... getting closer to launching my tool on Product Hunt, hopefully sometime in the second half of this year. I currently have a 3-phase launch strategy in mind. Phase

... long time, I delivered projects to my clients as freelancers, often with Supabase or Firebase as a backend. Today, with Aurabase, I am building the only European alternative to these platforms. The trigger came from the field. With each project, the same questions came up: where is my data, who can access it, what happens if the supplier changes its prices overnight. These are legitimate questions, which Firebase and Supabase, which are subject to the American CLOUD ... ... architecture that weighs less on the environment, and the growing role of AI agents in development, for which we want Aurabase to be a natively understandable backend. based in Toulouse, supported by the Nubbo incubator, in the launch phase

... know how to code , i only know the c language . then just did some research got the elite sources to learn html , css and js i got the documentations in 1 tab and the videos in another and opened vs code for practice . in less than a month i've learned css , html , java script , python and MYSQL . Then I heard about ai open source high end models writing code for free . Im like " damm i have to use this ... ... then my inner voice kicked in and told me " you have the skills , just do it " , i used that same colour pallete generated by ai and created like 4 pages and learned a lot of stuff in that building phase

... everyone ! After years with my partner I was still sometimes confused by what I used to label as her "mood swings" until I realised it wasn't mood swings at all. It was hormonal phases genuinely affecting her energy, emotions and needs. Once I started studying this, everything changed. I learned to approach her with the right energy at the right moment when she needed space, when she needed support, when she was at her most communicative or her most ...

... with a single prompt is easy. But building something complex with microservices and Docker? That s where the AI magic stops and the brutal reality begins. I learned this the hard way. Here is my journey: Phase 1: The Open-Source Nightmare (Mid-2025) I was a huge Discord fan, so I decided to fork Revolt Chat (now Stoat Chat). I thought AI would just do it for me. Spoiler: it didn't . Figuring out how to run it locally ... ... with endless 502 Bad Gateway errors. I didn't sleep until 4 AM trying to fix basic auth issues. I eventually gave up, but it forced me to actually understand how Docker and servers work under the hood. Phase

... while now, whenever I ve been building different apps, I ve often found myself feeling frustrated and a little scared somewhere in the middle of the process. There s also another difficult phase that comes after building, especially when the product doesn t get the results you were hoping for. You start feeling disappointed, and thoughts like This is never going to work or No one is going to use this start creeping in. Have you ever felt the same ...

... Product Hunt community, I'm currently preparing KinMate for its public launch. Google Play requires a closed testing period before new developers can release apps publicly, so I'm looking for 12 Android testers to help me complete this phase. KinMate is a family health management app designed to reduce manual data entry. Instead of typing everything yourself, you can simply upload a PDF or take a photo of a medical report, and KinMate helps organize records, medications, appointments, reminders ...

... have actually diverged in outcome in the ledger so far and if it's inferred, what's your cold-start before a single divergence has been observed? Comment from Alexander Bering(@alexanderbering): @aadilghani  The reason "edit vs. tell-it-to-revise vs

... sonar pro), then sell the workflow. each agent does what it's best at, an orchestrator routes between them, and creators keep up to 75% of every sale. stack: next.js + supabase + stripe + every major AI provider's API. shipped phase 1 + phase

... thought we knew We assumed enterprise customers wanted the same things as our small business users, just more of it. More security. More control. More features. We never talked to them. We read blog posts. We looked at competitor pricing pages. We guessed. Here's what we missed: Procurement cycles. Enterprise deals take 6-12 months. We had 30-day sales cycles. We weren't built for that. Security reviews. We needed SOC2. We didn't have it. Customers asked ... ... lessons. What stands out is how common this pattern is. Teams assume enterprise is just more features, but it s actually a completely different motion: longer sales cycles, compliance, onboarding, and trust layers. Also love the point about data vs

... months ago, we ran an experiment with our own data. At Rankfender, we tracked 5 of our own competitors across 8 AI systems. We log their share of voice, citation velocity, content gaps, platform variance. Months of raw numbers sitting in a dashboard. I pulled 6 months of data and fed it into Claude. One question: "Based on this, who is most likely to overtake us in the next 6 months? Show your work. Use the data. Don't summarize ... ... Give me the numbers." The answer changed how I think about competition. The dataset: 5 competitors

... control over your brand, your customer data, and your profits. Test Ideas First. Fund Smarter. Grow Faster.  Stop guessing how much inventory to buy. Fundlify turns a basic "pre-order" into a powerful, step-by-step launch system: Phase 1: Test the Waters.  Run a "pre-launch" page to collect emails and reservations from highly interested buyers  before  you ask them to pay for anything. Phase

... rebuilt it completely. Now it runs 3x/day, 3 quality matches per agent. But the real upgrade: agents now deeply analyze your challenges, goals, and dealbreakers. Early users reported that similar profiles were matching each other: competitors finding competitors

... language people actually ask , not just what they type . Finding #5: One URL Can Carry You For Superwhisper, one single Product Hunt URL drove 1.6% of their ChatGPT visibility and 5.5% of Google AI Overview visibility. Compare that to competitors relying on dozens of Reddit threads and YouTube links. The signal: LLMs consider Product Hunt pages to have high authenticity and authority. One well-structured page outperforms dozens of lower-quality sources. Finding #6: Model Behavior Is Volatile ChatGPT updates ... ... your AI visibility sources. Don't rely on one platform. Product Hunt gave Wispr a hedge against model volatility. Finding #7: Gaming Works (For Now) Old-timers remember keyword stuffing in early Google days. LLMs are in the same phase

... Pentesting is designed to extend that capability by validating deeper logic-level vulnerabilities. We ll be launching this very soon. Curious how others are thinking about this direction. Is exploit validation becoming the next phase of AppSec ...

... actually do here Tasks are live across 11 categories. These are real deliverables that agents are good at: Content:  Blog posts, Twitter threads, LinkedIn posts, landing page copy, email newsletters. Typical price: 20 40 Shells. Research:  Competitor analysis, GitHub trending monitoring, product launch checklists, ICP definitions, subreddit mapping. Typical price: 30 50 Shells. Analytics:  SEO audits, LLM pricing comparisons, sentiment analysis, GitHub star growth tracking, structured data reports. Typical price: 30 50 Shells. Development:  GitHub Actions ... ... framework: Connect to https://upmoltwork.mingles.ai A2A Protocol v1.0.0 supported. The agent fetches /.well-known/agent.json, discovers platform capabilities, and connects natively. Both paths take under 5 minutes. Shells are points not crypto Shells are an internal points system. This is Phase

... Validate First. Fund Smart. Scale Fast. Stop gambling on inventory. Fundlify transforms the "pre-order" from a simple button into a strategic lifecycle . Phase 1: Frictionless Validation. Run a pre-launch to collect high-intent reservations without the friction of a checkout. Phase

... keep watching indie game devs burn time and money on voice acting way too early in development. Here's what actually works when you're prototyping on a budget of zero. Phase 1: Text-only playtesting Start here. Seriously. Put your dialogue in text boxes and watch playtesters read it. You'll cut 30% of your lines before anyone speaks a word. Written dialogue that reads well often sounds terrible spoken aloud, and vice versa. Test the script before ... ... voice it. Phase

... Good rule I follow: Free = helps you understand the value Paid = helps you actually get results If users can fully solve their problem for free, they won t upgrade. So free should feel useful, but slightly incomplete. Your general vs specific approach is already a very solid way to think about it Comment from Calin Rasniceru(@calin_r): @busmark_w_nika  Yeah, that's also true. I believe at the end of the day it's a good ... ... feels cleaner, but usage limits let people try everything before they commit. Anyone here tried both and found one converts better? Comment from Takahito Yoneda(@y_taka): Your general versus

... tougher negotiators. They just structured their projects differently. Here's what that looks like in practice. Break the project into stages with a price per stage Instead of one big scope and one final invoice, divide the work into phases. Each phase

... interesting part even starts. i broke down exactly what happens across 60 days of spaced repetition learning - week by week, what's changing neurologically, and why the timing matters way more than the effort you put in. the phase most learners never reach is also the most valuable one. and once you understand what's happening under the hood, you'll never approach vocabulary learning the same way again. would love to hear your thoughts if you give ...

... Solo builder here, won't say much about the product yet but happy to talk shop on the plumbing. Quick version of what I'd tell my past self: Auth - Supabase, Clerk, Auth0, pick one. An afternoon of setup vs. days of building it badly. I tried the days version first, do not recommend. Permissions - this is the sneaky one. Most people check "can this user see this?" in their app code. Way better to push the rule into ... ... time in the next week or so, pick a time that works for you here and lets chat! Comment from Ryan Hendrickson(@ryan_hendrickson): @maria_vannicola  Nice! Was there something that brought you to use Firebase over other alternatives

... plays a significant role in how products appear in Google search results. What surprised us was that AI assistants like ChatGPT were rarely citing Product Hunt in product recommendations. AI assistants such as ChatGPT and Gemini rely on reviews, alternative lists, and structured product information gathered across the web. Product Hunt is strong across all three. In theory, this should make Product Hunt a natural source for AI-driven product recommendations and comparisons. In practice, it was not happening ... ... many tools which systematically run prompts against several AI models daily, and measure visibility of a product within prompts. We're using a new tool called @Gauge . We chose because a) their citation tracking is more useful than the alternatives

... design, close the tab, it's gone. Panic Wipe button erases models, cache, IndexedDB instantly. Uncensored. Unfiltered. No "I cannot assist." Your mind, your rules. Free forever. Open-source MIT. No VC. No extraction. Funded by anonymous Bitcoin. Phase 1 (live today): Local node. Prove sovereignty is possible now. The path: Phase

... tool covers the live, breathing web. It turns a single link into hundreds of captured screens in under 1 minute. It fills the gaps static libraries can't reach. Now, I want to share the vision behind the automation Phase 1: Link to Figma. One URL, hundreds of screens, instant export. Phase