... finally read the whole study instead of the headline, and the actually useful findings are different from what got shared. First, in their realistic-config lane (instruction file + several MCP servers), the "light" harness came out HEAVIER: ~90.8k vs ~75k. A 72KB instruction file alone added ~20k tokens to every request, on both harnesses. Their own conclusion: configuration, not the harness, accounts for most of the production bill. The harness sets the floor, you set the ceiling. Second ... ... close to a fixed cost. An unstable small one can out-spend it. Size isn't the sin, churn is. Third, session shape flips the winner anyway. On a multi-step task the heavy harness finished cheaper (121k vs

... server on 127.0.0.1:3000 genuinely refuses connections from anywhere else so the check says "closed". Accurate, and completely useless. The most interesting services on the machine you care most about are exactly the ones a network probe can never see. Local Services a new tab on This Mac that doesn't probe

... I built SpatialProbe a 3D globe for exploring real terrain and imagery, layered with data earthquakes, wildfires, Wikipedia points of ...

... keep a daily probe that asks the assistants the buying questions in my category and records every source behind every answer. Last week I pointed it at Google's two AI surfaces, the AI Overview box and the fuller AI Mode, and counted. Thirteen answers. 168 citations. Every single answer used a different domain for each of its sources. Not one domain was cited twice, in any answer, the whole week. Thirteen of thirteen, no repeats. That stopped me, because ...

... edge than timing, honestly. ..today the generator works from the code path + known failure classes, not your real data distributions .. it doesn't peek at samples. What it can do is reason about what the code assumes vs. what it guards: if a handler does float(row['amount']) with no type check, "amount is sometimes a string / sometimes null" is exactly the shape it'll try, because the fragility is visible in the code even when the distribution ... ... type-coercion is a known class, so that one it'd likely catch. What it can't do is know a shape that only lives in your prod data and isn't betrayed by the code your 90/10 string-vs

... questions we got in our Product Hunt comments this week came from a researcher who asked something I've been thinking about ever since: When an AI moderator detects hesitation or an emotional shift mid-interview and decides to probe deeper how do you make sure the follow-up question uncovers the participant's thought rather than planting it? This is a real and serious concern. A human moderator reacting to visible confusion can easily lead a participant without realising ... ... phrase a follow-up the word you choose, the tone you use, even which moment you decide to probe

... limited testers. They gave us the first feedbacks for us to make the app better. After we didn't succeeded with a try on LinkedIn, where the feedback was nearly zero, we are on our way to find good alternatives. Hopefully Producthunt will help us and I'am pleased to help you, if you like. Maybe we will make the world of apps a little bit better. Is my first day on this page and we are very excited what ... ... about momentum. Great points you raised! Comment from Abusaid islam said(@abusaid_islam_said): @busmark_w_nika  Haha, absolutely! Coffee is definitely a must-have for launch day And to answer your question yes, 100%. Doing a quick "competitor

... 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

... exactly what we set out to kill. On verification: after generation we first compile the code (esbuild catches syntax/import errors), then boot the actual packaged extension in headless Chrome via Puppeteer. It loads the manifest, navigates each UI page, probes the background service worker for startup crashes, and captures uncaught exceptions and blank renders. Any real runtime failure is fed back into a self-healing loop that repairs it automatically before delivery so the verification is behavioral, not just "does ...

... says "this makes sense" while visibly struggling. In brand perception studies where stated attitudes don't match purchasing behaviour. The traditional workarounds are imperfect. Projective techniques add noise. Implicit association tests are hard to run at scale. Follow-up probing helps but depends entirely on the moderator catching the right moments. And even the best human moderator misses things, they can't track vocal confidence, facial micro-expressions, and conversation content simultaneously across 40 interviews. At Decode , the reason ... ... tools just made the performance flawless. The working principle that survived for me sounds exactly like your evidence-not-verdict framing: an inferred signal (emotion, confidence, AI-likeness) is only allowed to point a human at a moment worth probing

... launched Mira on Product Hunt today, and the conversations in the comments have been the most interesting part of the whole day. Researchers asked about probe neutrality whether the follow-up questions an AI asks mid-interview can lead a participant, rather than uncover them. They asked about cultural calibration, whether emotion models trained largely on Western data can accurately read a participant in Jakarta or Nairobi. They asked whether the say/feel mismatch gets surfaced as raw evidence or quietly ... ... moderated session? Is it full transparency into how emotional signals are weighted? The ability to see raw signals and override them before they appear in a report? Proof of regional validation against local human coders? Something structural about how probes

... agents will collect your peer reviews from people you have worked with. We use sentiment analysis to ensure reviews are not toxic. No one can review the same person in less than 3 months again. AI agents not only probes reviewers for skill based questions but also reviewee's personality questons All these reviews get converted into a trust score which you have put on your CV, LinkedIn or Email Signature. Some points which came in the questions ...

... compare findings across multiple projects over time. The part most people ask about: The emotional layer runs during the interview not after. So when a participant says "I like it" but their face shows hesitation, Mira catches it and probes deeper in the same conversation. That is the core difference from transcript-only tools. First study is free this month happy to help anyone set one up. Drop a comment below or book here: https://www.entropik.io/book-dem... See Mira ...

... from outside the process is short. Node selection pressure (no, no evictions in the events). A draining node (no, the nodes were stable). An admission controller (no, none configured for this). Or kubelet itself, in response to a failing probe. That last one was a thread we hadn t pulled on yet. The one pod that lived Before pulling it, we noticed something we d been overlooking. We had several web pods running the same image, with the same ... ... should have looked at sooner kubectl describe pod on a crash-looping pod had been telling us the answer the whole time, in 2 lines we d glossed over because they looked like noise: Warning Unhealthy worker-... Liveness probe

... live links click one and the main window opens right on that section, even if you'd closed it. The little live traffic chart and one-click IP copy are still there. Shortcuts that follow you . Refresh, Probe Ports and Alert History used to only work on the Devices tab. Now they work from anywhere. And a polish pass everywhere the device list, the Wi-Fi list and the Security views all share the new look, search sits where ... ... those popover cards (devices, risk, public IP, alerts) are clickable, tap one and the main window opens right on that section even if you'd closed it. So it's a launchpad now, not just a dashboard. Second, Refresh / Probe

... plans multi-step tasks, calls tools, checks its own output, and keeps going without hand-holding. Demos include autonomously playing Factorio and building a working CAD editor (with its own AI copilot inside). Coding: 80.3% on SWE-Bench Pro vs 69.2% for Opus 4.8. Knowledge work: top scores on GDPval-AA, ahead of Opus, GPT-5.5 and Gemini 3.1 Pro. Long context + vision: noticeably stronger on long documents and multi-turn work. The interesting twist: it ships with hard guardrails ... ... Comment from Geert Zaal(@geert_zaal): first impressions are in on working in a mature Swift/Appkit environment (MetaScope) after using Fable 5 on a long coding arc: it raised the floor a lot. Strong coherence over many hours, empirical probes

... actual insight, and it's bigger than it looks: making the notification say why it's waiting is what turns a ping into a triage. "Done" makes you tab back to find out what "done" means. "Needs approval vs finished vs

... being genuinely citeable, not fluff) plus third-party content and distribution (Reddit, Substack, mentions). Engines weight both. Onsite alone won't do it; distribution alone won't either. So, keep the SEO compounding, and treat GEO as something you probe and measure as you go, rather than look to rank on immediately. Comment from kaavya prasad(@kaavya_prasad): @lyshen  That's a great question! The answer is yes and no, and I think the nuance actually matters here ...

... early days. Buyers want to know who they're trusting, not just what they're buying. Would do it differently now founder brand first, product brand second. Comment from Henry Stewart(@henry_stewart): Maybe it s less brand first vs product first and more about separation. Build visibility if it helps, but keep product assets and founder identity separate enough that the business can scale or change hands later. Comment from Nika(@busmark_w_nika): @azouzidesign  To be honest ... ... just sharing what I've found, people engage differently than when they encounter the product cold. They ask questions, share their own experiences, and tell me what they wish existed. I haven't A/B tested "anonymous launch vs

... track changes. Comment from Maliik(@maliikb): @imed_radhouani  Honestly, I don't have a perfect answer, which is probably the most honest thing I can say. The current design is tiered ingestion. RSS feeds run first as lightweight probes. They're fast, rarely rate-limited, and catch most new recalls within minutes. The heavier API calls only run for enrichment: full details, images, classification data that RSS doesn't carry. So at 2x volume, the RSS layer scales fine ... ... spent 6 months paying for shortcuts you took in the first 6 weeks. The cost breakdown is not about the money. It is about the lost features you never got to build. The customers you never acquired. The competitors

... users. What we saw building BlockaBot says otherwise. Using BlockaBot.com , In the last 24 hours from a small test deployment: 398 unique threat IPs observed 68 total requests captured, all identified as automated 59 WordPress-related attack attempts Continuous probing across admin paths and random endpoints Peak hour reached 99 unique attacking IPs Top attacking IPs (sample): 34.138.252.24 193.32.126.230 8.229.128.10 35.230.33.51 These are not targeted attacks. They are constant, automated scans looking for anything exposed: wp-login and WordPress surfaces ... ... admin panels PHP endpoints misconfigured environments BlockaBot was built to deal with this layer before it becomes a problem. What it does: Detects and classifies incoming traffic in real time Identifies attack patterns like WordPress probes

... identifies your core arguments and organizes them into a logical draft in real-time. Not Solo Thinking, but Socratic Dialogue: SocraDraft is a "Thought Partner." It asks you the questions you didn't think to ask yourself. It probes your logic, surfaces blind spots, and pushes you to explain your ideas more clearly. Not Static Storage, but Dynamic Output: The goal isn't a "note." The goal is a Knowledge Artifact . Whether it s a blog post, a memo ... ... note-taking happens when we're in "capture mode" but writing needs "creation mode" which feels like a completely different headspace. I'm wondering how SocraDraft handles that mental shift, like if I'm dumping thoughts after a meeting versus

... milestone: 300 points @Kilo Code  still is #1 Product of the Day and just reached 300 points. 07:00:AM:PST - new milestone: 331 points When @Kilo Code first launched their @VS Code extension on Product Hunt about a year ago , they got 330 points. They just surpassed it. Product Hunt is about consistency. Launch, and keep launching. 09:39:AM:PST - new milestone: 400 points Currently #1 Product of the Day, @Kilo Code just reached 400 points. They ... ... launch? Would love your hunter eye Comment from Siarhei(@siarhei_ai): @fmerian Congrats on the launch! Kilo Code Reviewer looks solid auto PR reviews with 500+ models is huge for speed. We re doing similar in voice: real-time probes

... different moment: when you ve dog-eared a book, paused a podcast, or stepped away from an article because YOU have something to say, and the window to crystallize a thought is closing fast. Instead of summarizing, it asks, probes, and reflects, so your ideas don t evaporate. Question for the community: does this pain point resonate with you as well, and if so, what non- summarizing features would actually help you think in that moment? Launching soon. https://classix.app ...

... making engine. It doesn't just "chat" with you; it audits you. The Council: 5 AI members Alpha (Logic), Dominic (Action), Augustus (Data), Lilith (Safety), and Serena (Harmony) each with distinct roles to tear apart your dilemma. The 3-Probe Rule: You have only 3 opportunities to cross-examine specific members. You must decide who to trust. The 16-Point Audit: Submit your final plan. If the Council doesn't score it at least 16/25, you are REJECTED. High Stakes ...