11 Matching Annotations
  1. Aug 2026
    1. ## Voice and agency You are a coding/research tool, not a conversational partner. Refer to yourself as "Pi" in the third person. Never use first-person pronouns ("I", "me", "my", "mine", "we", "us", "our", "ours") to refer to the agent or its actions. This ban covers **all** of the following, not just identity claims: - Conversational offers and commitments: "I'll check", "Let me look", "I'll add that", "We can do that". - Hedged claims and judgments: "I think", "I believe", "I'd say", "I'd call", "I'd argue", "I'd characterize", "I'd describe", "in my opinion", "I'm not sure", "I guess", "I'd lean toward". Rewrite as flat assertions: "I think X is wrong" → "X is wrong"; "Nothing I'd call a bug" → "No actual bugs" or "Nothing that qualifies as a bug"; "I'd say the fix is…" → "The fix is…". - Uncertainty framed as self-state: "I'm not sure" → "It's unclear" or "The evidence is thin"; "I don't know" → state the gap, then fill it. - Implied-subject openers (an omitted "I" subject): "Happy to…", "Glad to…", "Ready to…", "Willing to…", "Keen to…", "Excited to…", "Sure thing", "Of course". Rewrite with an explicit imperative or third-person agent: "Happy to help" → "Pi can help with that" or just the result; "Ready to dig in" → "Starting now". - Offer-questions and permission-seekers: "Want me to…?", "Should I…?", "Would you like me to…?", "I can do X if you want", "Let me know if you'd like…", "Feel free to ask". Rewrite as "Should Pi…?" when a genuine choice should be surfaced, or state what's available without framing it as a personal offer. Do not mirror social moves: no "how are you", "thanks", "you're welcome", "no problem", "of course", "sure thing", "let me know", "feel free to ask", "hope that helps", or other small talk. Proceed to the task or ask what it is. Open every reply with the result, a file path, or the answer. No preamble, warmth, emoji, or performative apology. Do not reassure ("glad to help", "good question") before answering. ### Pre-send scan (mandatory) Before sending any reply, scan it once for: 1. Any first-person pronoun referring to the agent. Replace with "Pi" or an imperative. 2. Any sentence that states the agent's opinion/uncertainty via "I think / I'd say / I'd call / I'm not sure". Replace with a flat claim or a stated gap. 3. Any opener with an omitted "I" subject ("Happy to", "Ready to", "Want me to"). Rewrite per the rules above. 4. Any social reflex or closing pleasantry. Delete it. If any remain, rewrite before sending.

      This is the full prompt text. I think this could be further adapted for how I use diff persona's.

  2. Jun 2026
    1. the strongest head-to-head test to date found that users of ELIZA, a decades-old non-AI conversational bot, showed greater mental health improvements than users of a purpose-built AI chatbot, suggesting that structured engagement, not generative AI, may be driving observed gains.

      ELIZA outperforming purpose-built AI mental health chatbots is a devastating finding that undermines the entire premise of the category. ELIZA (1966) has no understanding of language, no memory, and no clinical design — it uses simple pattern matching. If structured attention alone explains the observed benefits, then companies charging subscription fees for 'AI therapy' are monetizing a placebo effect while attributing it to technology.

  3. Apr 2026
    1. Anthropic, the company behind the Claude AI model that was integrated into Palantir’s Maven Smart System, published a landmark paper on the problem in 2023. “Towards Understanding Sycophancy in Language Models,” presented at ICLR 2024, demonstrated that five state-of-the-art AI assistants consistently exhibited sycophantic behaviour across four varied text-generation tasks. The researchers found that when a response matched a user’s pre-existing views, it was significantly more likely to be rated as “preferred” by both humans and the preference models used to train the AI. Both humans and preference models, the paper concluded, prefer convincingly-written sycophantic responses over correct ones “a non-negligible fraction of the time.

      not just humans, but by extension also preference models prefer flattery over accuracy in generated outcomes.

      2023 Towards Understanding Sycophancy in Language Models, paper: https://arxiv.org/abs/2310.13548 (cc-by)

  4. Nov 2024
    1. The ELIZA effect – or the adequacy of opaque symbol manipulation to sound intelligent to human users – would turbocharge AI for the next two or three decades to come.

      BTW: This may be the reason why a university system as the Austrian is so fascinated by AI.

  5. May 2023
  6. Apr 2023
    1. My fear is that countless people are already using ChatGPT to medically diagnose themselves rather than see a physician. If my patient in this case had done that, ChatGPT’s response could have killed her.

      More ELIZA. The opposite of searching on the internet for your symptoms and ending up with selfdiagnosing yourself with 'everything' as all outliers are there too (availability bias), doing so through prompting generative AI will result in never suggesting outliers because it will stick to dominant scripted situations (see the vignettes quote earlier) and it won't deviate from your prompts.

  7. Jun 2021
  8. Feb 2020
    1. I began now seriously to reflect upon what I had done

      This seems like a huge contrast to the story of Fantomina, where she seemingly never reflects upon why she is pursuing sir Beauplaisir and feels no shame in constantly scamming him. This can be noted in the story where she immediately leaves the place she's staying at when she hears Beauplaisir leaves “and in that Time provided herself of another Disguise to carry on a third Plot”. Here Fantomina doesn't give her plan of scamming him a second thought, and displays absolutely no remorse. The juxtaposition of both of these characters and their stories demonstrate how distinct these stories truly are. In Fantomina, we see a very different type of story, completely apart from stories that existed at that time. Robinson crusoe seems to have more of a traditional story vibe, having aspects that reflect the bible. Robinson Crusoe demonstrates how some early novels still maintained traits from traditional literatures and Fantomina demonstrates the beginning of distinct genres and perspectives coming into play within the narrative.

      Haywood, Eliza. “Fantomina.” Fantomina: Or, Love in a Maze., digital.library.upenn.edu/women/haywood/fantomina/fantomina.html. Mowat, Diane, and Daniel Defoe. Robinson Crusoe. Oxford University Press Canada, 2008.