General
p/general
Share and discuss tech, products, business, startups, or product recommendations
How (not) to gather first users when you are an unknown brand. May be helpful to new product makers
From testing new products, I've come to several conclusions and possibly also identified mistakes that product creators make when launching them.Whenever you want to attract your first testers (especially those who are well-known), try first to build up your credibility.During product testing, I encountered the following mistakes that left an inconvenient impression:🥲 No publicly available contact (about the company, owner)🥲 Testimonials using "fake" stock photos (this is especially noticeable to people who work in marketing and tech)🥲 Untraceable product creator – do not know his name, face,...🥲 Not offering a free trial version and immediately asking for paymentIf you do all of these things at once, it leaves a very bad impression.Recently, I wanted to try a tool, and accepted the terms of use, but couldn’t cancel the trial after submitting my card – the system technically didn’t allow me to cancel. At the same time, the product didn’t even work. There was no person I could contact. Suspicious.I’m surprised how many people launch products this way, even on Product Hunt, because, with these steps, such a product feels more like a scam than a serious business.If the business is not supposed to be a scam 😉, please:☝️ Build trust, ideally also a personal brand, if you’re serious about it.☝️ If you don’t have testimonials from people yet, use a video where you demonstrate the product; ideally show your face too – human aspect.☝️ It’s better to let people test the product for free because it might not be technically finished yet, viz. my experience. (People, who don't pay, are not so loud on the internet as people who already paid, IYKWIM.)Do you have a similar experience?Next time, we could cover how to prevent fraud, btw. 😀 (I have a lot to share.) 😀
37
OpenAI
p/openai-api
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OpenAI launches new tools for building agents
On their livestream today, OpenAI just released a bunch of new tools for reliably building and using AI agents. From what I can tell, this is what's new-New APIs:Responses API - a new multi-modal API that builds on chat completions to allow for the next-generation of tool calling, starting with the new tools announced today.New tools:Web search tool - Gives the API access to leverage web search and cite sourcesComputer use tool - Gives the API access to use a remote machine, this is hugeFile search tool - Upload a batch of files to a vector store and then query them via an endpointWeb search toolI read this as we can now give API calls the ability to search the web and the return object can contain citations. This is interesting to me because it's the first time (to my knowledge) that OpenAI has surfaced it's citations via API. Amongst many other things, this would enable AISEO optimization companies and anyone gathering "AI SEO-esque ranking" data to build datasets and reverse engineer how to become cited by AI. This also seems like a bad day for @exa.ai though they are still much further along than Open AI. I have to imagine AI rank tracking tools must be coming soon in products like @Ahrefs and @semrush. Web search tool pricing: $30 and $25 per 1K queries for GPT‑4o search and 4o-mini search.Computer use toolThis enables developers to use the API to to control remote environments. This is massive to be able to do this programmatically and unlocks a ton of new use cases for automation. Computer use tool pricing: $3 per 1M input tokens and $12/1M output tokens.File search toolThe new file search tool allows you to create vector stores and upload files to them and then give the model access to these knowledge bases. Prior to this tool, you'd need to have set up a vector store and uploaded files to it. This cuts out that step. In other words, this is RAG in the easiest possible way to get there. Projects are limited to a total size of 100GB for all files but each file can be up to 512MB.File search tool pricing: $2.50 per 1K queries and file storage at $0.10/GB/day. First GB is free.What did I miss? What do you think? What can we build now with these tools that we couldn't yesterday? How does this impact other startups?
8
Fine
p/fine
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"Vibe coding" for non-coders
Recently I've worked with a group of non-corders trying to "vibe code" their apps with AI. While knowing code is clearly not a must these days, it helps to get technical.People who were familiar with basic software engineering concepts were 10x more likely to success and get better results.So, with the hope of providing value to the non-coders people, I've created a quick roadmap for the basic terms and concepts you should be familiar with. Requirements: Building apps with AI is all about being able to clearly guide AI and express your app features and requirements. You need to be able to express those ideas and explain them as you’d explain to a human developer. Think like a Technical Product Manager. Frontend: The face of your app. It's what your users see and interact with. It could be a website, a mobile app, or a desktop app. Most popular frontend libraries and frameworks are React, Next.js.UIs: They are the buttons, the forms, the modals, the tooltips, etc. In React, the UI is built with components. For design & styling, Tailwind CSS is the most popular library. For animations, Framer Motion is the most popular library.Packages & npm: Apps are not built from scratch.They are built on top of existing libraries and frameworks, like lego blocks. The most popular package manager is npm. For example, "react-hook-form" is a famous package that helps you build forms.Backend: The backend is the part of your app that runs on the server. It's where you store your data, your business logic. e.g: If you want to send an email, or process payments - this is where you'll do it.Vibe tip: Use minimal backends with serverless functions.Database: The database is where you store your data. It's where you store your users, your projects, your tasks, etc. Think of it as a big spreadsheet.I recommend using a database that is integrated with your frontend. For example: Fine, or Supabase.API: Real-life apps almost always need to integrate with other apps. For example: if you want to send email, or get weather data, or integrate with AI - it's all done through APIs.Hosting & Deployment: For your app to be accessible to the public, you need to host it. The code is usually hosted on GitHub, and deployed to platforms like Fine, Vercel, Netlify.Finally, being comfortable with code is helpful - even if not a must. AI often makes minor mistakes (like importing a wrong package), and if you’re not afraid of reviewing code - you will get better results faster.
14
Product Hunt
p/producthunt
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Product of the Week Winners: March 3-9 Spotlight
Hello Product Hunt friends!Juan checking in from the community team. Hope your week is off to a great start!Time to shine a light on our Product of the Week winners that made waves last week.These innovative teams deserve some recognition for what they've built:MGX by @MGX (MetaGPT X)MGX (MetaGPT X) is a multi-agent AI platform based on software SOPs. Chat with AI agents including a team leader, product manager, architect, engineer, and data analyst to create websites, blogs, shops, analytics, games, and more.Teamble AI by @TeambleTeamble AI helps improve employee feedback throughout the year. Better feedback leads to better learning and performance, all integrated with Slack and Microsoft Teams.Supergrid by @DepictDesign custom Shopify storefront collection grids with editorial images/videos and AI sorting to improve shopper conversion. Features 1-click installation, no-code required, and minimal impact on site speed. Reframeanything by@OpusClipAn AI reframe tool that resizes videos for different social platforms. It tracks actions and applies suitable layouts to your video, making it easier to create social-ready content quickly. Finyx by @FyniXFynix is an AI-powered coding assistant that adapts to your style by learning your preferences. It helps streamline workflows with natural language commands and customizable AI within your IDE.Congratulations to all these teams on their impressive work!I'm curious - which of these tools would solve a specific challenge you're currently facing? And if you've already tried any of them, what was your experience like?Drop your thoughts below!Juan from PH
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