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You.com AI

You.com AI

You.com AI

You.com AI

You.com AI

You.com AI

You.com AI

You.com AI

You.com AI

You.com AI

I created an amazing Chrome extension that helps transfer chats to another AI when the chat limit is reached.

I created a chrome extension which helps in switching conversation without losing your Chat context between multiple AI , such as Chatgpt to Gemini , claude , grok , etc . You can interchange btw any of them . Try it's free - https://chromewebstore.google.com/detail/ai-chat-transfer/gfeohkmgfphhoodfhiaffmgcoeljhnhp Uses of this extension - The extension is useful when chat limits, usage caps, or context limits are reached on one platform. Instead of losing progress or restarting from scratch, users can continue the same conversation in another AI tool while keeping important context intact. It is designed for researchers, developers, writers, students, marketers, creators, and AI power users who regularly work across multiple AI models. The extension helps preserve prompts, code snippets, brainstorming sessions, research discussions, and long-form conversations. AI CHAT TRANSFER also helps reduce repetitive explaining by carrying over previous discussion context between AI systems. This makes comparing responses, testing different models, and maintaining workflow continuity much faster and more efficient. submitted by /u/Faaaaaaaaaaaah [link] [comments]

Top mathematician Timothy Gowers: "AI has now solved a major open problem ... one that many mathematicians had tried."

submitted by /u/EchoOfOppenheimer [link] [comments]

I used Claude Code to build while delegating coding to Mistral/DeepSeek - 10 days, 57M tokens saved, over 90% costs savings, Claude quality result

I've been running vibe-skill ( https://github.com/pcx-wave/vibe-skill ), a Claude Code skill that delegates coding tasks to Mistral Vibe instead of burning Claude tokens. I initially did that because couldn't bear with hitting session limits so fast on Pro plan, but didn't want to lose the quality of Claude's planning. Here's a breakdown after 10 days usage. What it does: you type /vibeon , Claude decomposes the task and delegates coding to Vibe, Claude reviews the diff and corrects if necessary. Vibe's token burn stays on the cheap model. Vibe being agnostic, i tried with default model (Mistral medium 3.5) and Deepseek vs flash. 10-day results (254 runs, 57M tokens delegated) By model: Model Tokens Actual cost Claude equiv Savings DeepSeek V4 Flash 29M $4.13 $92.16 95% Mistral Medium 3.5 28M $0 (pro sub) $84.77 100% 98% success rate across 254 runs. If something fails, Claude catches it and corrects. Mistral tokens are usually 50% cheaper than Claudes, Deepseek tokens are 95% cheaper... however i'm also a pro subscriber of mistral so i get a huge quota of free tokens included with the sub (circa 1Bn). So with Mistral Pro, every delegation is $0 until quota is reached, at which point you switch to DeepSeek immediately (Mistral PAYG at $1.52/M is 10× more expensive than DeepSeek). So at what monthly volume does DeepSeek alone cost more than the Mistral sub? $18.36 mistral sub price / $0.14 per M deepseek token cost = 131M tokens/month Below 131M → DeepSeek alone is cheaper, no Mistral subscription needed. Above 131M → Mistral Pro wins, and you get ~10× more headroom before hitting the quota. More details in repo concerning orchestration flow: https://github.com/pcx-wave/vibe-skill Did a similar skill with gemini https://github.com/pcx-wave/gemini-skill as i know they give cheap tokens too, but haven't practiced it as much yet because gemini isn't as configurable as vibe so delegation can be a bit flaky. submitted by /u/pcx_wave [link] [comments]

MCP Apps Developers : Skybridge Framework v1 released 🎉

Hi Reddit, Over the last few weeks, my team and I at Alpic have been working on a complete revamp of the Skybridge framework to make it as smooth and easy to get started with as possible. As you may know, Skybridge is an open-source framework we built to help developers get started with MCP apps. It’s a thin layer on top of the official TypeScript SDK that provides the wiring and tooling needed specifically for apps. We believe that apps integrated into chats will soon play a key role in how people access information and interact with the web. With this v1 release, we’ve introduced: New DevTools with a UI designed specifically for MCP apps development An integrated tunnel that can be started with a single click directly from the DevTools Shareable chat URLs to test or showcase your MCP apps with a real LLM An audit feature to ensure your app and metadata comply with store requirements before submission (which can save a lot of time, since app reviews can be lengthy!) We also stabilized the API with a simplified design and are proud to offer strong tool-to-component type safety. It’s now also possible to deploy Skybridge outside of Alpic (the company behind Skybridge). While Alpic was designed specifically for MCP app hosting, we understand that some users may prefer hosting on different stacks for their own reasons. Hope you enjoy it! github.com/alpic-ai/skybridge submitted by /u/harijoe_ [link] [comments]

Neevu is finally launched! As a new parent, this journey was definitely not easy.

I became a dad in November 2025, and the first two months were so chaotic. I looked for parenting apps to help us through it, but most were either too expensive or just not something we connected with. I’m a Product Designer (UI/UX) by profession, so one day I thought, why not build the app we wished we had? Building an app while learning how to take care of a tiny new life at the same time was a challenge. My wife and I spent weeks brainstorming, improving, testing, and refining every part of the app together. It’s still an MVP, but we’re proud of what we’ve built as parents. Neevu is a baby development, growth tracking, and parenting app for babies aged 0–12 months, built with Indian parenting in mind. We divided the app into two phases: Gentle Phase and Play Phase. Gentle Phase (0–2 months) The first two months can be overwhelming and anxiety-inducing. We wanted this phase to feel supportive instead of stressful. That’s why Neevu is completely free for parents with 0–2 month babies. No paywalls. No locked features. Just guidance when parents need it the most. Parents can choose to support us with Premium, but it’s completely optional during this phase. Gentle Phase includes: Weekly guidance to help parents understand baby’s growth and what to expect next Gentle Essentials, simple newborn reminders without pressure or endless checklists Daily affirmations for difficult days Milestones and Growth tracking Songs and lullabies Parenting articles This is our small gift to new parents. Play Phase (2–12 months) As babies grow, Neevu becomes more activity-focused. Play Phase is completely free for the first 14 days. No credit-card required. It includes: Daily age-based developmental activities Activities focused on cognitive, physical, social, emotional, and language development CDC-based milestone tracking WHO-based height and weight tracking Parenting articles covering various topics for babies, moms and dads Stories, lullabies, action songs, and folk tales One thing we consciously included was article support for dads. We noticed that a father’s mental well-being is often ignored after childbirth, and we wanted Neevu to acknowledge that too. All content inside Neevu is strictly reviewed using guidelines from AAP, IAP, CDC, and WHO. We never wanted to build something we wouldn’t personally trust as parents. We hope Neevu helps make life a little easier for new parents trying to figure things out one day at a time. If you’d like to support us, please download the app on the Play Store and leave a rating or review ❤️ Get it on Play Store: https://play.google.com/store/apps/details?id=com.neevu.app Built using Claude Code, Codex, Figma, and ChatGPT. iOS app is coming soon. submitted by /u/VisAlGhul [link] [comments]

Four backend concepts for Product Managers using Claude Code

You don't need to write backend code. But if you understand how backend systems behave, your prompts get dramatically better because you're speaking the same language as the system. Async vs Sync: user clicks "generate," you call OpenAI, it takes 3-5 seconds. If that's synchronous, the entire UI freezes, Nothing responds. The fix is to make the call async. Show a loading state immediately, let the user keep interacting, update the screen when the response arrives. Tell Claude Code "handle this asynchronously" and watch the output quality jump. Race conditions: two users click "claim this spot" on the last available slot at the same second. Backend reads the database, sees one spot, confirms both. Now you have a double booking. You don't need to write the fix, but you need to spot this pattern in your specs. Anytime a user action reads a value then updates it, ask one question: what happens if two users do this at the same time? The fix is an atomic transaction read and write happen as one indivisible operation. Idempotency user submits a form, internet cuts out for half a second. Did it go through? They don't know, so they click again. Without idempotency, you now have two records. With it, the second request returns the same result without creating a duplicate. The fix is an idempotency key is unique ID generated on the frontend, sent with every request. Backend checks if it already processed that key. Stripe uses this for every payment call. Graceful degradation: your app calls OpenAI and the API is down. If you haven't planned for this, users see a blank screen or a raw error code. Every feature needs three states: happy path (everything works), loading state (we're waiting), error state (something failed). Retry up to three times. If it still fails, show a friendly message and keep the rest of the page working. Never let one dependency take down the whole experience. TLDR: Next time you're in Claude Code, try using these terms in your prompt — "handle this asynchronously," "make this endpoint idempotent," "add graceful degradation." The output gets significantly better when you speak the system's language. Post inspired from this video, you can checkout SkillAgents AI on Youtube for similar content. submitted by /u/InfamousInvestigator [link] [comments]

Got Rick rolled by Claude

Had opus put together a mock up of a Web link page, I guess it has substantial training data on “never going to give you up “ being a popular video link to share. submitted by /u/Matthew_Kvamme [link] [comments]

Anthropic's skills guide as an interactive walkthrough skill

Someone suggested that Anthropic's skill building guide should be a skill that walks you through it not a pdf, so here it is: https://github.com/egalano/build-a-skill Install it, say "walk me through building a skill" in a new chat, and the agent runs the tutorial. It asks what you want to build, drafts the YAML with you, picks the workflow pattern that fits, and runs a checklist before you ship. Should take about 15-20 minutes. The content adhere's strictly to the guide from Anthropic's pdf I just rearranged it into a conversational flow. Install: the zip from the Github releases, upload via Settings → Capabilities → Skills, or Unzip it, cd into the new directory and: cp -r build-a-skill ~/.claude/skills/ for claude code Would love to hear how it works for you. Please flag any potential improvements or issues you come across submitted by /u/hypereg [link] [comments]

I A/B tested Claude building UI with vs without a design spec (200 apps)

I kept seeing the "Opus is ridiculous for frontend" takes and wanted to know how much of that is the model vs what you feed it. So instead of arguing, I ran it as an eval. Setup: same "clone this screen" task across 200 well-known apps (Spotify, Things, Linear, Duolingo, etc.). Two conditions — (1) prompt + screenshot only, (2) same prompt + a structured DESIGN.md spec (design tokens, spacing scale, component list, states, nav model). Targets: SwiftUI, Jetpack Compose, and Expo. What I found: Iterations to "ship-able" dropped from ~5-6 to ~2 with a spec. Component choice got idiomatic — spec runs used native nav/list patterns; prompt-only runs reached for generic stacks/divs regardless of platform. Biggest delta was consistency across screens. Prompt-only drifts on spacing and type scale screen to screen. Spec-fed stays locked because the tokens are pinned. The model mattered surprisingly little for layout fidelity once the spec was there. It mattered a lot without one. Takeaway: "Claude is good/bad at frontend" is mostly a context problem. The spec does the heavy lifting. I open-sourced the 200 specs I used (MIT, plain markdown, no deps) so you can repro or just drop them into Claude Code: https://github.com/Meliwat/awesome-ios-design-md/ Two questions: Which apps should I add next? Taking requests — that's literally how the list grows. For those of you vibe-coding UI without reading the output (saw the phone post this week) — are you eval-ing the result at all, or shipping on vibes? submitted by /u/meliwat [link] [comments]

why cant i delete my acc😭

submitted by /u/DlCKH34D [link] [comments]

Open-sourced an MCP server that catches the security mistakes Claude / Cursor / Copilot actually make

AI coding tools like Claude, Cursor, and Copilot sometimes write code that looks fine but quietly leaves your app wide open like turning off security checks to make an error go away, or telling you to install a software package that doesn't actually exist (which means a bad actor can create that name later and take over anything that installs it). Made a free tool that scans your project or any GitHub repo and tells you what's broken, ranked by how bad, with the exact commands to fix it. https://github.com/ExecutiveKoder/sureguard-code-scanner submitted by /u/sks8100 [link] [comments]

shipped a tiny public CLAUDE.md to keep long AI coding agent sessions from rotting

honestly the failure mode i kept hitting is not dramatic. agent gets slower, noisier, less decisive. it keeps planning, it keeps explaining, it keeps checking, it stops shipping. so i wrote one file that targets that drift directly and i've been running it for thirty days on private repos before putting it out. it's just a CLAUDE.md you copy in. ask the agent to follow it before any long-running task. the rules are short: act over narrate, live evidence over stale memory, compact session state, memory events only if they change future behavior, hesitation as telemetry, recovery on restart without replaying everything, safety checks that don't become cages. not a framework. not a prompt pack. not a benchmark. mit, one file. repo: https://github.com/jaswalmohit8-collab/weasel discord: https://discord.gg/H78WYHYThY what's missing or overfit in your opinion? submitted by /u/Mother-Grapefruit-45 [link] [comments]

I packaged a Claude Code skill to Github that fixes the "go to sleep" nagging

Built a Claude Code skill last night that fixes two things that were bugging me. Problem: The nagging. "Time to rest, you've earned it." Claude has no idea what my energy state is and I hate it when it interrupts work to tell me to sleep at noon LOL Solution: This skill instructs Claude to ask you if you are ready for a break or if you want to keep going. It's nice to have the check in but this keeps the interaction a conversation instead of a command from Claude. Problem 2: I'm legit addicted to Claude Code and I really do need to take a break but I don't want to stop making progress. Solution: This skill pairs the ask with suggestions of what tasks it could knock out while you're away so it can keep working. Tasks suggested tend to be ones that require few permissions and will take a long time to execute. Further, it front-loads permission requests so it's more likely to get the job done without further interaction. Skill repo + permission cheat-sheet: https://github.com/TheTalentCat/sleep-solution.git PRs welcome on the cheat-sheet especially since it gets more useful the more edge cases it covers. submitted by /u/ScriptureSlayer [link] [comments]

GitHub’s Fake Engagement Problem Is Hiding in Plain Sight

Turns out: very visible. Yesterday's scan found 185 out of 185 engagers on a single repo were bots. Not 90%. Not "mostly suspicious". Every single one. The repo had zero legitimate stars. What I built phantomstars is a Python tool that runs daily via GitHub Actions (free, no servers): Scrapes GitHub Trending and searches for repos created in the last 7 days with sudden star spikes Pulls star and fork events from the last 24 hours per repo Bulk-fetches every engager's profile via the GraphQL API (account creation date, follower counts, repo history) Scores each account on a weighted model: account age (35%), profile completeness (30%), repo patterns (25%), activity history (10%) Detects coordinated campaigns using timestamp clustering and union-find: groups of 4+ suspicious accounts that engaged within a 3-hour window Files an issue directly on the targeted repo so the maintainer knows what's happening Campaign IDs are deterministic SHA-256 fingerprints of the sorted member set, so the same group of bots gets the same ID across runs. You can track a farm across multiple days even as individual accounts get suspended. What the pattern actually looks like It's remarkably consistent. A fake engagement campaign in the raw data: 40-200 accounts, all created within the same 1-2 week window Zero original repositories, or only forks they never touched No bio, no location, no followers, no following All of them starring the same repo within a 90-minute window The target repo usually has a name implying it's a tool, hack, executor, or generator Today's scan: 53 active campaigns across 3,560 accounts profiled. 798 classified as likely_fake. The repos being targeted are mostly low-quality AI tools and "executor" software that needs manufactured credibility fast. Notifying the affected repo When a repo hits a 40%+ fake engagement ratio or a campaign is detected, phantomstars opens an issue on that repo with the full suspect table: account logins, creation dates, composite scores, campaign membership. The maintainer sees it in their own issue tracker without having to find this project first. Worth noting: a lot of these repos have issues disabled, which is a red flag on its own. Those get skipped silently. Why I built this Stars are how developers decide what to evaluate, what to depend on, what to recommend. When that signal is bought, it affects real decisions downstream. This started as curiosity about how measurable the problem was. The answer was more measurable than I expected. It's part of broader research into AI slop distribution at JS Labs: https://labs.jamessawyer.co.uk/ai-slop-intelligence-dashboards/ The fake engagement problem and the AI content quality problem are really the same problem. Fake stars are the distribution layer that gets garbage in front of real users. All open source. The data is append-only JSONL committed back to the repo after every run, queryable with jq. Repo: https://github.com/tg12/phantomstars Findings are probabilistic, false positives exist, the README explains the full scoring model. If your account shows up and you're a real person, there's a false positive process. Questions welcome on the detection approach, GraphQL batching, or campaign ID stability. submitted by /u/SyntaxOfTheDamned [link] [comments]

Versioned humanity: existential risk with AI

Honestly I'd like you guys to check out my blog and share what you think. I'd appreciate the feedback, your opinions, thoughts, disagreements, are welcome. Hope you check it out, my first blog. https://ilovehumanity9.blogspot.com/2026/05/are-we-witnessing-end-of-humanity.html submitted by /u/Quiet-Nerd-5786 [link] [comments]