theORQL

@the_ORQL mentioned recently in this Dev.to post written by @BatsouElef Check it out 👇

Generic AI can hallucinate fixes. theORQL sees runtime evidence and maps UI to code instantly. One click runs: reproduce → fix → verify → diff You verify the fix by re-running. theORQL gives you a reviewable diff. Try it! 🔗 theorql.com #VibeCoding #FrontendDev #BuildInPublic

Most AI coding tools only see your code text. @the_ORQL sees the runtime reality: • Chrome stack traces • DOM signals • network events • build failures from Vercel / Netlify And maps it back to the exact code path in VS Code. Still active on Product Hunt if you want to check it out 👇 producthunt.com/products/stop-… #AItools #DevExperience #ProductHunt #DevTools #Chrome

Runtime context > educated guesses Here’s how theORQL compares to Cursor Debug Mode 👇 theorql.com/blog/40-theorq… #FrontendDebugging #AIForDevelopers 🛠️

Ever fixed a bug and then wondered if it actually fixed the issue? With theORQL you verify the fix by re-running. theORQL gives you a reviewable diff. Debugging you can trust. Active on ProductHunt 🚀 producthunt.com/products/stop-… Download theORQL here 👉🏼 theorql.com #AICoding #VibeCoding #DX #theORQL

Most AI coding tools only see your code text. @the_ORQL sees the runtime reality: • Chrome stack traces • DOM signals • network events • build failures from Vercel / Netlify And maps it back to the exact code path in VS Code. Still active on Product Hunt if you want to check it out 👇 producthunt.com/products/stop-… #AItools #DevExperience #ProductHunt #DevTools #Chrome

This happens a lot when a field moves fast. The technology leaps forward, but the organizations building it still evolve like traditional software companies. In dev tooling you see the same thing: AI speeds up coding, but the workflow around debugging and runtime context hasn't caught up yet.

In a sales cycle (buying) with one of the top 10 AI companies and it’s shocking how they’re just another software company: * Internal messiness between product lines and acquisitions * Sales team follow ups are inconsistent * Simple table stakes features don’t exist (timeline: months, which I’m sure will become quarters) I thought this was going to be like meeting the Beatles and it’s like talking to my buddies who work at random SaaS company number 83974839.

@itsandrewgao Honestly, not that crazy. GitHub gives agents structure: repos, diffs, history, ownership. Much easier to reason about than a pile of files in a drive. Same idea behind theORQL, giving agents structured runtime context instead of scattered logs.

i wonder if one second order effect of AI is that non-coders start to use github repos instead of google drive / one drive far-fetched idea, but it's way easier for agents to work with github than other file-storage software

@burkeholland This is exactly the trap people hit when vibe coding. Error. Paste. Retry. Repeat. At some point the agent is just guessing. Capturing the runtime evidence first changes the loop. That's actually the idea behind theORQL, give the agent the real context, not just error text.

If your AI agent can't fix a bug after 3 tries, stop. You're making it worse. Here's what most devs do - they paste the error message back into the chat. Agent tries something. Doesn't work. Paste the new error. Agent tries again. Doesn't work. You're now 10 messages deep and your code is more broken than when you started. This happens because the context window is poisoned. The agent is so fixated on its previous failed attempts that it's basically guessing at this point. Here's what you do instead. When the agent gets stuck, don't give it another error message. Give it a job. Say exactly this: "Add whatever logging we need to reproduce this bug." The agent knows your codebase. It'll drop console statements in exactly the right places - the ones it actually needs to understand what's happening. Strategic logging, baby. Works every time. Most of the time.

@_simonsmith Interesting signal. Editing with a light touch requires strong intent modeling and restraint. Most models optimize for 'rewrite quality', not 'diff quality'. Developers are starting to care more about the size and precision of the diff than the rewrite itself.

Seriously, GPT-5.4 is the first model to which I can say "edit my writing without changing my style" and get something back that's improved without being rewritten into generic AI output or slop, that's ready to post as-is. It gets my intent. It moderates its work. It has a light touch when I want it. Opus 4.6 is also a great writer and editor, but I find it's much harder to moderate. If I tell it to edit my writing without changing my style, I still tend to get back something that I feel removes my voice and I end up having to change quite a bit.

@thdxr Honestly a reasonable concern. The real issue isn't AI writing code, it's losing visibility into how that code gets from prompt, to repo and then production. The tooling around audibility and traceability hasn't caught up yet.

we spoke to a company today who's security team is so concerned by ai code they're considering banning ai tools your first reaction might be "they're gonna get left behind" but if you are practical their concerns aren't invalid if you are a huge multi national org with tens of thousands of employees and they just got a button that appears to do their work, it's gonna get pushed a lot and the process around knowing what is making it to production is totally melting being honest we're all getting a bit lazier see that kiro related aws outage as a real life example so they're genuinely arguing over how much this is going to be allowed esp since the net productivity gains for the average dev seem to be pretty low

@tomfgoodwin A lot of the variance comes from the stack around the model: tooling, context, latency, and workflows. Same model, completely different experience depending on how it's integrated, which is the layer we're thinking about at theORQL.

I still don't get how my entire feed is either "AI can do everything" "What AI can do is going to change everything" "AI is improving faster than ever" "AI can't do anything" "AI is pointless" "AI is actually getting worse" And not, It's complex It depends on when it depends on where it depends on how it depends on who it depends on X,Y, Z and more It can both be magical and impressive but neither valuable or effective

Safer quick-apply: [codex -p "Patch minimally to fix the bug; annotate why above each change." < file.py | diff -u file.py -] Read the diff, then apply. Eyes on, hands off.

Some bugs only appear in real browser conditions. @the_ORQL runs inside Chrome and captures live network requests, DOM mutations, and execution context when errors happen. Debug with precision. Live on ProductHunt! 🚀 producthunt.com/products/stop-… #JavaScript #ReactJS #DevTools #Engineering #ProductHunt

This is what debugging without context-switching looks like.

If you're vibecoding with AI, you already know: You ship faster. You experiment more. You break things differently. theORQL captures real runtime context inside Chrome so you're not debugging blind. Live on Product Hunt 🚀producthunt.com/products/stop-… #AIcoding #BuildInPublic #DevTools #ProductHunt

Still Top 5 among yesterday’s launches on Product Hunt 🚀 Huge thanks to everyone checking out theORQL and sharing feedback. Momentum continues 👉🏼 producthunt.com/products/stop-… #ProductHunt #DevTools

We're live on Product Hunt today 🚀 theORQL is built for AI-assisted dev workflows, when you're shipping fast, iterating constantly and bugs don't come with clean repro steps. It runs in Chrome, captures real runtime context, and helps compress the reproduce → fix → verify loop. Would love your thoughts 👉🏼 producthunt.com/products/stop-… #ProductHunt #BuildinPublic #DevTools

.@the_ORQL, a product that I've used a lot in the previous months, is launching today on @ProductHunt! 🚀 "Cursor for frontend. Build and debug in Chrome and VS Code." Let's support it! 🔗 (More info below) 👇

Today's the day, theORQL is live on Pruduct Hunt! 🎉 It runs in Chrome, captures real runtime context, and helps compress the reproduce → fix → verify loop. 🔗 producthunt.com/products/stop-… #Debugging #WebDev #ProductHunt