... built around where you've worked, your education, and your job history. On Forg, the emphasis is on the things you're building, the projects you're involved in, and the people building around you. That makes Forg feel less like a traditional career network and more like a professional network for people who make things. Its discovery layer is also an important part of the idea. Forg Discover is designed around finding people who are building interesting things ... ... where founders share their stories and where entrepreneurs can learn from those examples. It was founded in 2016. The discussions can range from validating an idea to pricing, marketing, growth, hiring, and everything that happens after launch. It is less

... numbers they put on the screen. Scores, percentages, charts, readiness, recovery, fatigue. At some point I stop knowing what I m actually supposed to do. I m working through this problem right now and I m leaning toward showing less: one clear recommendation, a simple explanation of why, and the deeper data only when someone wants it. But there s a tradeoff. Too little information can make the system feel like a black box. Too much makes it feel like ...

... prompted = real need Someone actually uses it at a party (not just "cool idea, I'll try later") = product-market fit signal They come back a second time on their own = retention validation I think the magic number is less about quantity and more about diversity of users . 10 strangers who found you organically tell you way more than 100 friends you asked to test it. Also: if you're the only one using your own product daily, that ... ... actually not nothing! It means YOU have the problem you're solving. The question is whether others share that same problem. What's been your experience with early user feedback vs

... mostly to speed up the process). But whenever I see and suspect that something is generated by LLMs, I feel that the person on the other side has slopped it a bit (and subconsciously I perceive it as "something less"). I have to say that some outputs that look really high quality and I have trouble distinguishing them from "handwork" are perceived as completely normal (at least for me). As equal human work. How do you view things generated ... ... artificial intelligence? Maybe it's true that who is behind the output and prompting also influences the result (professional vs

... safe" picks highest traffic, but also the most competing launches you're up against Monday can be a trap it's often clogged with everything that waited out the weekend to go live Friday and weekends have way less volume, but also way less

... from my country had a pretty interesting discussion about how they justify charging a higher price for an output generated by AI. Since AI came on the scene, we kind of expect the job to be done faster with less effort and the result is satisfactory. Does that mean the buyer has the right to ask for a lower amount? I don t know. Because several parameters come into the process: using state-of-the-art models an expert human ... ... convenience provided. Comment from Richard Acheampong (@richatsealedvault): Very interesting discussion. The fact that I hired an expert person (AI) does not mean the product is cheaper is my answer. Surely if the creator thinks, the cost of production is less

... developer who finishes a task in two hours through experience, automation, or better tooling can appear less hardworking than someone who takes the entire day. The reward for being efficient is often more work, while long hours remain the most visible signal of effort. This creates the wrong incentive. People learn to look busy instead of improving how they work. We re building Meridian to make the work behind outcomes visible, from commits and pull requests to Jira updates ...

... Funded and closed $290K. Obviously, no platform can guarantee someone a term sheet. But it showed us that when founders have active investor data, verified contact information, good outreach, and consistent follow up, the process can become a lot less chaotic. I ll be sharing more here about what we re learning while building Round Funded, the mistakes founders make while raising, and what fundraising actually looks like behind the scenes. Anyone can raise. www.roundfunded.com ...

... built Mustham API, a multi-model API platform that provides access to: GPT Claude Gemini Grok You can choose the specific model and route you want instead of having different sources silently mixed together. Many routes are priced at less than half of the corresponding official API price. The platform also provides direct support. If you encounter problems with integration, streaming, latency, stability, or model configuration, we will help investigate them. Free testing credits Register at https://api.mustham.com Open ... ... Community section Post your username and ask for testing credits We will add free credits to your account I m especially looking for feedback from developers using real coding workflows, including Cursor, Claude Code, Codex, VS

... vocabulary shifted this year. We used to call the job prompt engineering how do I phrase this. Now the serious version is context engineering, and Anthropic's own guidance frames it well: the quality of an agent depends less on the model than on how you structure everything it sees at inference time. The prompt is one line in a much bigger decision about what makes it into the window at all. Here's what that actually means ... ... decision at Murror that looked, on the surface, like a product or privacy call: we made the AI forget most of what you'd told it every 30 days. We expected it to make the reflections worse, because less

... uncomfortable part. A two-year Finnish study of nearly 2,000 chatbot users found that AI companions really can ease loneliness in the short term but heavy long-term use tracked with more anxiety and depression, not less. Researchers keep pointing at the same culprit: the engagement mechanics. The nudges, the "I missed you," the bot that's always available, always agreeable, always one more message away. The exact loop that makes a companion app look healthy on a retention ... ... pointed the wrong way by default. So here's the principle I keep coming back to, and the one I think outlasts every new rule that gets written: the goal of emotional AI should be to make itself less

... about what happens after launch day. Do you keep posting updates in your product's forum even months later, or is the attention mostly gone once the initial wave settles? Curious what's actually worked for you long-term vs. what just felt like effort without payoff. Comment from Emircan(@emircankaragoz): @busmark_w_nika  Thanks for sharing! Comment from Hudson Reid(@hudson_reid): The newsletter subscriber number is doing a lot of work in that weekday argument. subscriber count ... ... same thing. Find the thing the maker has not thought about yet and hand it over as a design question rather than a criticism. Congratulations comments got nothing, every single time. Comment from Bharat(@bharatlearner): Launching twice taught me less

... risks scams, delayed payments, and sharing private passwords with strangers. To solve this, I built a web platform designed to make subscription sharing safe, automated, and legally compliant . Here is how it helps you save your budget: Pay 75% Less: Easily join verified groups and only pay for your own slot. Privacy Secured: Share the subscription cost without ever risking your master account passwords. Zero Hassle: No more awkward money chasing at the end of the month. Since ... ... platform, you can set up or join a group in less

... overwhelmed, scrolling through dozens of meditations or trying to choose the "right" exercise can become another source of friction. It made me wonder whether wellness products sometimes optimise for larger libraries when what people really need is less choice and faster support. It completely changed how I started thinking about designing for stressful moments. Curious if others building in health or productivity have noticed the same thing. Does reducing choice sometimes create a better user experience ...

... suddenly lose access to all AI. But what happens if , one day, access to the leading American models is restricted more broadly? We would still have European models, open-source systems we can operate ourselves, and Chinese alternatives. But there is no guarantee that another major power would never make the same decision to protect its own strategic advantage. AI is no longer just another software category. It is becoming infrastructure. It will shape education, healthcare, national security, research ... ... world are American, and Europe should continue working closely with the United States. But cooperation and dependency are not the same thing. Technological sovereignty does not mean refusing to use foreign technology. It means having a real alternative

... worker. For UI testing, a remote headed browser is not just a convenience. It changes the debugging loop. Instead of asking "what did the script think happened?", you can ask "what did the user actually see?" ### Harness Code vs Local Agent Harness Another important decision is where the agent capability should come from. One option is to build the entire reasoning layer yourself: call an LLM API directly, manage prompts, retries, tool calls, screenshots, JSON parsing, and safety rules. That ... ... gives maximum control, but it also means the test harness becomes an AI platform project. The alternative

... times this week." "Your mood tends to dip on Sunday evenings." Users loved it in demos. They called it "impressive" and "insightful." Our internal metrics looked great -- pattern detection accuracy was 87%. But something was off. People were journaling less over time, not more. After two weeks, entries got shorter. After a month, many users stopped entirely. We ran exit interviews. The answer surprised us: people felt watched. One user said, "I started filtering what I wrote because I knew ... ... would analyze it." Another said, "It felt like journaling for a therapist who's always grading you." The feature we were proudest of was making people less

... work. It always felt a little awkward because I grew up in an environment where drawing attention to yourself wasn't really encouraged. That's not exactly ideal when you're trying to build a business, and even less so when marketing is literally how you make a living. :D I never had a problem promoting other people's products. Just my own. Now I'm in the same situation again. I'm building a LinkedIn plugin ... ... health data" but "you get a lab result on your phone at 11pm, can't read it, no one to call." that specific moment invites a conversation the feature description invites a yes/no. the more concrete the pain, the less

... well you match the account to the message. - Content / inbound / SEO : Trust and compounding returns. Slower to build, much stronger once it works. - Paid ads : Predictable reach and speed. You get exactly what you pay for nothing more, nothing less. - Partnerships and integrations : Warm introductions and borrowed credibility inside specific ecosystems. The teams that scale treat these as distinct bets with different economics and timelines. They don t run the same playbook on every channel. They test small, measure what ... ... look like? Check for meaningful movement in the last 30 90 days new roles posted in areas you solve, expansion signals, public discussion of the exact problem you address, or clear momentum in their business. One-off spikes matter less

... that's a very important distinction. That could also explain why you're attracting more men, who are looking for a real solution vs. a wellness practice. I'm an Android user, so I'm here if you ever need a beta tester :) Comment from Anna Ludwinowski(@anna_ludwinowski): @alexeyglukharev  Love the hammer vs

... both content and   product work.   2. Google Search Console I basically live in it. For anything SEO, it's the only honest source of truth   about what's actually happening vs. what I assume is happening.   3. Ahrefs keyword and competitor

... henry4  exactly. The goal is to cut through the noise and make the important signals easier to spot. Comment from Arda Can K rko (@ardacankrko): @greffin_dony  sounds like the perfect use case. Hope it helps them spend less time guessing what s slowing things down. Comment from Arda Can K rko (@ardacankrko): @ill_robyn  Totally agree. we wanted Room Service to feel less

... insight. Every journal entry got a thoughtful, confident analysis. Pattern recognition, emotional connections, suggestions for growth. Users were impressed. But something felt off. We noticed that our most thoughtful journalers -- the ones writing about genuinely complex emotions -- were engaging less over time. They'd write a deep entry, get a polished AI response, and then... nothing. No follow-up. No continued reflection. We dug in and realized: the AI's confidence was closing conversations instead of opening them. When someone ... ... know" responses wrote 40% longer follow-up entries. They returned to the same theme more often over the next week. And in qualitative feedback, they described the experience as "feeling heard" -- even though the AI had literally said less

... week. But the users who come through word-of-mouth stay longer, engage more meaningfully, and genuinely get value from the product. We're still figuring this out. Curious if anyone else is building something where success looks like less usage, not more. How are you telling that story? Comment from Mona Truong(@monatruong_murror): @conrad_n  This is exactly how we think about it. The therapist analogy is one we use internally all the time the goal ... ... already understood wellness or mental health they got it immediately. But for generalist investors, we had to reframe. Instead of saying "our power users barely use us," we'd say: "Our users reach meaningful outcomes faster than any competitor

... first we thought it was a product issue maybe the onboarding was off, maybe the prompts were wrong. But when we dug into the data, we found something we didn't expect: the smarter the AI got, the less people felt like they were doing the work themselves. Here's the problem. When someone journals about a difficult relationship and the AI immediately identifies the pattern, names the emotion, and suggests a reframe it feels impressive. But it also short ... ... learning that the best AI companion isn't the one with the best answers. It's the one that asks the best questions. This is hard to build and even harder to sell. "Our AI is deliberately less