... makers! I'm Hamid, and I built Fleck AI because I realized something: the best products aren't built by AI or designers alone. They're built when humans think, and AI amplifies. Here's what I learned designing for 12+ years: The real leverage isn't in the pixels. It's in the thinking, validating ideas, mapping flows, understanding trade-offs, knowing what matters. That thinking? Only humans can do it well. The problem is all the friction around ... ... your idea in natural language. Fleck AI scores it (0 100) for market viability, differentiation, feasibility, and monetization. Instant clarity on risks, opportunities, and MVP scope. You decide what matters. Map while you think : Auto-generates user flows, personas, competitor

... Quick story that pushed me to build PriceForge : Three weeks ago, I was in final stage of a $50K deal. Sales call went great. Then the pricing objection hit: Prospect: "Your competitor just dropped their Pro tier to $79/mo with unlimited workspaces." Me: frantically opening competitor

... Ever looked out at a room full of people and thought... "Is anyone even listening?" We built Amphioo because we were tired of one-way events. No engagement. No feedback. Just slides and silence. Amphioo

... 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 ... ... customer you didn't have? How much did it cost you? What did you learn? Imed Radhouani Founder & CTO Rankfender Evidence over ego. Retention over requests. Comment from Liviu Chita(@liviu_chita): the API rate limits vs

... Last month, I did something that felt slightly insane. I took our product description, fed it into ChatGPT, and asked it to build a competitor. Not a parody. A real competitor

... building ai personal branding engine. The main goal is to help people to build personal branding Comment from Amplifyzone(@amplifyos

... just exposure, but the degree to which AI treats your brand as a credible source . Share of Voice (SOV): Represents your brand s voice share within AI narratives the probability that AI mentions your brand rather than a competitor when answering a topic-related question. Sentiment: Captures the emotional tone of AI mentions positive, neutral, or negative showing how AI portrays your brand. Together, these four metrics answer the two most fundamental GEO questions: How frequently does AI mention ... ... brand? and In what tone and context is the brand represented? 1.2 Trends and Competitor

... found errors. Average cost: 28k." 120k impressions, 400+ new signups. Free resource: Post as a human. Share what you're learning in real time. People don't follow companies. They follow people. 5. Multi-Language: The Hidden Channel Most competitors track AI in English only. We built for 120+ languages from day one. Why: A German user asks in German. AI answers in German. If you're not in German content, you don't exist. One example: A US SaaS ... ... with perfect German translation had zero German AI mentions. A local competitor

... Rankfender , we've identified clear patterns. Certain content types get cited 3x more often than others. Here are the 7 content types that win AI citations with real examples you can steal. First, the data: Content Type Citation Rate (vs. average) Best For Comparison pages 3.2x higher "X vs

... Minute Audit Step 1: Keyword Selection (5 minutes) Choose 20 keywords to audit: 10 branded keywords: Your company name Your product names Your founder/CEO name Your flagship features 10 non-branded keywords: "[Your category] best tools" "[Your category] alternatives" "How to [solve problem you solve]" "[Your category] vs

... Continue your thinking Ask for a second perspective of your thoughts Structure decisions Paste text and refine it It s slowly becoming less of a note tool and more of a thinking companion. We re calling it a cognitive amplifier. Not productivity but CLARITY. Im Curious: Do you think better by typing or by speaking ...

... thinking companion. We re building toward something bigger: Not note taking, not productivity, but something that gives you CLARITY. Grateful for this community. A lot of this came directly from your feedback. Curious what a true cognitive amplifier should feel like ...

... hitting 80%+ of my limit almost every day. Worth every penny. - Cursor: Using about 60% of fast requests. Solid value. - ChatGPT: Maybe 20% usage. I was using it mostly as a Claude backup when rate-limited. - Copilot: Under 10%. VS Code autocomplete was nice but I wasn't really dependent on it. Without usage data, all subscriptions feel equally necessary. With data, the picture is obvious. I cancelled Gemini ($20/mo saved) and I'm evaluating whether Copilot is worth keeping ... ... That's potentially $30/mo saved $360/year. TokenBar paid for itself in the first week. What it shows: - Usage vs

... competing, they were filling a verified gap. Phase 2: Viewer Psychology Mapping Critical Success Factors: Use Channel Insights to decode your specific audience's emotional triggers and content preferences Map viewer journey patterns showing what keeps people watching versus bouncing Identify psychographic patterns unique to your community, not generic demographics The Channel Insights component addresses what researchers call the "relevance gap", the difference between what creators think resonates and what actually drives engagement. Creators who understand viewer psychology ... ... View Duration : Target 50%+ completion (YouTube's recommendation threshold is 40-50%) Click-Through Rate : Achieve 6-8% CTR within first 48 hours (our A/B testing drives 40% improvements) Audience Retention : Maintain above 60% at the 30-second mark versus

... Product Hunt! I m Yana Welinder, you might remember me from Kraftful. Today, we re launching as part of Amplitude with Amplitude

... Netflix uses for recommendations). Here's the flow: USER FEEDBACK LOOP Write AI Suggests Accept/Deny/Retry System Learns Model Stats DB Model A: 85% Success rates Model B: 72% Model C: 91% Use this one! Thompson Sampling Algorithm Balances exploration vs exploitation Try new models Use proven models (10% of time) (90% of time) What's Thompson Sampling? Think of it like this: The Casino Analogy: You walk into a casino with 5 slot machines. Some pay out more than others ... ... emails Mistral is fastest for quick edits Week 3: Sarah just writes SourcePilot automatically uses GPT-4 for blog posts Switches to Claude when she's writing emails Uses Mistral for quick grammar checks Sarah's accept rate: 91% (vs

... noticed two main narratives in how companies view their competitors. Either it s a fight to the death approach exactly like what we see between Replit and Lovable (though it seems Replit does more of the provoking ) basically: We speak badly about our competition. Or it s more motivational: We speak positively about our competition. Tho I do not know whether I have seen some example of this competition, I can see it only in terms of personal branding when ... ... people do not want to say bad things about someone, even when they are competitors

... Product Hunt I m building LitmusB.com , a tool that helps product teams stay ahead by: Benchmarking your product s UX against competitors Tracking what your competitors

... curious about how their recommendations are actually pulled from the web. I'm not an expert, listen to the podcast, but I am actively tackling it so have some tactical learnings. I mainly came across AEO by looking at competitors and researching. I was always surprised that I d search and end up on the home page of a product, not another more credible source - just because they d written a smart blog post about it. See this for "best ... ... Wikipedia is powerful, but tricky . You need notable online coverage to get approval by Wiki moderators to have a page about your company/product, which again comes back to press. We're close to our page going live, fingers crossed. Competitors

... brand mentions across these models in real time, analyses sentiment and provides prompts showing how and where the brand is being referenced. It also sends real time alerts when a brand is cited by an AI model and offers competitor monitoring to identify positioning gaps. Thirdeye as one of the most-advanced AI analytics and recommendation platform that helps brands get discovered not just on Google but inside ChatGPT, Claude, Gemini and Perplexity, emphasising that if you aren t cited ... ... platforms such as ChatGPT, Claude and Gemini are becoming the new homepage for information, so brands must optimise for visibility across these models. This shift is supported by wider industry data: according to Nowspeed s guide on AEO vs

... standards TikTok just doesn't play well with that world. The Problem (Before State) "I need to add TikTok auth to my app, but I don't know where to start." "I m digging through vague documentation from AWS, Amplify, and TikTok, trying to piece together a working solution." "I m stuck connecting TikTok OAuth to Cognito correctly." " I'm worried about getting the Cognito User Pool and Identity Pool settings wrong, leading to security vulnerabilities or a broken user ...

... replies, retweets and DMs to harvest the language your audience actually uses. 2. Rapid-fire experiments We never waited for launch day. Instead, we treated our entire buildup as a real-time lab: Email CTA swaps ( Try Chronicle Pro vs. See Cursor in action ) Slack micro-polls in our beta channel ( Which benefit would you tweet? ) Tweet thread formats (numbered list vs

... essential in 2025 The consensus was pretty clear: besides AI everything , the modern GTM tech stack for mobile apps boils down to five key components: Your app Backend for data storage (DB or DWH) Product analytics (Firebase, PostHog, Amplitude, Mixpanel) Mobile Measurement Platform (MMP) e.g. AppsFlyer or Adjust Emailing tool/ Customer Engagement Platform (CEP) Mailchimp, Launchlist, Airship, Braze, MoEngage, etc., depending on where you're at in relation to launch. This stack gives you full-funnel visibility, cross-channel orchestration ... ... pretty far. Most, but not all free but you can make a free version of the below if you need to be scrappy: AppsFlyer (MMP) for attribution Brevo/ Mailchimp/ ConstantContact/ or Airship / Braze / MoEngage for communication/journey automation PostHog or Amplitude

... Curious how other teams are handling backend setup these days. At Raftlabs, we recently kicked off a client project and decided to try AWS Amplify instead of setting up our usual stack. To our surprise, it saved us a ton of time. In just a few days, we had: Auth (Cognito) File storage (S3) GraphQL + REST APIs (AppSync + Lambda) CI/CD auto-deploying the frontend Proper environment separation (dev, staging, prod) No custom infra scripts, no hours lost in IAM policies ... ... Just shipped real features. It made us wonder: How are you handling the backend setup right now? Do you build from scratch or lean on tools like Amplify

... Command AI was acquired by Amplitude in October 2024. We just re-launched one of our products as an Amplitude