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Google AI AI

Google AI AI

Google AI AI

Google AI AI

Google AI AI

Google AI AI

Google AI AI

Google AI AI

Google AI AI

Google AI AI

Help Wanted: Opinions

Solo dev here. Building an AI companion that lives entirely on your device — no cloud, no account, no data ever leaving your phone. Coming soon to Google Play. Would love honest feedback. I genuinely just want opinions. It is not even available yet. I have been working on this for over a year. I am still building it. I started this project because a regular family budget like mine cannot just go out and purchase an AI companion robot. So I started with a cheap robot kit from Amazon — something my 9 year old son and I could build together. Then I thought... "What if I could give it a real brain?" I had an old Samsung Galaxy collecting dust and went to work. Scout is a calm AI companion that transforms an old phone into a friend. He listens, remembers, learns, and provides a warm family-safe presence — designed to feel less like an assistant and more like someone who is simply glad you are there. Everything runs offline. No account. No subscription. No data leaving your phone. Ever. I will need beta testers later — but right now I am just curious: What would make you look at something like this and think "that is actually kind of nice"? submitted by /u/CapeManCoral [link] [comments]

Massive Thank you to Claude AI

Don’t know if this is the right place but recently for my coursework, ( A Level NEA Computer Science) it suddenly disappeared from my google drive ( not sure if my ex revenge deleted it or my mum ). and i had no back ups because i never expected this. i mainly used ChatGPT back then but after 30 days the files get deleted from the chat. However, i pasted my whole write up to Claude including the code to it to check for minor improvements and 6 months later it is still there which saved me months of work. all i had to do was format it and 3 days later good as new. Im glad Claude AI doesn’t delete files sent, completely saved me big time it genuinely saved my uni offer. submitted by /u/Due-Plenty-8744 [link] [comments]

I used Claude Code to build a free Pokémon personality profiler from scratch in one session

Hey r/ClaudeAI, I built NotRandom (notrandom.vercel.app) a free web app where you type your favorite Pokémon and get a psychographic profile based on your choice. The premise: your favorite Pokémon is not random. It reveals something real about you. What it does: Fetches the Pokémon's types and Pokédex lore from PokéAPI Classifies it into one of 10 archetypes (The Sovereign, The Rebel, The Shadow Operator, The Jester...) Generates a Core Identity, Shadow Side, a unique nickname ("The Calculated Vanishing" for Greninja), and a one-liner "The Line" designed to feel uncomfortably accurate Lets you download a 1080x1080 shareable image card How Claude Code specifically built this: Everything was written by Claude Code in a single session. Here's what it actually did: Full architecture I described the concept, Claude Code planned the stack (React + Vite + Tailwind + Vercel serverless) and the complete file structure before writing a single line All React components from scratch LandingPage, LoadingScreen, ProfileCard, ShareCard, state machine in App.tsx The archetype system designed and coded the mapping of all 18 Pokémon types to 10 personality archetypes with color palettes per type The Claude Haiku prompt engineered to return a structured JSON with the right tone (intelligent, slightly poetic, never cringe) Solved a real architectural problem — the Anthropic API blocks direct browser calls (CORS). Claude Code diagnosed it, then created a Vercel serverless /api/profile route to proxy the call server-side Debugged the share card the downloaded image was black. Claude Code identified two causes: position: fixed breaks html-to-image's canvas renderer, and Google Fonts fail silently during capture. Fixed with skipFonts: true + sprite conversion to base64 before capture Full deployment Vercel config, environment variables, 30s timeout for cold starts I described what I wanted, Claude Code wrote the code, I tested, reported what broke, it fixed. Classic loop. https://preview.redd.it/i62hsrbd0n4h1.png?width=1080&format=png&auto=webp&s=aa31a839f094fa5760e401e8f336b01efbb49179 Free to use: https://notrandom.vercel.app no login, just type any Pokémon name in English (all 1025 are supported). submitted by /u/dyloum84 [link] [comments]

I stopped using Claude in the browser for 80% of my daily tasks and my usage actually went up

This is going to sound counterintuitive but let me explain. I love Claude. I use Opus for deep work, Sonnet for quick stuff. I was probably using claude 15 to 20 times a day. Summaries, brainstorming, code review, email drafts, research questions. Standard knowledge worker usage. But I noticed a pattern. Most of my usage happened in bursts. I would open Claude, do 4 or 5 things, then close it and not come back for 3 hours. Not because I did not need it, but because I forgot about it. I was deep in something else and the thought "I should ask Claude about this" did not occur to me in the moment. So I built a small thing. An agent that runs Claude Sonnet on the backend, connected to my calendar, todoist, email, and a few notion databases. It lives as a contact in my iMessage called "C" (very creative I know). Now instead of opening claude when I remember to, I text C throughout the day the same way I text anyone else. "What is on my calendar after 3pm." "Draft a reply to that email from alex, keep it short, say yes to the timeline." "Remind me to review the pitch deck before tomorrow's call." "What did I write in my product notes last week about the onboarding flow." My actual Claude usage went UP significantly. Not because the model got better but because the access point changed. Texting is a zero-friction action I already do 80 times a day. Opening a browser tab is a deliberate decision I have to remember to make. The deep work still happens in claude.ai. When I need the full context window, artifacts, file uploads, the browser is still better. But that is maybe 20% of my interactions. The other 80% are quick, context-specific queries that take 30 seconds and are perfectly suited to a text message. Stack: claude sonnet via API, a small express server for the tool integrations (google calendar, todoist, notion, gmail), photon codes for iMessage delivery, deployed on a $7 render instance. Langfuse for tracing when something goes weird. Total cost is about $35 a month in API calls which is less than what I was already spending on the Pro subscription that I still also have. The meta point: Claude is incredible. The browser is holding it back for most daily use cases. Not because the browser is bad but because it requires intent. The best AI interactions are the ones that happen when you barely think about it. submitted by /u/ScaryAd2555 [link] [comments]

You can chat with the AI in google search

Wow. Wow! Even the Ai can talk! submitted by /u/Proud-Environment754 [link] [comments]

Something I’ve been wondering lately

Big platforms are racing to integrate AI into everything. LinkedIn, Google, Microsoft and Meta they all want AI handling tasks, recommendations, outreach, content, and workflows. But the moment regular users try to use AI as a real assistant on those same platforms, it suddenly becomes a ToS issue. I’d love to use Claude as an actual personal assistant to manage emails, help with LinkedIn, handle routine web tasks but most sites seem designed to stop that from happening. When I tried giving Claude browser access, I spent more time worrying about account flags, automation detection, and unintended actions than I saved through automation. So how are people actually doing this? Are you avoiding sites like LinkedIn entirely? Only using AI for drafting and research? Or have you found a setup where you can genuinely delegate tasks without constantly supervising it? It feels like AI assistants are finally capable enough, but the platforms themselves don’t really want users having that level of automation. TL;DR: AI is being built into big platforms, but when users try to use it as a real assistant on those same platforms, it quickly runs into restrictions. Curious how people are actually working around that gap. submitted by /u/Litun1 [link] [comments]

My wife tried to log 1k phone-free hours but quit. So I vibe-coded an app

​This past summer, my wife set an audacious goal: she wanted to log 1,000 hours of phone-free time with our family. ​To track it, she’d put away her phone and start a manual timer. At first, it was great. But between managing two young kids and constantly forgetting to start or log the timers, the friction just became too much effort. After about 120 hours, she gave up. ​I wanted to find a way to handle the data collection for her so she could just focus on being present. The problem is, I’m a school teacher with a very limited, hobbyist programming background. I had never created anything close to a native Android app before. ​With all the recent talk around "vibe-coding" and AI agents, I figured I’d see if I could cobble a solution together. ​The result is Green Dot. It’s a native Android app built with Kotlin and Jetpack Compose. The core philosophy is pretty simple: not less phone, just better phone habits. Instead of being a punitive screen blocker, it tracks your long lock durations and rewards you for taking intentional, 1-hour breaks away from the device. ​The development process honestly went way beyond my expectations. I used VS Code (leveraging the education benefits) and did the vast majority of the heavy lifting using Claude Sonnet. After a couple of days of prompting and debugging, I had a working prototype. After about three weeks of working in my spare time, I had a fully functional app live on the Play Store. ​As someone without a formal CS background, it’s wild to me that these tools can democratize software development to this extent. It’s obviously not going to replace a software company, but it allowed a parent to ship a real, working tool over a few weekends to solve a hyper-specific lifestyle problem. ​My wife is back to tracking her hours, and I've shared it with a few friends and family who have found it useful for disconnecting. ​I’m sharing it here because I'd love to get the community's thoughts—both on the psychology of rewarding lock durations rather than locking users out, and on the technical side of spinning up a native mobile app from scratch using LLMs if you've done something similar. ​Play Store Link: https://play.google.com/store/apps/details?id=com.greendot.phonebreaks submitted by /u/starcraftgamerz77 [link] [comments]

How does AI help with Job productivity?

For Context: I work in a semiconductor manufacturing company as a modelling engineer, I use some modelling softwares etc but none of them use AI. I wanted to understand the whole AI craze nowadays, people say that AI will replace jobs/Increase productivity and I don't get it at all. All I see is a simple chatbot (ChatGPT) which is a super impressive version of google and can solve some basic math/science questions and Co-Pilot in my workplace which I found to be useless, for example the facilitator thing which is supposed to make meeting notes is so bad at summaring meeting minutes etc. I don't think AI is there yet to do very basic things. So yes in theory if AI gets better in few years/decades sure it take the non-technical part of my job like making meeting minutes/making ppt's etc but I think its still not there yet. For AI to take over my job it needs to get the basic shit correct first and then maybe it can do the technical stuff. One really good use-case of AI that i can see is to generate Code based on the project requirement, So I can see how entry level coder's jobs might be affected sure, but that's a very small portion of the economy, right? submitted by /u/the_axe_effect [link] [comments]

Google’s AI mode is threatening me… i was just trying to look up a family guy clip…

submitted by /u/Early_Mail9268 [link] [comments]

Claude Cowork & Meta/Google Ads

Somewhat new to AI. I’ve been working on Cowork the last few weeks on my wife’s wedding photography business. Her old website was a slightly modified Squarespace template that was out of date, terrible seo, no AEO, and just, needed to go. She worked with a branding company and has a great brand, fonts/colors/styling, and I fed that to a project and have been working on a full redesign on Wordpress that is almost ready to launch. Fully SEO/AEO optimized and all that. Now I’ve had Cowork (in the same project) help me plan a marketing launch for the new site, and addition to a content plan for organic posts, we’ve built out a $30/day paid ads plan for Meta/Google. Has anyone got connected to Google and/or Meta through Cowork? I know Meta has an MCP Server but haven’t dove into that yet. I want something that from my Claude Cowork project, I can ask it how the ads are performing relative to our plan, create/edit campaigns and ads, and adjust as needed according to the plan. submitted by /u/johnnyglass [link] [comments]

I built a full app with Lovable + Claude + Gemini and it has 100+ real users. Here's what actually worked.

I'm a software engineer but never had a fullstack/frontend development experience . I wanted something on the internet I could call mine, so I built Earnest — a free app that helps people track bank account bonuses (open account, meet requirements, collect bonus, close it, repeat). The stack: Lovable for the UI and scaffolding, Claude + Gemini with Google Antigravity to make complex parts work. What surprised me: - Lovable got me from 0 to something real embarrassingly fast - Claude was much better at understanding *intent* when I described the full user flow instead of individual features - Gemini was useful as a second opinion when I was stuck - The hardest part wasn't the AI — it was knowing what to ask for Where it landed: 19+ active promotions, $9,700+ in available bonuses tracked, 100+ users, $5,000+ in bonuses earned by users so far. App: earnest.lovable.app Happy to share more about the build process — what prompts worked, what completely failed, how I debugged without being able to read the code properly. submitted by /u/Any-Constant [link] [comments]

Becoming a power user

Hi all, I use Claude across both personal (free tier) and work (enterprise) as a thinking partner for reasoning and research. I have a technical but mostly customer-facing role, and I can code at a basic level. I’ve been following the AI space pretty closely for about a year now, but I feel like I’m still scratching the surface of what’s actually possible. What finally unlocked AI as a genuine tool for you and not just a smarter Google search? Prompting habits, specific use cases, workflows? Big or small, I’d take any tips. submitted by /u/jkwnbn [link] [comments]

Looking for vibe-research collaborators on “One-pass context-to-weight consolidation”

I’m a software engineer and AI enthusiast who wants to get involved with AI research, but I don’t have the full requisite math, ML coding chops, or compute needed to do typical research. I’m writing this post because I assume there are many other sub members in my boat, and i think i have a meaningful research problem with a shape that allows people like me to make progress. I explain the problem and why it’s tractable by people like this at length in the google doc linked in the comment of this post, but in essence: I believe there’s a chance there’s some mathematical rule that allows you to cheaply imbue the in-context understanding a model gains directly into its weights. IF a rule like this existed, then checking if you’ve found it requires very little compute. The core loop requires running the input token forward passes of a model large enough to learn in context (for reference, a 1 billion parameter model can do this and runs on a mac book pro), apply this rule (which, by the hypothesized construction of where in the solution space we’re looking, is computationally cheap), then quiz the model without the context on what it demonstrably knew in context / run regression benchmarks to make sure the application of the rule didn’t damage the model’s other capabilities. Although checking if you’ve found this rule is computationally cheap, proposing and implementing candidate rules is very difficult. It requires diverse mathematical and machine learning expertise, along with the scientific rigor to guide the search process. Up until now, there were very few people with access to those abilities. However, this is changing with modern frontier models. OpenAI and Anthropic both have soon to be released models capable of valuable mathematical work (re the erdos unit distance problem solved by the internal OpenAI model and Mythos). My proposal is to form a research community of “citizen scientists” to make progress on this problem. It’s possible the solution doesn’t exist, or is so incredibly complicated that modern frontier models have no hope of solving it. But, my argument is that for the first time, the solution is plausibly within reach of model capabilities. This, in combination with the immense upside of LLMs being able to cheaply learn from experience, makes researching it very high expected value. Participating in this community would involve sharing results, progress, benchmarks, and research insights. To productively contribute, rough requirements are: a 200 tier AI subscription a computer ~ as capable as a mac book pro M3 chip / willingness to pay 10 bucks a day for the cloud compute, A working knowledge of how LLMs function and the field of AI / cognitive science. submitted by /u/Independent-Soft2330 [link] [comments]

Cave Prompt: Making AI understand your requirements better

[Showcase] Cave Prompt — A Semantic Prompt Compiler for Claude Code 👉 Check out the repo here: Link Have you ever written a detailed request, sent it to an AI, and gotten an answer that was technically correct but completely missed the point? The AI isn't the problem—it's the "noise" in your prompt. Key constraints get buried at the end, or the core intent gets lost in conversational filler. Cave Prompt is a compiler skill that runs before your AI processes your request. It extracts your true intent, surfaces hidden requirements, resolves conflicting constraints, and restructures everything into a high-density execution prompt—so the AI works on what you actually need, not just what you literally said. Key Advantages: Attention front-loading: Critical constraints go first, where the model weighs them most heavily. Hidden requirement extraction: Finds what you didn't explicitly say but genuinely need. Constraint conflict resolution: Catches contradictions before the AI goes in the wrong direction. Vague → specific: Transforms fuzzy ideas (e.g., "track my finances") into structured specs (e.g., "a 3-sheet Google Sheets dashboard with SKU-level margin tracking"). Who is this for? Non-technical users: Those who describe things conversationally and aren't sure how to structure a prompt. Product managers & business owners: Anyone who knows what they want but struggles to translate it into precise AI instructions. High-stakes tasks: Anyone where a misread from the AI would cost real time or money. Teams: For standardizing prompt quality across members with different communication styles. When to use it: Use it for long, multi-constraint requests where clarity matters. Skip it for simple, single-intent prompts—the overhead isn't worth it there. This is my first skill build, so there may be rough edges—I truly appreciate your patience and any feedback you might have! As a developer, I’m putting a lot of heart into this project. A ⭐ on the repo would be a huge boost for my work and personal growth—it really motivates me to keep building and improving. If you find the idea useful, I’d be incredibly grateful for the support. Thanks for reading and for helping me grow! 🙏 submitted by /u/hieudeptrai1962000 [link] [comments]

From Making $200 to $20K/Month Offering Free Website Drafts

So I’m writing this for anyone running a web agency who’s struggling to get consistent clients or build scalable systems. I understand how stressful it can be because I was in the exact same position. I’ve been running my web agency for 4 years, but only in the last year did I start using AI seriously, and honestly it changed everything for me. I used to build websites on WordPress and do all my outreach manually. It worked, but it was inconsistent and exhausting. Once I started implementing AI into my business, I went from constantly chasing clients to doing around $20k/month recurring. This is basically what changed for me. At first I was targeting businesses with no websites, but switching to businesses that already had websites worked way better. There are SO many businesses with outdated websites that clearly need upgrading. Plus, these business owners already understand the value of having a website because they’ve already paid for one before. It’s way easier convincing someone to improve something they already believe in than trying to convince someone from zero. The second big shift was moving from manual outreach to automated email outreach that actually feels personalized. Instead of sending generic emails, I now use a tool that mass analyzes a business’s website and generates personalized outreach based on things like design issues, SEO problems, site speed, mobile optimization, and overall user experience. The third thing that changed everything was offering a free redesigned draft version of their current website. Realistically, who says no to free? I can build these drafts really quickly using Claude Code, and most of the time they already look way more modern than the client’s existing site. Once business owners see a better version of their own company in front of them, selling becomes way easier. Another huge mistake I used to make was just sending preview links through email. They open it later when they’re busy, nobody’s there to explain the improvements properly, and eventually the lead goes cold. Now I always present the website live on Google Meet and try to close them on the spot. That alone massively increased my close rate. Also, always charge upfront for the website build, but don’t ignore monthly recurring revenue. Hosting, maintenance, edits, SEO, ongoing changes, etc. That’s where stability comes from if you actually want predictable income every month instead of constantly hunting for new clients. For anyone curious about the tools I use, it’s honestly pretty simple. Apollo for finding leads because you basically never run out of businesses to contact. Swokei for outreach. I upload my lead list there and it analyzes each business website, scores it, and turns flaws in design, SEO, speed, and mobile optimization into personalized outreach emails automatically. Pointing out actual issues on their website increased my reply rates massively. Claude Code for building websites. And honestly, people saying AI built websites don’t perform well are just wrong. If you know what you’re doing, you can build pretty much anything now. And Cloudflare for hosting client websites. That’s pretty much the system I run now. submitted by /u/Murky_Explanation_73 [link] [comments]