
Codepilot AI Code Review
Analyze and debug code with AI-powered review using OpenAI's API.
TOPDEV99999 · GitHub
AI-codepilot An advanced AI-driven code analysis tool built with Next.js, leveraging OpenAI's API to review and debug code efficiently.
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Analyze and debug code with AI-powered review using OpenAI's API.
TOPDEV99999 · GitHub
AI-codepilot An advanced AI-driven code analysis tool built with Next.js, leveraging OpenAI's API to review and debug code efficiently.

Inspect and debug AI agents to identify step-by-step where they fail.
mathurpriya19 · HN
Kalytera – Find out why your AI agent failed, step-by-step

Benchmark AI models by having them animate a 3D banana plant's full lifecycle.
fran-mora · HN
I gave 5 AI coding agents one prompt: grow a banana plant through its whole life in three.js: sprout, leaves, flower, fruit, rot, then pups that restart the loop. It's deceptively simple and yet very hard to get right from procedural code: you have to write working three.js and understand how the plant is actually built; how it hangs, ages and decays. Get the biology wrong and the code renders something weird. These are agents, not bare models (Claude Code and Codex for now). They can use tools, including playwright to check their work and improve it.

Test AI agents against production mirrors using replayed traces to find bugs and regressions.
aisinghal

Capture in-app recordings and screenshots, then triage feedback with AI to fix bugs faster.
@keshav__dev · X
Hi priyanka i am also building in customer feedback space but with some dev related features. Maybe you want to check

110+ free developer tools including JSON formatter, JWT decoder, and regex tester that run entirely in your browser.
@abhilakshharora · X
Just launched DevTab on Product Hunt 🚀 110+ dev tools that run 100% in your browser. Zero server calls. No signup. Free forever. Would love your support 🙏 → #buildinpublic #DevTools

Work through code review challenges and system design problems to practice technical evaluation.
u/Most-Football-4401 · Reddit
AI is writing more and more of our code. I think that means we need to get much better at reviewing it. We have a lot of tools to practice coding (LeetCode, HackerRank, Codewars, and so on). But I see very little on practising reviewing code, especially code written by AI . I am aware industry is running to build tools for AI review AI written code (the fox guarding the henhouse). But I believe it is just a matter of time before regulators start slapping hands for doing so in regulated indus

Measure code review performance across GitHub teams with leaderboards and reviewer analytics.
u/SnooStrawberries827 · Reddit
my team had 47 open PRs and nobody was reviewing them, so I gamified it our team hit 47 open PRs at one point last month and nobody was reviewing them. tried slack reminders, deadlines, rotating reviewers, none of it really stuck. might be related to the fact that everyone's hyped about how fast AI can write code now, copilot cranking out entire features in hours, but none of that matters if the PR just sits there for a week. feels like writing code stopped being the bottleneck a while back

Notes with code blocks, Kanban bug tracker, and snippet library with GitHub import.
@SinghApurv1711 · X
Hey! Check it out here:

Connect a GitHub repo to automatically detect user flows, visualize code structure, and identify where users get stuck.
u/freestyle_gonzo · Reddit
Vibe coding made building fast. It didn't make understanding easy. Something changed in the last year. Vibe coding (or agentic engineering if you ask some) made writing an app fast. Week-to-weekend fast. More people are building software than ever before, and I think that's a genuinely good thing. But fast building creates a new bottleneck. Writing code is no longer the hard part. Understanding what you built and its nuances is. A huge share of people shipping right now have never analyzed

Autonomous agents that test web and mobile apps to discover flows, find bugs, and replay scenarios.
@AbdullahYusufY · X
Here is ours We are developing autonomous QA agents feel free to check it out.

Detect if your LLM API has been model-swapped or degraded with 6 deterministic probes.
cocodot LLM 降智检测 — 免费的 LLM API「降智/偷换模型」在线检测:填入任意 OpenAI 兼容端点的 base_url 和临时 API Key,跑 6 项探针(模型声明、动态题、能力完整性等)生成分项报告;Key 仅用于当次检测、不落库不留存,检测方法[开源](https://github.com/cocodot2026/cocodot-llmprobe)