Canva AI

Canva AI AI

Canva AI AI

Canva AI AI

Canva AI AI

Canva AI AI

Canva AI AI

Canva AI AI

Canva AI AI

Canva AI AI

Canva AI AI

The hidden overhead that most 'make money with AI' guides never mention

Most guides listing AI income opportunities do not mention what it costs to run the recommended tools every month. Here is the honest overhead picture for a beginner: ChatGPT Plus: $20 per month A voice or audio AI tool: $29 to $69 per month Canva Pro: $15 per month Cold outreach or email tool: $20 to $40 per month Domain and basic landing page: $10 to $20 per month Sign up for everything commonly recommended and you are spending $100 to $165 per month before earning a dollar. A lot of beginners do exactly this. Three things that actually change the math: Start with free versions only. ChatGPT's free tier, free Canva, Google Docs. LinkedIn ghostwriting, email sequence writing, and basic content work can all be done this way. There is no beginner service that strictly requires paid tools in month one. Let clients fund your tool upgrades. If a project genuinely requires a paid tool, charge enough to cover it. Do not pay $30 to $50 per month for a tool you are speculating might win you clients. Pay for it after the first client confirms they need it. Track margin per service, not just total income. Earning $300 a month while spending $160 on tools is a $140 result. Some AI services have tighter margins than the surface numbers suggest. Ghostwriting and email writing have almost no tool cost. Video production and voice work carry more overhead. The services with the best margin-to-effort ratio for beginners tend to be: LinkedIn ghostwriting, email sequences, and custom GPT setup for small businesses. All of them run on ChatGPT Plus alone. This is not complicated. It just never shows up in the posts about how much you can make. submitted by /u/Street-Gate7322 [link] [comments]

Please Keep Canvas!!!

As a ChatGPT Pro user, Canvas has been one of the most useful parts of ChatGPT for me, especially for business writing for blogs, proposals, specifications, instructional emails, and more! Anything I need to gather my thoughts together on works great in Canvas and saves me time. What made it so valuable was having my document open in an editor while ChatGPT sat beside it like a real editing partner. I could ask questions about structure, tone, or wording before changing anything, think through the response, and then decide what to do. Even better, I would have it reference meeting transcripts and process flows stored in the project and I could ask it to reference this while I develop the document. The inline editor is not the same. It feels slower, more awkward, and much less flexible. I can't ask it's opinion or to look something up - it just acts on my question before I can determine the best approach to write about. Yesterday, I finished a 30-page proposal using Canvas, and losing that workflow is honestly really disappointing. (Not to mention I had trouble polishing the proposal up this morning). I have tried the models available to me, and it seems to be gone in the places where I actually used it. Glad I have it in 5.4 still, but somehow I feel this is temporary. OpenAI: Please bring Canvas back!!!! For some of us, it was not a side feature. It was a core part of how we write and think inside ChatGPT. submitted by /u/BlueRidgeTog [link] [comments]

How to Create A4 Brochures with Claude and Canva

I tried to create a4 4 page brochures using Claude.ai and canva. But the result was terrible and ugly, mostly words only. No images and terrible colours and icons. I thought that with Claude Design it will be able to generate awesome brochures in no time. Usually I spend almost 4-6 hours in Canva pro to tweak and get the right fonts, sizes, images, placements before the brochure is done. What do you guys use? Is there any skill or front end design or something that I am missing here? submitted by /u/DirectionDramatic675 [link] [comments]

Claude makes documents into apps

Any document can become an app I’ve been working on an open-source document format and viewer called Adaptive Markdown. The basic idea is simple: A document should not have to stay static. It should be something a coding agent can extend, reshape, and turn into an interactive workspace. This is not just a canvas you edit with a chatbot. The bigger idea is that the document becomes both: the source of truth the programmable interface In other words, the document becomes a living app. You write notes, collect data, draft text, or import files. Then a coding agent can directly modify the document surface: add charts, create calculators, build filters, restyle sections, generate summaries, export views, or turn rough notes into an interactive tool. So instead of having: a document a spreadsheet a dashboard an app a changelog a separate AI chat about all of it You can have one living .md file that contains those layers together. Example A fitness log might start as a plain Markdown journal. Then the agent adds charts. Then it pulls in device data. Then it adds weekly summaries, rolling averages, goal tracking, export options, and a dashboard view. The document did not move into an app. The document became the app. Other use cases A billable time log that computes subtotals and rewrites rough notes into polished narratives A research notebook with experiment parameters, runnable code, outputs, and methodology notes A recipe book that scales servings and generates shopping lists A math textbook that can explain a theorem at different levels A project README that explains the system, demonstrates the system, and lets the agent modify it from inside the document A small data report with embedded CSV data, live charts, filters, and exportable views The thing I’m most interested in is not "Can Markdown support more widgets?" It is: What happens when the document itself becomes the programmable, agent-editable interface? Demos I made a few short video demos: Turn your document into a snake game: https://youtu.be/l-I2UiZd-Jw Basic Adaptive Markdown features: https://youtu.be/cLdzvZAL96I Import CSV, create tables, edit and format them: https://youtu.be/XKh9D3BlTCg Import MusicXML and transpose sheet music: https://youtu.be/8YV3zjMLvA8 Why I’m excited about this The biggest use case I’m excited about is academic and technical reading. In a few years, I don’t think people will just read papers passively. I think they’ll translate passages, ask questions, generate examples, explore alternate proofs, run code, attach notes, convert math to Lean where possible, and keep all of that inside the document instead of scattered across chats and notebooks. This is already pretty natural inside a browser when a coding agent has access to JS, CSS, and the document structure. It’s very early, but the workflow already feels useful to me. I’m using it for my own notes and documents. Right now it is configured for the Anthropic coding-agent SDK and experimentally for Codex. The longer-term goal is to make it run entirely locally. GitHub: https://github.com/SemiSimpleMath/Adaptive-Markdown I recently added per-document skills, so agents can automatically know how to style or transform the text or data inside a specific document. Curious whether this seems useful to anyone else, or whether I’m just overexcited because I built it. Feature requests welcome. submitted by /u/IDefendWaffles [link] [comments]

Which AI image generator is actually worth the money?

I've looked at about a dozen different image generators: Nano Banana Flux Midjourney GPT Image 2 Firefly Ideogram Recraft Leonardo Canvas Meta AI They all have their pluses and minuses but they all do a decent job. If I'm looking to spend thousands over a year on an image generator, what would you suggest. This would be mainly for business and a little for art. submitted by /u/DogDetector42 [link] [comments]

I wish there was a “Canva for AI training” already

Honestly one of the biggest reasons AI training still feels intimidating is because the workflow is unnecessarily painful for normal builders.You still end up dealing with random CUDA errors, dependency conflicts, broken environments, terminal commands, config files, dataset formatting, cloud GPU setup, checkpoint management, crashes, and 20 different tools stitched together just to fine tune a model. Meanwhile most people don’t actually want to become ML infrastructure engineers. They just want to train a specialized model for their own niche idea. I genuinely think there’s room for a platform where you could Upload dataset, Choose base model, Pick behavior/settings, Press train, Deploy API and That’s it. Almost like a “Canva” or “Shopify” moment for AI model training. Feels inevitable honestly. Once AI training becomes abstracted enough, the bottleneck shifts from infrastructure knowledge to creativity, data quality, and problem understanding. And I think that changes who gets to build powerful AI systems completely. submitted by /u/Raman606surrey [link] [comments]

I built a zero-code visual client to test remote MCP servers instantly (Tested with Cloudflare’s free MCP).

Hey everyone, The Model Context Protocol (MCP) is amazing for standardizing how agents talk to data, but I got incredibly frustrated every time I wanted to quickly test a new remote MCP server. Writing custom client-side boilerplate or wrestling with CLI tools just to see if a tool actually exposes the right schema is a massive time sink. So, I built a native MCP client directly into the visual canvas of AgentSwarms. You can now test any remote MCP server entirely in the browser without writing a single line of code. Here is the workflow I just tested with Cloudflare: Cloudflare released a free MCP server for their documentation. Instead of building a local client to test it: I dropped their SSE URL into the new MCP Servers integration in AgentSwarms. The canvas immediately connected and extracted the available tools (e.g., cloudflare-docs-search). I wired that tool up to a basic agent and started asking complex infrastructure questions in natural language. The agent successfully used the MCP tool to pull live docs and synthesize an answer. Why this is useful for AI devs: If you are building your own MCP servers, you need a fast way to visually test if your endpoints are exposing tools correctly and if an LLM can actually route to them properly. This gives you an instant, visual debugging playground. It handles the SSE connection, tool extraction, and LLM routing automatically. It’s completely free to play with in the browser. I'd love for anyone building MCP servers right now to plug their endpoints in and see how it works. Link: https://agentswarms.fyi/mcp submitted by /u/Outside-Risk-8912 [link] [comments]

I built a zero-code visual client to test remote MCP servers instantly (Tested with Cloudflare’s free MCP).

Hey everyone, The Model Context Protocol (MCP) is amazing for standardizing how agents talk to data, but I got incredibly frustrated every time I wanted to quickly test a new remote MCP server. Writing custom client-side boilerplate or wrestling with CLI tools just to see if a tool actually exposes the right schema is a massive time sink. So, I built a native MCP client directly into the visual canvas of AgentSwarms. You can now test any remote MCP server entirely in the browser without writing a single line of code. Here is the workflow I just tested with Cloudflare: Cloudflare released a free MCP server for their documentation. Instead of building a local client to test it: I dropped their SSE URL into the new MCP Servers integration in AgentSwarms. The canvas immediately connected and extracted the available tools (e.g., cloudflare-docs-search). I wired that tool up to a basic agent and started asking complex infrastructure questions in natural language. The agent successfully used the MCP tool to pull live docs and synthesize an answer. Why this is useful for AI devs: If you are building your own MCP servers, you need a fast way to visually test if your endpoints are exposing tools correctly and if an LLM can actually route to them properly. This gives you an instant, visual debugging playground. It handles the SSE connection, tool extraction, and LLM routing automatically. It’s completely free to play with in the browser. I'd love for anyone building MCP servers right now to plug their endpoints in and see how it works. Link: https://agentswarms.fyi/mcp submitted by /u/Outside-Risk-8912 [link] [comments]

How I built a 9-agent team where my agents actually talk to each other

I've been running Claude Code for 6 months, shipping my product and running content/launch ops for it. The thing that kept breaking wasn't the agents themselves. It was me. Every handoff between research and write and code and review was me copy pasting context between sessions. I was the dispatcher and context holder for my own AI team Tried gstack first. The roles are great but I'm still the one cycling through slash commands. /office-hours → /plan-eng-review → /review → /ship. Good output, but I'm orchestrating every step Spent a weekend porting my workflow over. Here's the lineup: Engineering (4 agents) arch: owns architectural decisions. Reviews proposed changes before code starts. Soul: "senior staff engineer, asks 'what breaks at 10x' before approving anything backend: owns /api, /services. Implements after arch greenlights frontend: owns /web. Picks up from backend when API contracts are stable review: reads every PR before I do. Catches the lazy stuff so I only review substantive changes Growth/Content (5 agents) research: uses ahrefs MCP to analyse keywords/opportunities/market and hands off to strategist strategist: reads research, writes campaign briefs. Doesn't write copy, only frames the angle writer: drafts blog posts given by strategist and avoid mistakes using the memory from the edits I have previously suggested editor: fact-checks and rewrites for voice. Brand style guide lives in its memory SEO: takes finalized copy, adds metadata, structures for the blog The handoff that changed everything: when backend ships an API change, it messages frontend directly. When writer finishes a draft, it pings editor. When arch blocks a change, it explains why in team chat and backend adjusts. I see the conversation happen on a canvas What actually works Each agent has a persistent Soul + Purpose + Memory. The editor knows our voice after 3 weeks. The arch agent remembers what we decided about caching last month Auto-captured Knowledge Base. The strategist remembers the pattern of our best-performing posts and create briefings accordingly Happy to share the Soul/Purpose docs if anyone wants them, they took the longest to dial in submitted by /u/Not_Average78 [link] [comments]

How Can I Automate Personalized Real Estate Seller PDFs Using AI + Canva + Property Monitor?

Hi everyone! I wanted to ask for some advice. I’m a real estate agent in Dubai, and one of the biggest hurdles is convincing sellers to list their properties online. I’ve created a marketing strategy that I currently present to sellers through a Canva PDF, and it has been working very well. However, I’d like to take it a step further and make the PDF more personalized: Ideally, I want to enter a unit number + building name, and then have ChatGPT or Claude pull data from a website I have access to called Property Monitor. The goal would be for it to automatically find: The last 3 transactions for the same series/layout on comparable floors + 3 current live listings for the same series/layout on comparable floors. Then I’d like that data to populate directly into placeholders in Canva and automatically generate a personalized PDF for the seller. Is this technically possible? I’d really appreciate any advice on the best way to set this up, what tools would be needed, and whether ChatGPT/Claude can realistically be integrated into a workflow like this. Thanks so much! submitted by /u/Omayab [link] [comments]

Claude for Small Business launched this week with 8 integrations. Most SMBs use 20+. What does that mean for the rest of the stack?

Anthropic launched Claude for Small Business on Tuesday. The package includes 15 prebuilt agentic workflows and 8 named integrations: Intuit QuickBooks, PayPal, HubSpot, Canva, DocuSign, Google Workspace, Microsoft 365, and Slack. The workflows handle things like invoice chasing, payroll planning, month-end close, sales campaigns, contract routing, and cash-flow forecasting. Owners approve before anything sends or pays. The basic facts are not in dispute. What's interesting is the math. Most small businesses use more than 8 tools. The common ones not on that list: Shopify, Stripe, Square, Klaviyo, Mailchimp, ActiveCampaign, ConvertKit, Pipedrive, GoHighLevel, Calendly, Notion, Airtable, ClickUp, Webflow, Zapier. Then vertical-specific tools: ServiceTitan, Jobber, Housecall Pro for trades. Kajabi, Teachable, Circle for creators. Toast, Resy, OpenTable for restaurants. Etsy, Faire, Printify for makers. Real question worth asking: how much of a typical small business stack does the 8-tool package actually cover, and which kinds of businesses are well-served versus left out? A rough walk through some common archetypes: Office-based service business (consultants, accountants, agencies, B2B services). Coverage is decent. Most are on Google Workspace or Microsoft 365, run finance through QuickBooks, communicate via Slack, and many use HubSpot. The 8 tools probably hit most of the core stack for this group. E-commerce or DTC brand. Coverage is thin. Shopify isn't there. Stripe isn't there. Klaviyo isn't there. The actual revenue stack of an online store is mostly outside the covered set. Local trades (HVAC, plumbing, insulation, electrical, landscaping). Coverage is essentially absent. The operating systems for these businesses are ServiceTitan, Jobber, Housecall Pro, Square for payments, sometimes QuickBooks for accounting on the back end. The customer-facing and operational tools are not on the list. Creators, coaches, course sellers. Coverage is absent. Kajabi, ConvertKit, Teachable, Circle, Substack. None of it is in the package. Restaurants and hospitality. Coverage is absent. Toast, Square POS, Resy, OpenTable, Toast Payroll. The actual operating systems are not on the list. A few patterns emerge from that walk. First, the package targets a specific kind of small business. Office-based, white-collar, finance running through QuickBooks, meetings on Google or Microsoft, sales through HubSpot. That is a real segment. Anthropic chose it deliberately and the workflows make sense for that profile. Second, for everyone else, the prebuilt workflows mostly don't touch the tools they actually use day to day. The choice isn't "use Claude for Small Business or not." It's "AI in my operations, yes, but via custom work outside this package." That's not a complaint about the launch. Building 8 polished integrations is hard and Anthropic had to pick. It's more an observation that "Claude for Small Business" as a category name covers a wider universe than what the package actually addresses on day one. Curious how this lines up with what people are actually running. If you operate a small business, how many of the 8 covered tools are in your stack? And what's NOT on that list that you'd most want connected to an AI agent? submitted by /u/KolioMandrata [link] [comments]

HTML artifacts are starting to replace Google Docs on my team (But it's missing comments)

Been using Claude to convert long-form work docs (spike readouts, architecture notes, meeting prep) into self-contained interactive HTML pages: inline SVG diagrams, sticky TOC, collapsible sections, tabbed comparisons. Publish to an artifact host, share a URL. The output is genuinely better than the equivalent Google Doc for dense technical content. But there's a glaring gap: no commenting, no suggesting edits, no inline review. Google Docs has 20 years of polish on highlight-and-comment + suggesting mode. Figma nailed comment pins on a canvas. GitHub has line-level PR review. None of those primitives have ported over to the "AI generates a static HTML artifact you share" workflow yet, partly because the artifact renders inside a sandboxed iframe, so the host platform can't just hook selection events the way Docs does on its own DOM. Feels like a real paradigm shift in how docs get made, with a real gap in how they get reviewed. What are people doing? Falling back to Slack threads on the URL? Has anyone actually shipped good commenting on iframe-isolated AI artifacts? submitted by /u/Comprehensive-Ad1819 [link] [comments]

I built a daily thought app with Claude Code, including a line-art system drawn entirely in SwiftUI

I built an iOS app called One Good Thing with Claude Code as my main coding partner. It is free to try, and the core daily card experience is free. The idea is simple: one thoughtful card per day, under two minutes. You either Carry it or Let Go, then close the app. No feed, no endless scroll, no pressure to stay inside it. What I thought might be interesting for this sub is not just the app, but one part of the build process: every illustration in the app is drawn in code. No pencil. No tablet. No image file. Each hand, bird, window, thread, dot, and curve is a SwiftUI Canvas path. The result is meant to feel hand-drawn, but it is all coordinates and Bezier curves. Claude helped in a few specific ways: Turning vague visual direction into first-pass SwiftUI Canvas paths Refactoring repeated drawing logic so the illustrations stayed consistent Catching SwiftUI edge cases, especially around view state, animations, and previews Helping me reason through Firebase, StoreKit, Cloud Functions, App Check, and Firestore rules without losing the product shape The workflow that worked best was not "make me an illustration." It was more like: Describe the feeling of the screen in plain language Ask Claude for a rough Canvas implementation Run it in the app Manually tune the coordinates until it felt less like an icon and more like a small mark someone might pause on Ask Claude to simplify or make the code safer once the direction felt right The biggest lesson for me was that Claude is much better when I treat it like a patient pair programmer, not a vending machine. It can get a first draft on screen very quickly, but the taste still has to come from you. The useful loop was: generate, inspect, adjust, reduce. The app itself also uses Claude-assisted code across the stack: SwiftUI for the iOS app, Firebase Cloud Functions, Firestore security rules, a Next.js landing page, and some AI reflection features for subscribers. But the line-art system is probably the most visible place where the collaboration shows. Would love feedback on: Whether the coded illustration idea comes through Whether this is a useful example of Claude Code beyond CRUD/app boilerplate What you would have done differently in the Claude workflow Free to try, core daily card is free. https://apps.apple.com/app/one-good-thing-daily-thought/id6759391105 submitted by /u/Evening-Strike-2021 [link] [comments]

🎉 Big news for small business. Canva is now integrated into @claudeai for Small Business, bringing the power of campaign creation to business owners doing it all. https://t.co/Gcrv8O5kjw

🎉 Big news for small business. Canva is now integrated into @claudeai for Small Business, bringing the power of campaign creation to business owners doing it all. https://t.co/Gcrv8O5kjw

Why do some people hate AI so much?

How come people hate AI so much? I do not understand why? To me AI has been helpful in terms of designing and putting my drawings to real life instead of spending hours doing it myself in Canva or paying hundreds of $$$ to animate my sketch. Also been helpful with my business ads on Instagram cause i am able to get what I visioned and I do not need to spend hours doing camera angles and having the actual product on my hands like old school advertising. Most big companies like Ulta or Sephora uses AI now on their marketing emails. For me, AI helped me save so much time making ad post cause I still work a full time job while running an online shop and time is my valuable resource. I tried to do ads the old school way and wasted 2 hours when I could have done so much in 2 hours. Now I am sitting here typing while I am waiting for chat gpt to generate me a new ad image I can use on my marketing email while in between doing laundry. submitted by /u/Active-Front1788 [link] [comments]