AI Tools SaaS @AITool_Stack

AI isn’t replacing people. People who know how to use AI are gaining an advantage over people who don’t. And the gap is getting bigger. Think about what you can already offload to AI: → Research in minutes instead of hours of searching → Write, rewrite & edit without staring at a blank page → Analyze huge amounts of information and extract the key points → Generate images & videos without a full creative team → Automate repetitive work that eats up your day → Turn an idea into something usable in minutes But here’s what most people get wrong: The advantage isn’t knowing how to use one AI tool. It’s knowing which tool to use for which problem. ChatGPT for one task. Claude for another. Perplexity when you need research. Specialized tools when you need design, video, automation, or data. The real skill is building an AI stack that fits your workflow. Less time on repetitive work. More time on thinking, creating, and executing. That’s what I’m building this page around. ⚡️ AI tools. SaaS. Better workflows. Practical ways to get more done with AI. Follow @AITool_Stack if you want to build a smarter AI stack.

AI is changing how people work. And if you’re still doing these tasks manually, you’re probably wasting hours every week. Here are 5 tasks you should stop doing manually: → Writing repetitive emails Follow-ups, meeting recaps, customer replies, internal updates — AI can draft them in seconds. → Summarizing long documents Reports, research papers, meeting notes, PDFs, and lengthy emails can be turned into clear takeaways almost instantly. → Researching basic questions Instead of opening 20 tabs and digging through search results, AI can help you find, organize, and summarize the information you need. → Creating social media content Turn one idea into posts, captions, hooks, content calendars, and multiple variations in minutes. → Organizing repetitive workflows From turning notes into tasks to sorting information and creating templates, AI can remove a lot of repetitive work from your day. The point isn’t to let AI do everything for you. It’s to stop spending your time on work that doesn’t require your time. Use AI for the repetitive stuff. Use your time for thinking, creating, making decisions, and building. Work smarter. Create faster. Get more done. ⚡️ Follow @AITool_Stack for useful AI tools, SaaS finds, and productivity tips.

5 AI tools that can save you hours every week — without adding more complexity to your workflow: 5. ChatGPT Research, writing, brainstorming, summarizing, strategy, and everyday tasks. Think of it as your all-purpose AI copilot. 4. Perplexity Need to research something fast? Perplexity combines AI answers with web sources, making it useful for finding and verifying information. 3. Canva Create social posts, presentations, ads, graphics, and other content faster with AI-powered design tools. 2. Notion AI Turn messy notes into organized docs, summarize meetings, brainstorm ideas, and speed up your daily workflow. 1. Claude Great for long-form writing, deep analysis, coding, and working with large amounts of information. And here’s the thing: You probably don’t need 50 different AI tools. You need a small stack of tools that actually fit the way you work. Research → Create → Organize → Analyze → Execute The right AI stack can save time, reduce repetitive work, and help you get more done every week. Follow @AITool_Stack for useful AI tools, SaaS finds, productivity hacks, and tools worth knowing. ⚡️

Most people use AI to save minutes. Smart people use it to save hours. AI can help you: → automate repetitive tasks → create content faster → research in seconds → run a business more efficiently → replace dozens of small tools I’ll share the best AI tools & SaaS I find. Save this account. You’ll find some useful ones here. ⚡️

Current AI tier rankings 💀

今のAIモデルティア表 絶対に異論はないはず、、

𝗠𝗼𝘀𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝘁𝗵𝗶𝗻𝗸 𝗔𝗜 = 𝗖𝗵𝗮𝘁𝗚𝗣𝗧. Not even close. ChatGPT is what you see. The real AI revolution is the massive ecosystem being built underneath it. This AI Stack Map captures 100+ tools powering modern AI applications. 𝗧𝗵𝗲 𝗺𝗼𝗱𝗲𝗿𝗻 𝗔𝗜 𝘀𝘁𝗮𝗰𝗸 𝗹𝗼𝗼𝗸𝘀 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗹𝗶𝗸𝗲 𝘁𝗵𝗶𝘀: LLMs → OpenAI, Claude, Gemini, Llama, Mistral Agentic AI → LangGraph, CrewAI, AutoGen, CAMEL, Agno RAG → LangChain, LlamaIndex, Haystack, GraphRAG Embeddings → OpenAI, Voyage, Cohere, BGE MCP → Connecting models with tools, data and systems AI Security → Guardrails, Presidio, Lakera, Prompt Security Observability & Evals → LangSmith, Langfuse, Phoenix, Ragas Memory → Redis, Mem0, Zep, Neo4j, Chroma Agent Frameworks → OpenAI SDK, Semantic Kernel, Google ADK, Bedrock Automation → n8n, Zapier, Make, Airflow, Prefect Vector Databases → Pinecone, Weaviate, Qdrant, Milvus, pgvector But here’s the part that matters more than the logos. 𝗧𝗵𝗶𝘀 𝗶𝘀 𝗻𝗼𝘁 𝗮 𝘀𝗵𝗼𝗽𝗽𝗶𝗻𝗴 𝗹𝗶𝘀𝘁. It’s a dependency graph. Your RAG is only as good as your retrieval + embeddings. Your agent is only as reliable as its tools + evaluations + guardrails. Your memory is useless if you can’t observe when context becomes stale or wrong. Your MCP layer becomes dangerous if permissions and governance are an afterthought. And a “best-in-class” stack can still become a terrible production system. Why? Because AI systems rarely fail only inside one component. 𝗧𝗵𝗲𝘆 𝗳𝗮𝗶𝗹 𝗮𝘁 𝘁𝗵𝗲 𝗵𝗮𝗻𝗱𝗼𝗳𝗳𝘀. Model → Retrieval Retrieval → Context Context → Agent Agent → Tool Tool → Memory Memory → Evaluation That’s where latency compounds, context gets lost, permissions leak, hallucinations propagate and reliability starts falling apart. 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹 𝗺𝗼𝗮𝘁 𝗶𝘀𝗻’𝘁 𝗵𝗮𝘃𝗶𝗻𝗴 𝗺𝗼𝗿𝗲 𝗔𝗜 𝘁𝗼𝗼𝗹𝘀. It’s designing how they work together. A stack map tells you 𝗪𝗛𝗔𝗧 exists. Production engineering decides 𝗛𝗢𝗪 it all survives contact with reality. Which tool in your AI stack has become indispensable? Save this map for your next AI build. Repost it for someone designing an AI architecture. #AI #ArtificialIntelligence #GenAI