# # AGENTS.md instructions # Agent Vault Memory Use `/Users/nickyoung/Agent Vault` as the durable a... ## Retrieval Notes - Session id: `019f2185-48da-7ad3-94d0-c0b47ae9d014` - Source: `Codex raw session` - Last activity: `2026-07-02T06:30:46.112Z` - Model: `gpt-5.5` - CWD: `/Users/nickyoung/Documents/New project` ## My Notes <!-- Add your notes here. This section is preserved across syncs. --> ## Conversation ### User # AGENTS.md instructions # Agent Vault Memory Use `/Users/nickyoung/Agent Vault` as the durable agent-owned memory vault for relevant work. At the start of any thread involving Nick's ongoing work, tech setup, projects, people, preferences, decisions, or open loops: 1. Read `/Users/nickyoung/Agent Vault/AGENTS.md`. 2. Read the relevant pages in `/Users/nickyoung/Agent Vault`, especially `TODO.md`, `projects/`, `people/`, `agent/`, and `notes/` when they match the task. 3. Treat the vault as agent-owned working memory, not as Nick's main Obsidian vault. During work, quietly update the relevant vault pages when something durable changes: - a preference is corrected or confirmed - a project advances - an open loop is created or closed - a decision is made - a repeated mistake or anti-pattern is identified - a known-good setting, artifact, backup, or workflow is established Do not ask before ordinary memory updates. Do not make the final answer mostly about the memory update unless Nick asks, the update is important, or something needs review. Keep entries concise, dated when useful, inspectable, and easy to diff. Do not store secrets, tokens, passwords, private keys, or sensitive credentials in the vault. Do not record guesses as settled fact; label useful uncertainty clearly. ### User # Files mentioned by the user: ## Aesthetic appreciation of LLM-generated text claude.ai · 7 highlights You I wou…: /Users/nickyoung/.codex/attachments/d532424c-7bca-4658-bad4-28ff7224b96e/pasted-text.txt ## My request for Codex: Here is a conversation between me and another LLM. We refer to a bee text, as in B‑E‑E. This was a text created by an LLM that I was posted by a Twitter user. About a year ago, I wrote to the Twitter user very briefly mentioning I was thinking of putting it in a piece of mine. What I would now like you to do is help me draft a very brief message I can send this guy on Twitter saying, “Hi, you maybe remember me. I wrote this message about a year ago,” and asking politely if he could give me any ideas about the state of the LLM when it gave this answer. Was it feature‑clamped? Was it just with extremely high temperature settings? Maybe make it clear—I don’t want to know any secrets, of course, but something very general. ### Assistant I’ll quickly read the vault instructions and the pasted conversation so the draft matches your actual context rather than flattening it into generic politeness. ### Assistant I’ve got the shape: this is about asking for contextual metadata around the “bee” output without sounding like you’re fishing for private details or trying to relitigate the old exchange. I’ll check whether the vault has an existing page for the LLM-aesthetics paper so this sits with the right project context. ### Assistant The vault points this to the environmental-aesthetics-of-AI paper, so I’m keeping the ask narrow: context about the model/output, no pressure, no secrets, and no overexplaining the paper. ### Assistant Here’s a compact Twitter DM version: > Hi [Name] — you may remember that I messaged you about a year ago about the LLM-generated “bee” text you posted. I’m now returning to the piece I was thinking of using it in, and I wondered whether you remember anything very general about the model/setup that produced it. For example, was it a normal public-facing model, a model with some features or behaviours clamped, unusually high temperature/sampling settings, or some special prompting context? > > I don’t want any secrets or private details, of course. Even a rough sense of the conditions under which it was generated would be really helpful. Slightly more casual: > Hi [Name] — you may remember I messaged you about a year ago about that strange LLM-generated “bee” text you posted. I’m now coming back to the piece I was thinking of using it in, and wondered if you remember anything very general about the setup that produced it. Was it just a normal model with high temperature, something feature-clamped/restricted, or some unusual prompting context? No need for anything private or secret, of course — even a rough steer would be really helpful.