... without actually understanding what triggered the failure. So I changed the order. Now my first request is: Reproduce the failure before changing anything. I ask the agent to: identify the exact failing scenario reproduce it locally show the expected vs actual behavior identify the smallest failing case explain what it thinks is happening only then propose a fix That extra step has been useful because it separates: I found some code that looks suspicious from: I can actually reproduce ... ... problem this code causes. It also catches a second problem: sometimes the reported bug isn't actually a bug in the code being inspected

... Closed-source software asks us to trust what we cannot inspect. We want to build differently. Three months ago, my co-founder and I quit our jobs to build Meridian full-time. It is an open-source, local-first AI work journal that runs on your device, captures your development activity, and drafts clear worklogs and updates for tools like Jira. Nothing leaves your device until you approve it. Meridian is MIT-licensed and free for individual developers. Your thoughts ... ... instead of being reconstructed from memory at the end of the week. Hoping meridian makes a difference to you! Comment from Akarsh Hegde(@akarsh_hegde): Open source is the foundation, not a marketing label. Developers should be able to inspect

... Three months ago, my co-founder and I quit our jobs to build Meridian full-time. We believe developers should be able to inspect the software that captures their work, control what it includes, and approve every update before it is shared. Meridian is an open-source, local-first AI work journal. It runs on your device, captures development activity, and drafts clear worklogs and updates for tools like Jira. Nothing leaves your device until you approve ...

... observability, and evaluations. To get started faster, browse ready-to-run workflow templates that you can copy, adapt, and run in your own Heym instance . You can also visit the Workflow Playground to explore real recorded workflow runs, inspect each node, and copy the workflow into your own canvas. We d love to hear what you are building and which workflows you would like to automate with Heym ...

... Over the past few years, I've noticed AI-powered UAVs evolving from simple aerial cameras into intelligent systems that can inspect infrastructure, monitor crops, generate maps, detect anomalies, and even make decisions during autonomous flights. The technology seems ready for much broader adoption, yet many industries still rely on traditional workflows. From what I've seen, the potential benefits include: Faster inspections

... automated my site's indexing checks this month and hit a wall that surprised me. The Search Console API will inspect URLs, report coverage state and resubmit sitemaps. The separate Indexing API only accepts job postings and livestream pages. The one thing everyone actually wants, the Request Indexing button, has no API at all. So my daily job does everything the API allows, inspects

... thing I rarely see discussed in B2B software is inspection fatigue . Not user fatigue. Not notification fatigue. Inspection

... built Toolboard because my browser workflow was fragmented across too many single-purpose extensions. It started with a small set of utilities and eventually grew into 83 tools for inspection, capture, conversion, productivity, and optional AI-assisted workflows. The biggest challenge was no longer adding features. It was keeping the product coherent: making 83 tools discoverable without turning the interface into a directory keeping interaction patterns consistent explaining why permissions such as tabs, clipboard, and capture access are needed separating ...

... when the product changes faster than the test suite. Agentic UI testing gives us a different shape. Instead of encoding every assertion as rigid script logic, we can let an agent read a test case, drive the browser, inspect the page, collect evidence, and judge whether the user-facing expectation is satisfied. The script becomes the harness: it controls safety, browser access, reporting, credentials, screenshots, setup, and repeatability. The agent handles the parts that require interpretation. This article describes ... ... focus and keyboard edge cases - OAuth or identity-provider flows - browser permission prompts - clipboard behavior - native dialogs - layout differences caused by real window chrome - animations and timing that behave differently under headless mode - visual regressions that require human-like inspection

... already discuss productivity, worklogs, AI coding agents, Jira, Linear, GitHub Issues, and engineering visibility. Use GitHub as the trust layer, since the product is open-source and local-first. The goal is not just stars, but getting developers to inspect it, try it, and share feedback. Create practical content around the pain: context switching, forgotten work, messy PR trails, standup updates, async reporting, and the gap between what actually happened during the day and what gets captured in tools. Talk ... ... effortless now. Direct conversations with individual developers also makes sense as the next step, since I need to validate whether a solo developer gets day-one value without a manager or team reporting layer involved. The bottom-up vs

... checklists, and audit forms. The real challenge is keeping those standards alive every single day. A checklist can exist, but if it s too long, too slow, or disconnected from frontline reality, people stop using it. Reports get archived. Inspections become a box ticking exercise. That s why I started building MORN. Not just another digital checklist tool, but a simpler way for teams to perform inspections

... probably a ton of other people feeling the same way. So I decided to just build my own. That's how Traceo came about, a Chrome extension for designers, developers, and QA folks. Instead of digging through DevTools to inspect CSS or report a UI bug, Traceo lets you inspect

... about this stuff way earlier than most. Plenty of people don't touch any of it until it's cost them a lot more than a not-live bug. Comment from Gal Dayan(@galdayan): @aadilghani  same read-only-vs-reversible line for me. the thing that changed it wasn't a rule I wrote, it was switching to a tool that asks per-action instead of per-session - so "let it rip" doesn't mean blanket auto-approve ... ... tabbing back to check more than I'd like. curious what your notification approach surfaces beyond just pass/fail. Comment from Stacy Wycoff(@stacywycof83995): @aadilghani  I don't run coding agents but I have the same read-only vs

... view that transforms everything your agents have read, written, and learned into an interactive 3D knowledge graph. The graph helps you explore files, previous decisions, development sessions, task relationships, and knowledge created by different AI coding agents. You can inspect connections, download important information, and reuse memory across agents instead of starting every session from zero. 4. Focus Mode and Break Games The Pomodoro timer inside Termi is now a complete focus tool. You can choose a session length, work ... ... limit context loss is the single most expensive interruption there is: the work isn't gone, but the agent's understanding of it is, and rebuilding that costs more than any feature saves. For what's next: unified "blocked vs

... Localization Jobs UI  lands end-to-end. Inspect job groups, watch per-language progress, see the source payload, see the webhook delivery, drill into any failed locale. The  async localization API  ships jobs in parallel across every target locale, retries on failure, and webhooks back when done now you can watch it happen instead of reconstructing from logs. Full changelog: lingo.dev/changelog ...

... coding agents. The goal is to keep the agents you already use, such as Claude Code, Codex CLI, Gemini CLI, OpenCode, Claude Desktop, and Codex Desktop, in one workflow: launch, bridge, inspect, continue, preview, and control them across devices. What s new in v0.7.7: Local Agent API Expose local Claude / Codex-style agents as OpenAI / Anthropic-compatible APIs for development and local testing. Remote / IM session continuity Better handover and pickup across desktop, mobile, browser, and IM channels, with ... ... headers, and several dense settings surfaces so the app is easier to scan and operate. Provider catalog and model picker updates Refreshed model/provider metadata for Kimi, DashScope, Volcengine, ZAI, MiMo, MiniMax, and other compatible API providers. Launch and request inspection

... comparisons, or historical trends would help you make better launch decisions? Comment from Antwon Randolph(@antwon_randolph2): Upvote velocity by hour (not just total count), conversion from tool page to signup, and where traffic is coming from - organic PH vs. maker's own network. Those three together tell you if a launch is actually working or just getting a popularity boost from the maker's existing audience. Comment from M. M. Carvalho(@m_m_carvalho): @oshylabs  Shipped ... ... substantive column right next to coverage, on the same denominator so the gap is impossible to miss. It uses exactly the crude signals you named: whether the reply carries a link or a number, and its length versus

... runbooks, and agent skills that can run Python and generate real files and reports. New integrations Amazon S3, Supabase, Discord, ElevenLabs, and ChatGPT through MCP. We are building Heym as a self-hosted AI workflow platform that teams can inspect, secure, and operate in production. We would really value feedback from the Product Hunt community: Which of these areas matters most to you right now? Security Observability Migration Integrations Agent capabilities Product: https://heym.run GitHub: https://github.com/heymrun/heym Which area ...

... mostly about making local coding-agent setups easier to debug and less fragile: Added a Bridge recorder for local API bridge debugging. When bridge mode is enabled, you can open a live recorder from the connection popup and inspect the original request body, bridge request body, upstream response body, and bridge response body. Improved local bridge proxy bypass for Codex launches, including local NO_PROXY coverage and Codex Desktop macOS no-proxy launch args, so system proxies like Clash ... ... agent flows I often want to see the exact payload shape at each step. A small transformation or routing mismatch can look mysterious from the outside. The recorder is basically there to make those failures less magical and more inspectable

... search support. - Search sources are configured locally in Settings; API keys stay in local settings. - Supported search source: Exa, Tavily, Grok, and Brave. Also new in this release: - Test configured web search sources directly from the desktop Settings flow. - Inspect search requests and source-separated results in the Bridge recorder. - Better profile connection coverage around bridge launches and provider test flows. - Fixes for Codex Desktop API bridge model routing, including fake model IDs such as `GPT-5.5` with DeepSeek. - Compatibility ... ... philip_coleman1  Pretty close in practice. VibeAround runs search sources in parallel, so the added overhead is small: mostly the search provider response time plus a bit of local normalization. For normal coding-agent use, the latency difference vs

... Cursor: coding Supabase: backend and auth Vercel: hosting GitHub: version control Google Search Console: SEO Campix: my own project, camp software, yes I'm biased Comment from Hans Desjarlais(@ismaelyws): Gmail Calendly Claude Code Google Docs & Sheets VS Code Comment from Bill Davis(@billspaced): @nolan_vu  Slack, not because I love it but because everything dies without it. YESSSSSSSSSSSSS Comment from Bill Davis(@billspaced): @riya_pariyar   @benfleming   @asapx  same question... never heard ... ... solo founder, these are the five tools I use almost every day: ChatGPT VS

... those features that sounds simple but saves a ton of time once you've got hundreds of saved videos sitting there unwatched. Curious how it holds up on longer form stuff like 1-2hr podcasts versus a short clip. Comment from Nolan Vu(@nolan_vu): @nidhisachan  I am glad to share and support your business case. Hope that your product can upgrade and develop further later on. I will continue sharing new stories so that businesses like your ... ... such a sharp positioning line, car listings hiding damage is one of those industry-wide trust problems nobody talks about directly. Solo and 4 weeks in is no joke. My honest take on your free-tool-vs

... real terminal? That is the gap LabEx Challenges is designed to address. Each challenge runs in a real hands-on environment. Users are given a task, a system state, and a set of checks. They need to inspect files, run commands, debug issues, configure services, or fix broken systems. Instead of choosing an answer, they have to make the environment pass verification. In that sense, the experience is closer to coding challenge platforms, but focused on Linux and infrastructure skills ... ... concepts, but challenges show whether you can actually use them when the steps are no longer written out. The real terminal + verification part feels especially important. A lot of Linux learning breaks down when the learner has to inspect

... None of these are bugs. They're what happens when memory is append-only and nobody's pruning it. The right model: . Every update is a commit. You can diff what it knows now vs. six months ago, roll back a wrong inference, audit what changed after a bad interaction. "The AI knows me" should mean something specific and inspectable

... Something I built led to a design decision I want to get feedback on. LineageLens is a free VS Code extension that captures every AI code insertion and scores it for risk on a 0 100 scale. Works with Cursor, Copilot, ClaudeCode, Gemini CLI. Zero config on install just start using your AI tools and your insertions start showing up in the sidebar. The scoring is deterministic rules: +28 for credential-like material, +24 for eval/exec patterns, +22 for subprocess ... ... This solves a problem I didn't realize I had until I read this. We've been using AI-generated code in production for months and honestly have no clear picture of which parts were written by AI vs