{
  "$type": "site.standard.document",
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    "uri": "at://did:plc:lk3jfj3zq4k4wxnk474axylu/app.bsky.feed.post/3mmgp7o36cmk2"
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  "path": "/t/feedback-from-a-remote-codex-helper-prototype-long-session-performance-durable-queue-and-mcp-process-reuse/1381062?page=2#post_22",
  "publishedAt": "2026-05-22T10:13:17.000Z",
  "site": "https://community.openai.com",
  "textContent": "Feature Request: AI Observer / Runtime-Aware Dev Agent\n\nI want to add a related Codex developer workflow request: an AI Observer layer for runtime-aware development.\n\nCurrent problem:\n\nLLMs help write code, but remain mostly blind during runtime. They often cannot see browser behavior, live DOM changes, extension popup state, console logs, workers, runtime state, or visual UI failures. This forces users to repeatedly explain obvious bugs and creates unnecessary clarification loops.\n\nRequested direction:\n\nCreate a browser and runtime aware assistant layer that can safely observe live development environments and report precise debugging feedback.\n\nKey capabilities:\n\n  * Browser vision and visual UI verification\n  *     * DOM state awareness\n    *       * Console, log, worker, and runtime monitoring\n      *         * Extension popup and runtime observation\n        *           * Progress and readiness tracking\n          *             * Safe test mode\n            *               * User notes queue\n              *                 * One active worker enforcement\n                *                   * Visual error reporting\n                  *                     * Persistent project context\n                    *                       * Clear distinction between static check, dry run, visual runtime test, and live browser verification\n                    * Desired workflow:\n                    * User says: Fixed it, test again.\n                  * AI Observer:\n                  *                     * watches the browser and runtime\n                    *                       * tests safely\n                      *                         * reports the exact issue\n                        *                           * suggests a focused fix\n                          *                             * keeps project memory and context\n                          * Important:\n                          * The assistant must not hallucinate test results. It should explicitly state what it actually verified and how: static analysis, dry run, browser test, visual inspection, or live runtime observation.\n                        * Long-term vision:\n                        * An IDE and browser connected AI orchestration system that is conversational, runtime aware, visually aware, project persistent, and useful for agent assisted development workflows.\n                      * This would reduce repeated clarification, make debugging faster, and improve developer trust in AI coding agents.\n\n",
  "title": "Feedback from a remote Codex helper prototype: long-session performance, durable queue, and MCP process reuse"
}