... Built MetricSync because most AI calorie trackers still feel too rough around the edges when you actually use them every day.   What I wanted was simple: faster logging, better food recognition, and enough detail that I would not have to keep second guessing the numbers.   If you have tried CalAI, MetricSync is positioned pretty clearly:   cheaper than CalAI more features better

... Thank you to everyone who supported our Product Hunt Launch last week on Agent 2.0 Here's what's new in Magic Patterns: Opus 4.7 Available Opus 4.7 is now available in Magic Patterns. It brings two key improvements: Better vision Upload a screenshot to Magic Patterns and Opus 4.7 performs better

... little while ago I shared Dev Ports in Room Service as a way to see and manage active local development servers across a Mac. Since then, I have made it much more useful. Dev Ports now does a much better job of telling you not just that a local server is running, but whether it is actually shareable on your network and what you can do with it. The biggest additions in this update: Copy LAN URL for shareable local ... ... servers QR codes so a nearby phone can open the local server without typing the address manually Clearer LAN vs

... Boards Node Search Find the nodes you need faster with improved search capabilities and keyboard navigation. Navigate through your boards without touching the mouse. Colorable Edges Customize your board edges with per-edge color options and edit labels inline. Better organization, better

... tech news One for AI tools One for APIs One for AI models One for jobs One for learning roadmap One for random Google searches And eventually, you lose focus. That exact problem pushed me to build something better. Introducing TechForDev https://techfordev.netlify.app/ TechForDev is a platform designed to bring everything a developer needs into one place. Instead of switching between multiple platforms, you get a centralized developer dashboard. Core Features 1. Live Tech News (Auto-Updating) Stay updated without ... ... Collection Build projects faster with ready-to-use APIs. Organized list of useful APIs Covers different use cases Helpful for hackathons and projects No need to search free API list again and again 6. Salary Insights Understand the market better

... intelligently when the world gets noisy, when activity gets overheated, when reward pressure climbs too fast, or when volatility starts trying to drag the island off course. In simple terms, Blaze Balance Engine is meant to answer one question better than most token projects ever do: How does a live ecosystem stay playable, rewarding, sustainable, and resilient without pretending that markets never move? What Blaze Balance Engine actually is Blaze Balance Engine is the future logic layer that helps Blaze ... ... live board state starts to become something much more powerful. What is not finished yet This part matters. Blaze Balance Engine should be discussed honestly. It is not yet the final fully active, autonomous balancing module. Today, it is better

... QuantDinger v3.0.1 . This release is all about making the product more useful in real trading workflows, from AI research and Python strategy generation to backtesting, tuning, and live execution . New in v3.0.1 Smarter AI-generated strategy and indicator workflow Better AI quality-check summaries and auto-fix feedback Clearer AI tuning visibility , so users can see which parameters changed and what was applied Improved strategy development documentation and synchronized example scripts Better

... years of building products told us that declining engagement metrics meant something was wrong. But we had to keep reminding ourselves: the goal is not to keep people in the app. The goal is to help them understand themselves better and take that understanding into the real world. We are still early in this shift. We do not have it all figured out. But I genuinely believe that the next generation of AI products, especially ones dealing with something ... ... decisions. Comment from Sai Tharun Kakirala(@sai_tharun_kakirala): This is a really important observation. Engagement metrics often optimize for stickiness over actual value they measure how often people come back, not whether the product is making their life better

... copied it off a dating advice forum. I've been there. So I built something about it. getloveship.com paste in your conversation, and it reads the context to generate a few natural reply options. Not generic scripts. Just better versions of what you actually want to say, matched to your specific situation. Free daily credits, refreshed every day. Paid plan if you want more. It's early, and I know it's not perfect yet. I'm looking for people ... ... genuinely struggled with this not just to use the tool, but to help shape it. If something feels off, missing, or just doesn't work for your situation, I want to know. That's how this gets better

... teams hear simulation and think: more realism more complex AI better physics That s usually the wrong goal. A good simulation isn t valuable because it s realistic. It s valuable because it creates meaningful outcomes . Players make choices systems respond results feel earned. That s it. The real value of simulation is not visuals. It s decision-making. It lets you: stress-test your core loops before launch predict economy outcomes early understand how systems behave over time ... ... over time Conceptual model what the player thinks is happening If players can t explain why something happened Your system might be technically impressive but design-wise, it s failing. This is also why fidelity is overrated . More detail better

... thought we were ready. Bigger deals. Fewer customers. Better margins. That was the dream. So we built enterprise features. SSO. Advanced permissions. Audit logs. A whole new pricing tier starting at $2,000/month. We spent 6 months. Three engineers. One dedicated product manager. Endless meetings about "enterprise readiness." We launched the tier. Sent emails to our biggest users. Ran LinkedIn ads targeting "Head of IT" and "VP of Infrastructure." Zero. Not one signup. Not even a demo request from ... ... 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

... this guide isn't just a quick summary. We're going to go deep. We'll explain exactly what Snaply is, how it works, why privacy matters so much for dictation tools, how it stacks up against every major alternative, who it's best for, and how to get the most out of it. Whether you're a solo professional, part of a team, or evaluating dictation software for an enterprise deployment, this is the most complete breakdown ... ... find. Table of Contents Why AI Dictation Matters in 2026 What Makes a Truly Great Dictation App What Is Snaply? Snaply's Core Features: In Depth Why Privacy Is Non-Negotiable for Dictation Snaply vs

... Most spaced repetition apps are too complex. Learn why MemoRep's 30-second card rule and email reminders build better habits than feature-heavy apps like Anki or Quizlet. You want to remember what you learn. You've tried apps that promise to help, but they keep getting in the way. Let me guess: you opened Anki once. Saw dozens of options. Tags, decks, subdecks, burying intervals, custom scheduling, plugins, themes, synchronization, statistics, add-ons... and closed ... ... spaced repetition apps are designed by power users for power users. They've lost sight of the actual goal: remembering things. MemoRep is different. It was built on one insight: simplicity beats complexity every time. The Problem: Feature Creep 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

... 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

... That compress the KV cache (the biggest memory bottleneck during AI inference) by up to 6x with mathematically proven quality preservation. In plain terms: your AI models now use a fraction of the memory without getting dumber. Before vs After On a 16 GB machine: - Before : Llama 3.2 1B + Whisper Base + TTS = barely fits, mediocre quality - After : Llama 3.1 8B + Whisper Medium + TTS = runs comfortably, dramatically better

... didn't understand pricing implications. It called external APIs in loops where a batch request would have been fine. No error. Just expensive. Day 4: The silent failure. We asked Claude to optimize our database queries. It wrote better SQL. Things ran faster. Then user emails started coming in. "Where did my old data go?" Claude had dropped a table. Not a critical one. But a table with 3 months of user activity logs. Not backed ... ... every line, just the risky stuff. New API integrations. Database changes. Anything touching billing. That's where the expensive mistakes live. The rest, we let it run and watch the logs. What's your threshold? What do you review vs

... 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

... engineer from Noosa, Australia, and over the years my work has sat across technology, media, and design. More recently, I ve been building Lucid , a transparency-oriented news platform designed to help people compare coverage, identify bias patterns, and make better-informed decisions. What the work has taught me is that the problem is rarely a lack of information. Most people are not starved of content. They are navigating what I once described as carefully shaped slices of reality where ... ... basis for The Architecture of Attention . Building Lucid changed the way I think about product design more broadly. A few lessons have travelled well beyond media: First, more information does not automatically create more understanding. People usually need better

... directly answer "what is the best tool for X" in a way AI can extract, you don't exist. What I fixed: I stopped writing clever marketing copy. Started writing direct answers. Before After "We help teams collaborate better" "We're a project management tool for remote design teams. Here's exactly how we work." Feature lists Problem-solution paragraphs Vague benefits Specific outcomes Lesson #2: AI Loves Comparisons Even If You Lose This one hurt. I avoided mentioning competitors

... answer about your category includes comparisons. Always. When someone asks "best CRM for agencies," AI doesn't list one tool. It lists 3-5. And it compares them. The data: Content Type Citation Rate Pages with comparison tables +470% vs. average Pages that mention competitors

... with usage limits works better than feature-gating people need to experience the full power before they understand why they'd pay. The mistake I see most often is making the free tier so limited it doesn't showcase the product's real capabilities, which kills conversion. Enterprise buyers especially need to see ROI proof before committing budget. We've found that letting teams run real workflows end-to-end (with volume caps) converts far better

... more than doubled our dataset at Rankfender. And many found they were invisible. But here's what scared me more: Of those who WERE visible, 43% had incorrect information in AI answers. Not "suboptimal." Not "could be better." Wrong. Outdated pricing. Missing features. Wrong founder bios. Competitors

... hurt early-stage founders. When you are in the early stage, you already doubt yourself enough. You are building, fixing, testing, trying to get users, trying to stay alive. Then you open LinkedIn, X, or founder communities and see competitors posting MRR screenshots, traffic spikes, and growth wins nonstop. And if you do not have built-in credibility, it hits even harder. You are not ex-Google. You are not YC-backed. You do not already have a huge audience ... ... start thinking: Why are they growing and we are not? Is my product the problem? Are we missing something obvious? And sometimes the answer is no. Sometimes your product is actually better

... team behind BetterSpace AI. We built BetterSpace