching Pretty Prompt 1.0 right here on Product Hunt.
I heard the requests and i also knew that the app wasnt perfect ,so while i work on that , You can use drift browser edition which is now on the website And Ofc Be it Mac , Windows or Linux ! CHANGES - Does it work the same ? - At the very Least You have a Free Simple Raw Screen Recorder (You can add Zooms) - You can CUSTOMIZE YOUR ZOOMS By Adding Manual Zooms with Speed / And Intensity Thank you for such reception , I just launched it without thinking anything or if i would get any visitors , did not expect #5 , 1000 page visits and 200 followers . Additionally Drift is an FREE AND OPEN SOURCE Project , I will be releasing the github contribution / proper documentation soon ! Happy Recording
