... QELLVIS is a system intelligence framework that models internal behavior inside complex environments. It does not predict outcomes it exposes the structural mechanics that produce them. Today we re releasing the full documentation: System3 engine Public API Connect importer Deterministic propagation logic Structural behavior

... simplified device behavior into two primitives: Button Switch That s it. Then we define what they do in JSON. Not as configuration, but as actual execution logic. Instead of: rewriting firmware rebuilding reflashing We just change JSON. We built this on top of the Matter standard. So it s not a simulation. It runs on real devices. Here s what that looks like: { "trigger": "button", "action": "start", "limit": "5min" } Same hardware. Different behavior

... lays out a phased strategy: start broad with baseline metrics, deep-dive into each analysis area, then look for cross-area correlations. It even includes example SQL queries tailored to e-commerce conversion funnels, revenue by category, repeat customer behavior so the agent hits the ground running. Recommendations takes what the agent discovered and turns it into specific, actionable steps with target segments, expected impact, and implementation details. Each prompt is edited with a markdown editor that supports preview mode ... ... also write category-specific prompts . Select "Multi-Category Store" from the dropdown and you'll see an exploration context that tells the agent to focus on cross-category shopping behavior

... Blaze Balance Engine: What It Is, What It Can Do, What s Nearly Ready, and Why It Matters Blaze Balance Engine is the part of the GrowHouse vision that turns raw chaos into controlled ecosystem behavior. It is not a promise machine. It is not a price-defense gimmick. It is not a hidden switchboard for fake stability. It is a bounded ecosystem balancing layer designed to help GrowHouse react intelligently when the world gets noisy, when activity gets overheated ... ... future logic layer that helps Blaze read the state of the ecosystem and recommend or apply safe, pre-approved balancing moves inside hard limits. That means it is about: pacing pressure resilience sustainability controlled response explainable system behavior

... Product Hunters, Most e-commerce spy tools on the market stop at the surface. They show you which ads a competitor is running or estimate their monthly traffic. They tell you what your competitors

... months, our most requested feature at Murror was a chat function. Users wanted to talk to the AI the way they talk to a friend. It seemed obvious. Every competitor had it. Every feedback form mentioned it. So we built it. And within two weeks, our core metrics started dropping. Session length went down. Return rate went down. The thing users said they wanted was actively making the product worse. Here is what we discovered when we dug into ... ... desires in the vocabulary of features they already know. "Chat" means "I want something more natural." "Feed" meant "I want less friction." The actual need was different from the literal request. Now before we build anything, we ask: what behavior

... bots and fake accounts Improve trust in conversations Clean up spam-heavy communities On the other hand, Reddit has always been built on anonymity , and changes like this could shift how people use the platform entirely. There are also alternative ideas being floated: Zero-knowledge proof verification Device-based authentication Temporary human verification tokens Two questions for the PH community here: If you use Reddit, what would you want: fewer bots or actual anonymity? Should Product Hunt apply the same ... ... trade-off is way off you sacrifice the one thing that makes Reddit uniquely valuable (anonymous, genuine opinion) to solve a problem that will just mutate into a harder one. The real question AI detection poses is about behavior

... marketing problem. They think: "Let the SEO team handle it." Here's why that's wrong: Your product is being evaluated by AI every single day. When potential users ask: "What's the best tool for [your category]?" "Alternatives to [competitor

... What is driving it? What should I do next? That is a big part of how we think about Pinnacle. The goal is not to flood you with biometrics. The goal is to turn signals from your body and behavior into something actionable in the moment. 2. Low-friction measurement really matters A lot of people responded to the fact that Pinnacle works from the iPhone you already have, without requiring extra hardware to get started. That convenience matters more ... ... tried using general AI as a coach, and the common experience is that it still puts too much burden on the user to know what to ask. What we are building is different: Pinnacle combines conversation with biometric and behavioral

... problem we kept running into Every founder and growth person I talked to was doing some version of the same thing: Manually scrolling Reddit and Slack to find relevant conversations Running half-broken n8n workflows with keyword alerts Checking competitor mentions once a week (if that) Looking at their LinkedIn feed and seeing posts that were 10 days old And the frustrating part? The conversations that actually mattered like buyers switching tools, people asking for alternatives

... According to @RevenueCat 's State of Subscription Apps 2026 report, " hard paywalls convert 5x better than freemium, but with significantly wider variance." Day 35 download-to-paid, freemium vs. hard paywall Does access method impact download-to-paid conversion within 35 days? Quoting the report: Median D35 conversion sits at 10.7% for hard paywalls. Freemium is 2.1%. That gap alone should make you pause. But the more revealing part is the distribution. Hard paywall top decile apps approach 40% conversion ... ... That s insane. Even the lower end performs at roughly double the freemium median. Behaviour

... like cardboard cutouts. The math gatekeeping was real. Then I discovered something that made me angry: the tools had evolved, but the learning resources hadn't. Unity ML-Agents lets you train reinforcement learning agents with visual tools. Unreal behavior trees are drag-and-drop. The complexity is already abstracted away. But every course still teaches like you're becoming an AI researcher instead of a game developer who wants to ship things. So I teamed up with some actual ... ... experts and built what I needed two years ago. AI Powered Game Dev For Beginners What's inside: Train NPCs that learn from player behavior

... just letting it rip . I m very curious whether others have struggled with free trial versus freemium and whether doing both is a bad idea (I m leaning towards that being a yes by the way). I also wonder if we are giving away too much for free and should be feature gating more. The challenge then shifts from a pricing perspective vs

... mental grid of 80 to 100 models drawn from across disciplines and use them simultaneously to analyze any situation: Physics & Systems : Feedback loops, critical mass, entropy, equilibrium Biology & Evolution : Natural selection, adaptation, ecosystems, redundancy Psychology & Behavior : Loss aversion, incentive bias, social proof, psychological denial Economics & Business : Opportunity cost, comparative advantage, creative destruction, moats Mathematics & Logic : Compounding, inversion, Bayesian thinking, power laws Engineering : Margin of safety, root cause analysis, redundancy design History & Philosophy : Second-order ... ... effects, Occam's Razor, circle of competence This isn't academic theory. Munger used this framework to make investment decisions, evaluate businesses, and understand human behavior

... descent." I'm not a math person. I quit three times over two years. Then I discovered something: modern game engines (Unity, Unreal) have AI tools that hide the complexity. You can train an NPC to learn from player behavior without writing a single line of calculus. Nobody told me that. Every course assumed I wanted to become an AI researcher. So I built what I wished existed. AI Powered Game Dev For Beginners What it actually ... ... required. Zero "let's derive backpropagation" energy. You build NPCs that learn, train reinforcement agents, make worlds that react 50+ hours of "watch me fail so you don't have to" content Unity ML-Agents, Unreal behavior

... 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 ... ... retrieval If your language does not match dominant queries, you will not be cited. Naming alone can materially change visibility. 3. Authority beats volume One high-signal, well-structured page can outperform dozens of lower-quality URLs. 4. Model behavior

... what your Windows system is really doing, in plain language. Sapience is a lightweight Windows security and visibility tool designed to help users understand unusual system behaviour without the noise or complexity of traditional security suites. Despite it being "lightweight" it is extremely powerful and has features usually only reserved for full EDR tools. It highlights things like: unusual or suspicious processes unexpected outbound network activity changes to scheduled tasks security relevant system events behaviours

... This is what memory polices offers - the ability to guide Mnexium's memory layer. Why Memory Policies? Not every app wants to memorize everything. Some teams need strict extraction rules for compliance, quality, or cost. Others need per-workflow behavior, like high-signal extraction in support chats and minimal extraction in casual chats. Memory Policies let you define those rules once, then apply them automatically with scope-aware resolution. API Endpoints Memory Policies are now available ... ... that I prefer concise weekly summaries.", model: "gpt-4o-mini", learn: true, recall: true, memory_policy: "mem_pol_support_assistant", }); console.log(response.content); What This Enables Memory Policies give teams a practical control plane for extraction quality. You can tune behavior

... written draft sitting there changes the task from "compose a thoughtful response" to "review and tweak." Way less cognitive load. We also added confidence scoring to each draft so you can quickly triage which ones are ready vs. which need your attention. Turns email into a 5-second review instead of a 5-minute writing task. Comment from AllurePixel(@allurepixel): I don t have a background in coding, so I really, really wanted to hand over all the keys ... ... Like you have never existed. And fall behind. Comment from Nika(@busmark_w_nika): @ponikarovskii  Which medical system? :) Comment from Nika(@busmark_w_nika): @joannachris  Regarding the first paragraph  did you refer to "access of human behaviour

... that lets you: Run what-if scenarios on marketing and product decisions Simulate responses across 100,000+ consumer simulations Explore outcomes before launching campaigns or features What s different The simulations are grounded in US Census based demographic and behavioral data Designed for startups making irreversible decisions with limited data Built to complement analytics, not replace them (use it before telemetry exists) Use cases we re seeing Testing positioning and messaging Comparing go-to-market strategies Stress-testing campaign ideas ...

... Common failure patterns observed Tokens designed for speculation instead of gameplay Unlimited or poorly controlled supply Whale dominance during ICOs High gas fees making gameplay impractical Interfaces built for crypto-native users only No protection against pump-and-dump behavior Why this matters: A game currency is not a DeFi token. The moment speculation outweighs utility, gameplay becomes secondary, and players disengage. SteliNovas was designed with the assumption that economic discipline matters more than hype . Project Context: What SteliNovas ... ... Blockchain UIs often assume users understand wallets, gas fees, and confirmations. Solution: UX design focused on clarity: wallet connection, SCNV purchase, and balance visibility were simplified using iterative feedback from non-technical users. Challenge 3: Preventing Pump-and-Dump Behavior

... sparked an interesting thought experiment: how likely is it that we ll see AGI (AI that thinks and learns like a human) within the next five years? The report highlights a fascinating divergence: the view from money vs. the view from science. Money : the probability inferred from trillions poured into data centers, Nvidia chips, and servers. Investors seem to be betting that AGI is inevitable. Science : the probability inferred from research papers and AI development models. Experts are far more ... ... What I take from this: AI is real and transformative, but the hype around AGI might be ahead of reality. Expect volatility, overpromised outcomes, and valuable lessons along the way. Meanwhile, AI continues reshaping work, attention, and human behavior

... howl while you're at work; they are experiencing a physiological panic attack. To stop the destruction and the noise, you have to stop managing symptoms and start rewiring their nervous system. Here is how to use canine behavioral science to turn your anxious pup into a confident, independent companion. ## The Science of "Safe Departures": Desensitization * **Identify the Triggers:** Explain how dogs associate "exit cues" (grabbing keys, putting on shoes) with abandonment, spiking cortisol before you even leave. * **The Muted ... ... immediately before you depart. * **Predictability:** How a rigid routine lowers baseline cortisol levels in high-strung breeds. ## When to Consult a Professional (The Medication Myth) * **Knowing the Signs:** Distinguishing between mild boredom and severe physiological distress (drooling, self-mutilation). * **Behavioral

... Emotions, not rational need, drive 70-95% of purchasing decisions. Not 'some' decisions. Not even 'most.' Almost ALL of them. These emotions? They're nudges - unconscious pushes toward behavior. And they're the most powerful nudges of all. Think about it: Stressed impulse buy (instant relief) Happy treat yourself (you deserve it!) Anxious avoid your bank account (because looking at it leads to additional stress) Spending gives instant gratification. Saving requires discipline. Our emotions push us toward the easier choice ...

... change. Threads often drift off-topic. High-quality answers may be buried under newer but less accurate responses. Performance can degrade as pages grow larger and more complex. And critically, the usefulness of a page often depends on the behavior of a community rather than on intentional editorial structure. Qeeebo takes a different path. A Static, Structured Alternative