{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreihhgvkbsghobp3oqfpiqowft6ec6bieg7ekg22mwkayaqv3o7fmpe",
    "uri": "at://did:plc:lk3jfj3zq4k4wxnk474axylu/app.bsky.feed.post/3mo5jcgyjov72"
  },
  "path": "/t/ai-as-an-operating-system/1383562#post_1",
  "publishedAt": "2026-06-13T04:31:49.000Z",
  "site": "https://community.openai.com",
  "textContent": "Hello OpenAI Team,\nOver the past weeks, I have been using ChatGPT not primarily as a chatbot, but as the central control unit of a larger AI ecosystem for work, leadership development, school management, automation projects, and personal productivity.\nThe experience has been extremely promising, but I have noticed that the biggest limitations are no longer related to AI intelligence itself. The bottleneck is orchestration.\nToday, ChatGPT can already help me:\nCreate concepts\nAnalyze complex situations\nGenerate documents\nBuild workflows\nEvaluate decisions\nCoordinate projects\nHowever, the following features would create a massive leap in practical usefulness:\n\n  1. True Project-Based Architecture\nCurrent state:\nConversations exist mostly as separate chats.\nDesired state:\nPlain text\nMission 36\n├── School Development\n├── Leadership Training\n├── School Automation\n├── Finance\n├── Health\n└── AI Ecosystem\nProjects should function as persistent workspaces with shared memory, shared objectives, and linked subprojects.\nThe system should understand relationships between projects automatically.\n  2. Native Multi-AI Orchestration\nCurrent state:\nChatGPT can recommend using other AI systems, but the user must manually copy and paste prompts between platforms.\nDesired state:\nPlain text\nTask\n↓\nChatGPT routes\n↓\nPerplexity research\n↓\nClaude quality assurance\n↓\nChatGPT integration\n↓\nFinal product\nWithout manual intervention.\nThe user should remain the decision-maker, but not the data courier.\n  3. Persistent Experience Library\nCurrent state:\nThe system remembers information but has limited ability to build a structured library of proven workflows.\nDesired state:\nPlain text\nTask Type:\nSchool Law\n\n\n\nProven Workflow:\nPerplexity → ChatGPT\n\nConfidence:\nHigh\n\nTests:\n12 successful\nOver time, ChatGPT should learn which workflows actually work best for specific task categories.\nNot theoretical recommendations.\nEvidence-based recommendations.\n4. Native Agent Workflows\nDesired state:\nThe system should be able to execute multi-step workflows autonomously:\nPlain text\nProblem\n↓\nClassification\n↓\nResearch\n↓\nQuality Assurance\n↓\nDocument Creation\n↓\nPresentation Creation\n↓\nFinal Package\nThe user only reviews the result.\n5. Professional Document Production\nOne of the largest gaps today is professional output generation.\nDesired state:\nHigh-quality:\nDOCX\nPPTX\nPDF\nExcel\nwith modern layouts, visual design, branding options, templates, and publication-ready formatting.\nFor many professional users, document quality is just as important as content quality.\n6. Workflow Memory Instead of Chat Memory\nCurrent state:\nThe system remembers information.\nDesired state:\nThe system remembers successful processes.\nExample:\nPlain text\nRecipe worksheets\n→ ChatGPT direct\n\nSchool law\n→ Perplexity + ChatGPT\n\nSchool development concepts\n→ ChatGPT + QA review\nThis would allow AI systems to evolve into true operating systems rather than advanced assistants.\nWhy This Matters\nThe limiting factor is no longer:\n“Can the AI solve the task?”\nIn many cases, it already can.\nThe limiting factor is:\n“Can the AI manage the entire process?”\nThe future opportunity is not just better answers.\nIt is AI-powered workflow orchestration.\nI believe this could be one of the most impactful directions for future versions of ChatGPT.\nThank you for building such an impressive platform. I am excited to see where it goes next.\nBest regards, A power user exploring AI as an operating system.",
  "title": "AI as an operating system"
}