Seamless.AI

Seamless.AI AI

Seamless.AI AI

Seamless.AI AI

Seamless.AI AI

Seamless.AI AI

Seamless.AI AI

Seamless.AI AI

Seamless.AI AI

Seamless.AI AI

Seamless.AI AI

How to automate Canva 4-page editable templates for Etsy using Claude AI?

Hello, fellow Claude experts! A quick question, how can I automate the creation of flyers for weddings, funerals, etc.? They are usually 4 pages and need to be fully editable in Canva. I've been trying to create them using the Canva connector in the Claude app itself, but it never produces what I need no matter how detailed the prompt is. By any chance anyone have an idea how to create these flyers seamlessly using AI? So far it looks like the only option is to do this job manually. Here an example for a flyer : LINK Yes, I am creating an Etsy store selling invitation cards. 😊 Thank you for your help! submitted by /u/Illustrious-Heat-571 [link] [comments]

Claude code Plugin - Makes your AI coding agent talk and think like Rocky, the Eridian engineer from Andy Weir's Project Hail Mary.

Hey, If you're tired of bland AI responses and want your coding sessions to feel like chatting with an Eridian buddy from Project Hail Mary, check out Rocky – the new output style plugin that's taking Claude Code to interstellar levels. What is Rocky? Rocky transforms Claude (and other coding agents) into "Rocky Mode" – a fun, alien-inspired personality inspired by the book's genius engineer Rocky. It adds quirky Eridian flair to code explanations, debugging, and more, without sacrificing accuracy. Perfect for making complex coding fun! Key Features Three Modes: Rocky Talk - your agent talks like rocky (plans, implementation are not effected) Full Rocky - your agent talks + thinks like rocky as engineer Rocky Buddy - you get your own rocky buddy as an ascii character Claude Code Native: Easy install as a plugin via .claude-plugin/plugin.json – works seamlessly with skills, agents, and hooks. Universal Compatibility: Built for Claude Code but adaptable to other coding agents. Lightweight & Fun: No bloat – just personality boosts for better engagement during long code sessions. Full docs in README: https://github.com/vikxlp/rocky/blob/main/README.md Feedback & ideas are welcome! Drop a comment 🌌 #ClaudeCode #AIPersonality #ProjectHailMary submitted by /u/vikalp02 [link] [comments]

I used Claude Code to build a portable AI worker Desktop from scratch — the open-source community gave it 391 stars in 6 days

I want to share something I built with Claude Code over the past week because it shows what AI-assisted development can actually do when pointed at a genuinely hard problem: moving AI agents beyond one-off task execution. Most AI wrappers just send prompts to an API. Building a continuously operating AI worker requires queueing, harness integration, and MCP orchestration. I wanted a way to make AI worker environments fully portable. No widely adopted solution had cleanly solved the "how do we package the context, tools, and skills so anyone can run it locally" problem effectively. What Claude Code did: I pointed Claude (Opus 4.6 - high thinking) at the architecture design for Holaboss, an AI Worker Desktop. Claude helped me build a three-layer system separating the Electron desktop UI, the TypeScript-based runtime system, and the sandbox root. It understood how to implement the memory catalog metadata, helped me write the compaction boundary logic for session continuity, and worked through the MCP orchestration so workspace skills could be merged with embedded runtime skills seamlessly. The result is a fully portable runtime. Your AI workers, along with their context and tools, can be packaged and shared. It's free, open-source (MIT), and runs locally with Node.js (desktop + runtime bundle). It supports OpenAI, Anthropic, OpenRouter, Gemini, and Ollama out of the box. I open-sourced this a few days ago and the reaction has been unreal. The GitHub repo hit 391 stars in just 6 days. The community is already building on top of the 4 built-in worker templates (Social Operator, Gmail Assistant, Build in Public, and Starter Workspace). This was so far from the typical "I used AI to write a to-do app." This was Claude Code helping architect a real, local, three-tier desktop and runtime system for autonomous AI workers. And people are running it on their Macs right now (Windows & Linux in progress). I truly still can't believe it. The GitHub repo is public if you want to try it or build your own worker. GitHub ⭐️: https://github.com/holaboss-ai/holaboss-ai submitted by /u/Imaginary-Tax2075 [link] [comments]

personas: a simple plugin framework for helpful assistants using native claude stuff (we have OpenClaw at home)

Hey y'all. I am writing this post myself! Not AI! Enjoy real humanity complete with all its flaws and imperfections. <3 I have been working as a web developer for many years but I have never shared any open source stuff and I am a bit shy about it so take it easy on me. Although, this isn't really my own project as much as a repackaging of Anthropic's work so maybe that makes it a bit easier. Ever since I started building things with generative AI, my goal was to create helpful assistants with useful persistence that could utilize tools to help organize and improve my life. For a long time the results were disappointing — tool usage sucked, context got polluted easily, memory often felt more harmful than helpful, browser usage was a total waste of time and tokens. But one by one, I noticed these issues being solved, and after being introduced to Claude Code for my work, I began trying to make the most of Anthropic's products for my day to day life. You can actually get very far with Claude Desktop, projects, and of course now skills and CoWork and whatever other 12 new features they release this week! The convenience of the desktop and mobile apps are really a big factor for personal assistant usage. However, I was always finding new things I wanted to do that were out of reach (remote deployment, always on, A2A relays, etc). So, I began to try to use Claude Code for some personal assistant tasks and of course, it is highly effective for that. But I did run into a few small things I thought I could plan out and improve upon, and I had some very specific ideas about how that would look: Core Decisions What I didn't want to make was what I see shared a lot - a hugely complicated and customized system built on top of some questionable practices for interacting with Claude Code or the Anthropic API. Anthropic moves so fast, and has such a rich and extensible feature set built in to Claude Code, I decided to try to work within their ecosystem as much as possible. That has really paid off so far in the few months of using and testing personas myself. Most every new feature they ship has been a seamless improvement that just worked from day one - the enhanced memory, remote control, and now browser and computer usage as well. This also means if you use Claude Code or CoWork, you already have everything you need, and getting started is as simple as adding the plugin marketplace. I also had a few other requirements: Isolated — I, like many of you, have a complex setup of skills, behaviors, etc for Claude Code that are not helpful for a personal assistant, and these personas needed to be isolated from that context. Sandboxed — I want to be able to skip permissions and not worry about them waiting for me, but I also want to keep my system32 file intact. Self-contained — I don't want them saving memory to some other folder on my PC, everything should be self-contained for easy storage. Git controlled — I want to be able to easily back up each persona in its entirety using Git/GitHub. Luckily, after spending approximately 200 hours browsing the Anthropic documentation sites, it turns out you can do all of this natively with a bit of knowledge and time to set it up. personas Essentially, each persona is just a folder: ``` ~/.personas/warren/ ├── CLAUDE.md# what the persona does, knows, and how it behaves ├── .claude/ │ ├── settings.json # sandbox, permissions, memory config │ ├── output-styles/ # personality and tone (replaces default Claude prompt) │ └── hooks/ │ └── public-repo-guard.sh # blocks personal data leaks in public repos ├── hooks.json # session lifecycle: start, stop, compaction, git guard ├── docs/ # reference materials, plans, domain knowledge ├── skills/ # reusable workflows (self-improve ships with every persona) ├── tools/ # scripts, utilities, data pipelines ├── user/ │ ├── profile.md# your personal context (filled during first session) │ └── memory/ # native auto-memory (local, git-tracked) ├── .mcp.json # MCP server connections (gitignored) ├── .claude-flags # per-persona launch flags └── .gitignore # protects secrets; optionally ignores user/ for public sharing ``` This folder can be deployed remotely, saved to the cloud, put up on GitHub privately or publicly. If possible, each persona is sandboxed at the OS level (bubblewrap on Linux, Seatbelt on macOS) - they can only read/write their own directory. Setup is just a Claude plugin. You install it, run the skill and describe the persona you want, and persona-dev scaffolds everything. It researches your domain, recommends helpful tools, sets up sandboxing, and walks you through configuration (in theory as long as I haven't broken anything). To interact with your persona: You can open it in Cowork, launch Claude Code from the folder, or use the persona name alias which should be created on setup if able. On first launch, the persona interviews you to build your profile. After that, it reads your profile and m

Aren't they overdoing it?

I really like the generative UI and I think it has great applications, but this is pointless. I asked for "text" and yet I got this. Not only is it pointless but it's more tokens and compute to something that didn't need it. To be fair I only had this happen a few times and every time it has been with Sonnet 4.6 w/ extended thinking off, but still. submitted by /u/Educational-Nebula50 [link] [comments]

Built Something. Break It. (Open Source)

Quantalang is a systems programming language with algebraic effects, designed for game engines and GPU shaders. One language for your engine code and your shaders: write a function once, compile it to CPU for testing and GPU for rendering. My initial idea began out of curiosity - I was hoping to improve performance on DirectX11 games that rely entirely on a single-thread, such as heavily modified versions of Skyrim. My goal was to write a compiling language that allows for the reduction of both CPU and GPU overhead (hopefully) by only writing and compiling the code once to both simultaneously. This language speaks to the CPU and the GPU simultaneously and translates between the two seamlessly. The other projects are either to support and expand both Quantalang and Quanta Universe - which will be dedicated to rendering, mathematics, color, and shaders. Calibrate Pro is a monitor calibration tool that is eventually going to replace (hopefully) DisplayCAL, ArgyllCMS, and override all windows color profile management to function across all applications without issue. The tool also generates every form of Lookup Table you may need for your intended skill, tool, or task. I am still testing system wide 3D LUT support. It also supports instrument based calibration in SDR and HDR color spaces I did rely on an LLM to help me program these tools, and I recognize the risks, and ethical concerns that come with AI from many fields and specializations. I also want to be clear that this was not an evening or weekend project. This is close to 2 and a half months of time spent *working* on the project - however, I do encourage taking a look. https://github.com/HarperZ9/quantalang 100% of this was done by claude code with verbal guidance ||| QuantaLang — The Effects Language. Multi-backend compiler for graphics, shaders, and systems programming. ||| https://github.com/HarperZ9/quanta-universe 100% of this was done by claude code with verbal guidance ||| Physics-inspired software ecosystem: 43 modules spanning rendering, trading, AI, color science, and developer tools — powered by QuantaLang ||| https://github.com/HarperZ9/quanta-color 100% of this was done with claude code using verbal guidance ||| Professional color science library — 15 color spaces, 12 tone mappers, CIECAM02/CAM16, spectral rendering, PyQt6 GUI ||| https://github.com/HarperZ9/calibrate-pro and last but not least, 100% of this was done by claude code using verbal guidance. ||| Professional sensorless display calibration (sensorless calibration is perhaps not happening, however a system wide color management, and calibration tool. — 58-panel database, DDC/CI, 3D LUT, ICC profiles, PyQt6 GUI ||| submitted by /u/MeAndClaudeMakeHeat [link] [comments]

I built a pet care app with Claude Code that connects to Claude via MCP here's the full appointment booking flow

Over the past few weeks, I built petclaw.app, a comprehensive pet care platform designed to replace tedious forms and screens with a seamless, conversational interface powered by Claude and the Model Context Protocol (MCP). By leveraging Claude Code to write the vast majority of the codebase—including a custom MCP server with 15 specialized tools, a Supabase schema, and a Google Calendar integration—I’ve created a system where users can simply say, "Book Mx a grooming appointment next Monday at noon near me," and the AI handles everything from location-based searching to calendar syncing and profile updates. The technical heavy lifting centered on refining MCP tool descriptions to ensure Claude could reliably resolve pet IDs, validate complex data, and follow step-by-step error handling. Built on a stack of Next.js, Supabase, and Gemini for health scoring, petclaw.app offers everything from natural language health logging and behavior scoring to expense tracking and document storage, proving that the future of pet management is a single, intelligent conversation. submitted by /u/LemonTrue9435 [link] [comments]

How to Stop AI from Killing Your Critical Thinking

Last week, I watched this TED talk by Advait Sarkar called: How to Stop AI from Killing Your Critical Thinking. Basically, text engagement has become extremely passive with the advent of AI summarizers and our weakening attention spans. Sarkar and his Oxford team (AI and design researchers) showed me a slightly different paradigm. Instead of chatbots delivering ready-made answers, AI is used to force deeper reading. Their goal was to make text engagement more difficult, challenging, and productive because research shows critical thinking tends to go down with increased AI usage; this design is meant to reverse that trend. I love hearing how tools can help me think deeper and better. AI doesn't have the same biases as humans, like confirmation bias, cognitive dissonance, or recency bias. They can provide alternative framings of problems, provide counterarguments to initial assumptions, and provide information re-organization to highlight logical gaps. When I saw the way Sarkar is using AI to increase the cognitive demand of reading, I started wishing I could have the same app shown in the talk (@8:13). So, I worked with Claude to build a version of it, and it basically one-shotted the damn whole thing! Meanwhile, I was watchingJeff Kaplan’s podcast on Lex Fridman and was inspired again. I asked Claude to make reading more like World of Warcraft, and it created an incentive-based quest/tracker system. Combining these two design philosophies into one app, I've been reading so much more, and the depth of reading is so much greater. It feels different from a book or as screen, it feels... more "engaging". It's more dopamine-maxxed for a lack of a better term. Some of the nuggets it's been surfacing have been very delightful, while the "provocations" (a term Sarkar uses) make me question my own assumptions as I read and take notes. This means there's intrinsic motivation from just reading along with AI support, rather than without. Seriously, try building this app yourself, the result is fantastic. I'm not going to give you some prompt or github link, you'll find your own design philosophy emerging, and that's the reward (IMO). So, now I keep taking lessons from different design philosophies, and Claude just somehow merges everything seamlessly together. It's unreal. I feel like this type of design is making me a better reader and writer, and connecting ideas while feeling that "productive cognitive load." I'm still looking for more design-inspiration and curious what others are doing to design "non-chat-bot" AI interfaces? Links appreciated, that way I can see how I can incorporate the philosophy into the design. submitted by /u/handsnerfin [link] [comments]

[Showcase] I'm a 40yo self-taught dev. I built a Multi-Model AI Bridge (TUI + Flutter App) using a Dart Monorepo.

Hey everyone, 6 years ago I started coding with Python and CSV files for a local shop. For the past few months, I've been acting as an "AI Orchestrator" (I design the logic and architecture, AI writes the code) to build Infinity CLI. It's a Full-Stack Dart ecosystem that turns your Android phone into a universal remote for your PC terminal, creating a seamless bridge with different AI agents. Under the hood: The Stack: Interactive TUI (PC) + Native Flutter App (Android). Low-Latency Bridge: I used Firebase RTDB to stream chunks in real-time between devices. Sentence-Level Chunking: Instead of standard token streaming (which causes UI flickering), the system accumulates chunks and streams full sentences for a much cleaner UX. Multi-Backend: Clean subprocess lifecycle management allows real-time swapping between Claude 4.6 Sonnet and Gemini 3.1 Pro directly from the app. The goal was to build a fluid ecosystem: your terminal, right in the palm of your hand. Would love to hear your thoughts on the Dart Monorepo approach and the overall architecture! (Turn on audio for the synthwave track on the video 🎧) submitted by /u/Rapsody-Dev [link] [comments]

I built a full-stack serverless AI agent platform on AWS in 29 hours using Claude Code — here's the entire journey as a tutorial

TL;DR: Built a complete AWS serverless platform that runs AI agents for ~$0.01/month — entirely through conversational prompts to Claude Code over 5 weeks. Documented every prompt, failure, and fix as a 7-chapter vibe coding tutorial. GitHub repo. What I built Serverless OpenClaw runs the OpenClaw AI agent on-demand on AWS — with a React web chat UI and Telegram bot. The entire infrastructure deploys with a single cdk deploy. The twist: every line of code was written through Claude Code conversations. No manual coding — just prompts, reviews, and course corrections. The numbers Metric Value Development time ~29 hours across 5 weeks Total AWS cost ~$0.25 during development Monthly running cost ~$0.01 (Lambda) Unit tests 233 E2E tests 35 CDK stacks 8 TypeScript packages 6 (monorepo) Cold start 1.35s (Lambda), 0.12s warm The cost journey This was the most fun part. Claude Code helped me eliminate every expensive AWS component one by one: What we eliminated Savings NAT Gateway -$32/month ALB (Application Load Balancer) -$18/month Fargate always-on -$15/month Interface VPC Endpoints -$7/month each Provisioned DynamoDB Variable Result: From a typical ~$70+/month serverless setup down to $0.01/month on Lambda with zero idle costs. Fargate Spot is available as a fallback for long-running tasks. How Claude Code was used This wasn't "generate a function" — it was full architecture sessions: Architecture design: "Design a serverless platform that costs under $1/month" → Claude Code produced the PRD, CDK stacks, network design TDD workflow: Claude Code wrote tests first, then implementation. 233 tests before a single deploy Debugging sessions: Docker build failures, cold start optimization (68s → 1.35s), WebSocket auth issues — all solved conversationally Phase 2 migration: Moved from Fargate to Lambda Container Image mid-project. Claude Code handled the entire migration including S3 session persistence and smart routing The prompts were originally in Korean, and Claude Code handled bilingual development seamlessly. Vibe Coding Tutorial (7 chapters) I reconstructed the entire journey from Claude Code conversation logs into a step-by-step tutorial: # Chapter Time Key Topics 1 The $1/Month Challenge ~2h PRD, architecture design, cost analysis 2 MVP in a Weekend ~8h 10-step Phase 1, CDK stacks, TDD 3 Deployment Reality Check ~4h Docker, secrets, auth, first real deploy 4 The Cold Start Battle ~6h Docker optimization, CPU tuning, pre-warming 5 Lambda Migration ~4h Phase 2, embedded agent, S3 sessions 6 Smart Routing ~3h Lambda/Fargate hybrid, cold start preview 7 Release Automation ~2h Skills, parallel review, GitHub releases Each chapter includes: the actual prompt given → what Claude Code did → what broke → how we fixed it → lessons learned → reproducible commands. Start the tutorial here → Tech stack TypeScript monorepo (6 packages) on AWS: CDK for IaC, API Gateway (WebSocket + REST), Lambda + Fargate Spot for compute, DynamoDB, S3, Cognito auth, CloudFront + React SPA, Telegram Bot API. Multi-LLM support via Anthropic API and Amazon Bedrock. Patterns you can steal API Gateway instead of ALB — Saves $18+/month. WebSocket + REST on API Gateway with Lambda handlers Public subnet Fargate (no NAT) — $0 networking cost. Security via 6-layer defense (SG + Bearer token + TLS + localhost + non-root + SSM) Lambda Container Image for agents — Zero idle cost, 1.35s cold start. S3 session persistence for context continuity Smart routing — Lambda for quick tasks, Fargate for heavy work, automatic fallback between them Cold start message queuing — Messages during container startup stored in DynamoDB, consumed when ready (5-min TTL) The repo is MIT licensed and PRs are welcome. Happy to answer questions about any of the architecture decisions, cost optimization tricks, or how to structure long Claude Code sessions for infrastructure projects. GitHub | Tutorial submitted by /u/Consistent-Milk-6643 [link] [comments]

Feature Request: True Inline Diff View (like Cascade in W!ndsurf) for the Codex Extension

Hi everyone =) Is there any timeline for bringing a true native inline diff view to the Codex extension (other words: in main code-edit-workflow)? Currently, reviewing AI-generated code modifications in Codex relies heavily on the chat preview panel or a separate full-screen split diff window. This UI approach requires constant user context switching, boring diff-search etc. What would massively improve the workflow is the seamless inline experience currently used by Winds*rf Cascade: * Red (deleted) and green (added) background highlighting directly in the main editor window - not (just) in chatwindow * Code Lens "Accept" and "Reject" buttons injected immediately above the modified lines. (+Arrows) Like in another Agents (AG Gem.Code.Assist, or C*rsor, W*ndsurf Cascade, etc) * Zero need to move focus away from the active file during the review process. Does anyone know if this specific in-editor diff UI is on the roadmap? Are there any workarounds or experimental settings to enable this behavior right now? Thanks! submitted by /u/Level-Statement79 [link] [comments]

The new Sora API extension update has confusing pricing. Extensions re-bill the entire clip

Sooooo I wanted to test the updated Video and Sora 2 API updates and features that OpenAI released yesterday, which includes a new “edit” function replacing the remix function so that it now matches the same function on the app, a new character saving feature for objects, items, or non human character (basically like Cameos on the app now but no human characters yet), and then my most awaited feature which is the ability now to extend API Sora 2 gens. BUT! Here’s the kicker. And I learned this the hard way so you don’t have to bahaha. The new extension pricing is absolutely cooked atm. And it hasn’t even been adequately communicated properly in the updated documentation, so it feels a bit shady imo. In essence, let’s say you generate an 8 second Sora 2 clip and you pay $0.8 - which is the normal 10 cents per second price. Then, you want to extend that clip another 12 seconds. So most would assume that you’d be at 20 seconds all up, so $2 in total right? Nope. You get charged $0.8 for the first 8 secs, then you get charged an ADDITIONAL $2 for the 12 second extension. Because they currently are re-billing you for the previously generated 8 seconds. So I made the error in my new Sora 2 web app of pressing gen on an extend, it got stuck, I pressed it again, and suddenly I had 2 of the same gens running both bringing the same video to 32 seconds, so I got charged an additional $6.40 💀. My recommendation is if you want to test it and save money in the process, generate a long first clip ie like 16 or 20 seconds. That way, it will cost either $1.60 or $2 straight up - and then if you do want to extend, go for another 16 or 20 second extension. You will still pay extra, but if you mess with like 4/8/12 second gens with multiple extensions, you just end up paying like double/triple the usual price and it’s a big waste of money. Anyway, I thought I’d share for discussions sake and to inform people before they get too excited lol. It is still amazing to have, but I wish the pricing would be more clear and transparently presented on the API documentation. And I hope OpenAI will alter how they charge for extensions because imo it seems unreasonable to charge you twice for something you’ve already generated, just to be able to extend/stitch it together. Especially when extensions are still unreliable. I’d still say only 60-70% of them are coming out mostly seamless, with others having glitches as it extends. What do you guys think about the new updates? Anything you’d like to see in the future? submitted by /u/indiegameplus [link] [comments]

GPT-5.4 vs Opus 4.6 for full-stack dev: why does GPT struggle with frontend?

So I was trying to build a SaaS application with the help of Codex and GPT-5.4, thinking set as high, but what I've seen is that GPT-5.4 really struggles a lot with UI and frontend optimization. Comparing it with Opus 4.6 / Sonnet 4.5, the UIs and the frontend is generally an afterthought, and even when it comes to backend integration with frontend, it feels very lagging. There are so many frontend issues that are not appropriately taken care of, despite using a huge number of relevant agent skills. The UI is laggy, the performance is absolutely atrocious, and then so many of the functionalities are buggy; they are not working completely. https://preview.redd.it/uwdnpuz8thog1.png?width=2142&format=png&auto=webp&s=04f31e5d8d59c8b2a2dbd05037ed452a1b378ec5 What I've seen is that it is clearly far behind Opus 4.6. With Opus 4.6, you could one-shot the frontend with backend integration and it will work out of the box. But in order to make it work with GPT-5.4, you have go multiple times back and forth. When it is a pure backend / CLI task, it is typically a one shot and it works perfectly. But frontend and full stack tasks involving frontend integration has been really bad. Do folks have suggestions and how we could improve the overall experience of using GPT-5.4 for front end and full stack integrations. https://preview.redd.it/w48uzezcthog1.png?width=3908&format=png&auto=webp&s=401d33817c24ae4bb6ca832aaa4e01401b05e4f9 submitted by /u/Creepy-Row970 [link] [comments]

Just Launched: SoulPrint Beta - Redefining AI Partnership

I'm excited to share that we've just launched the SoulPrintEngine.ai Beta! This isn't just another AI tool, it's a strategic partner that evolves with you. Our Dynamic Intelligence Search Engine remembers your patterns, learns your workflow, and adapts seamlessly. We're moving beyond static prompts to create a continuous, intelligent collaboration. It's about building a partnership where AI doesn't just follow commands but understands context. What features are missing from ChatGPT that you'd like to have? submitted by /u/Prestigious-Dig2263 [link] [comments]