... then yours. Now the plugin, its parents and anything inside it are refused, and an unrelated folder needs --force. The Where the deploy goes section of the WP Bones docs make:* never overwrite your work. A second make:controller Probe used to replace the file you were editing. Now it stops; --force if you mean it. tinker shows its errors instead of printing nothing, and never runs an exception message as code again. Failures exit 1 , so scripts ...

... build power, grow food, and research your way to the Moon and then to Mars. Each world has one resource the others need, so you run freight between them. The story ends when you send a fleet of probes out to the stars and your colonists go into a long sleep. What they wake up to is the ending. After that, the worlds are still yours to keep building. Why: a game that just keeps running never feels finished ...

... that only shows up when real money or real users are involved. What we're building toward: connect FetchSandbox MCP, prompt "make this app survive in prod," and the runtime reads your app config, infers the invariants that matter, probes against failure scenarios, then returns a public receipt with the full trace. Agent finds the bug, proposes the fix, re-runs to prove it held. Who this is for: builders on Lovable (or similar) who shipped something real and need ... ... that shows up in a support ticket or a chargeback, and by then a testing receipt is not what anyone is asking for. Comment from Raj Nagulapalle(@rnagulapalle): @rabnoor_s  100% agree on the business call vs

... Base44, etc. on the same stack. Same risk: anon key in the client, policies that look fine until they aren't. So I spent a day on hackymacky. Paste a URL. It checks the client bundle for secrets and probes anon Supabase permissions. MVP is rough. Looking for honest feedback: Is this a real problem for you, or already solved somehow? What would you want scanned that this doesn't cover yet? Anything about the flow that feels dumb ...

... write on the fetched object's own updated_at, so a stale read can't overwrite a fresher one, is what fixed it for me. Comment from Raj Nagulapalle(@rnagulapalle): @siarheihamanovich  Yeah that's actually how our probe engine works already, every run fetches current state from the provider before injecting anything so the twin always has real data to reason against. So we're aligned there. The concurrency one though, two concurrent fetches where the stale write wins ...

... guess: TLS 1.3 / TLS_AES_256_GCM_SHA384 against a local server, TLS 1.2 / ECDHE-RSA-AES256-GCM-SHA384 once I pinned that server down a version. so it's two more rows in the card, not a second probe. on the list, no date from me... one caveat worth stating, tbh, because it's where this kind of feature quietly overpromises: what you'd see is what that server chose while talking ...

... actually happened. Done : @maschiojv asked about Paddle, it now has 21 curated failure patterns instead of a bare spec import. @galdayan and @henry_s_jung both asked who keeps the sandbox honest over time. There's now a fidelity probe that fires the same request at the real provider and at our sandbox and diffs the result. It's already caught four real drifts in our own simulation. @vansh36 flagged the favicon was still the Next.js default. Fixed. Half done ...

... more often than ones that dont, has anyone actually run that comparison Comment from Nivy(@niveditha_patluri1): @bencohen  we track it. 20 buyer questions against a grounded model, aug 19. we came back mentioned in 0 of them. competitors got named in 17. the useful bit is what @serdarships said. one run each means the ci on that 0 runs up to 16%, so 20 probes

... exists. ) Behind a mail gateway? Proofpoint and Mimecast tenants don't advertise Microsoft in MX at all, so unknown domains now get one quiet "Work or school account?" line instead of a shrug. One line. We counted. The DNS probe goes through the machine's own resolver (DnsQuery_W) your domain never visits a third party, results are memoized, the whole thing is capped at 3 seconds, and if it fails the screen looks exactly like it did before. Fixed ... ... distinction between AADSTS65004 and the other consent errors is one of those tiny fixes users probably wont notice until it saves them from troubleshooting the wrong problem. Comment from Adams Parker(@adams_parker): I like that the DNS probe

... route table instead of the site is better than what I did and I am going to take it. Testing the matcher at the matcher also removes the thing that made my version slow, which is that every probe costs a round trip, so you stop early and call it clean. One axis worth adding to the generator, because it bit me today on a different property: the same path can return different things depending on request headers. I have ... ... coverage report is the concrete thing I'm taking from this. Different cadence, different granularity, and I'd have kept staring at coverage waiting for it to say something it structurally can't say. The absent-from-your-logs versus

... 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 ...

... stick for you. Comment from Siarhei Hamanovich(@siarheihamanovich): @monatruong_murror  I don't have that data cleanly either, and I'm the one who built the thing that would produce it, which tells you somethin. The cheapest probe I've found is the refill date. My free balance resets to 5 credits every 30 days, counted from each user's last renewal rather than a calendar date, so every free account hands me a small natural experiment ...

... 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 ...

... really an ordering bug a webhook arriving twice, out of order, or before the thing it references. Those are deterministic once you stop trying to hit the window and just fire the events in the pathological order; the probe controls the sequence instead of racing it. That covers most of them and we catch those reliably. Genuine nondeterministic concurrency (shared state, thread interleaving) is the harder tail .. if the bad interleaving can be forced/serialized we can reproduce ... ... 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

... caller, so treating its self description as evidence would have been the exact mistake. Comment from Giovambattista Fazioli(@gfazioli): @rabnoor_s  The "no artifact to review" line is the actual finding here, and it reframes what the probe is for. I'd been thinking of it as one more thing to check; you're describing it as giving an invisible property a location, which is a different and better job. A quarterly reminder with no page to open ...

... 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

... launch day? :) Comment from Nika(@busmark_w_nika): @konstantin_tikhaev  Wait! Did anything break in your tool? On launch day? :/ Comment from Nika(@busmark_w_nika): @victor_perdiguer  For how long have you been building the tool vs how long did you prepare for the Product Hunt launch? Comment from Nika(@busmark_w_nika): @new_user___26020267b63ea4605738cbb  I would recommend to add more images into the launch :) Comment from Nika(@busmark_w_nika): @nikunj_kothiya ... ... conversations were the real work; the ranking is just where they surface. One thing I'd add to your list from today: readiness to answer fast and honestly, especially the hard technical questions. We've had genuinely sharp people probe

... 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 ... ... better screener. And yes, please share this with your circle :) Feel free to ask any questions to us when you need something. Comment from Lavakumar E(@productrambler): @ian_fletcher1  Completely agree, and that's specifically what Mira's 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 ...