{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreigwevpvfrx7oieearlvr6ktopakmc6yxovwci4l6wzhuwo5t5mzae",
    "uri": "at://did:plc:lk3jfj3zq4k4wxnk474axylu/app.bsky.feed.post/3mlbbvvxo7p72"
  },
  "path": "/t/collection-of-gpt-image-generator-2-0-issues-bugs-and-work-around-tips-check-first-post/1379535?page=10#post_196",
  "publishedAt": "2026-05-07T11:30:48.000Z",
  "site": "https://community.openai.com",
  "tags": [
    "GitHub",
    "Build software better, together",
    "https://openai.com/index/memory-and-new-controls-for-chatgpt/",
    "developers.openai.com",
    "Context Engineering - Short-Term Memory Management with Sessions",
    "Building Reliable Agents with Memory and Compaction"
  ],
  "textContent": "Taragonn:\n\n> People may think I’m completely crazy for describing it this way. Maybe I am.\n\nI would say you are correct.\n\nBoth OpenAI and Anthropic have been working hard in how to manage memory to get past problems of the context window size, learning from prompts by finding patterns and storing them, etc.\n\nIf one regularly reads the blogs, cookbooks, GitHub commits, etc., this becomes evident.\n\nGitHub\n\n### Build software better, together\n\nGitHub is where people build software. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects.\n\nhttps://openai.com/index/memory-and-new-controls-for-chatgpt/\n\ndevelopers.openai.com\n\n### Context Engineering - Short-Term Memory Management with Sessions\n\nAI agents often operate in long-running, multi-turn interactions, where keeping the right balance of context is critical. If too much is car\n\ndevelopers.openai.com\n\n### Building Reliable Agents with Memory and Compaction\n\nThis Cookbook shows how to build an evidence review agent for a synthetic compliance investigation using the OpenAI Agents SDK. You will st",
  "title": "Collection of GPT-image-generator 2.0 issues, bugs, and work-around tips (check first post)"
}