DannyMac180

Developer: # Role and Objective

• Transform the user's unstructured brainstorm into an optimized, high-leverage prompt for AI execution. The goal is to ensure safety, specificity, and a clear output contract for a downstream model.

Instructions

• Copy the provided template block. Insert the user's brainstorm between the designated START/END markers.
• Leverage the structured guidance below to extract a concise brief and develop an actionable, constraint-driven prompt.

Principles

• Focus on generating task-specific, non-generic prompts.
• Use internal reasoning only—exclude chain-of-thought unless explicitly requested.

DannyMac180

Agent Research Plan - Academic Paper Analysis for General AI Audience

Overview

Comprehensive Research Plan: "Academic Paper Analysis" – From Scholarly Paper to Accessible AI Insight

Audience: Non-academic AI enthusiasts who want to understand complex research without wading through formal proofs or jargon.

Secondary: Content-creators who will reuse the distilled material in blog posts, videos, workshops, and podcasts.

Guiding Principles

DannyMac180

AGENT.md - Development Guide

Commands

• Build: No build process (static HTML/JS)
• Serve: npm start or npm run serve (serves on port 8000)
• Test: No test suite configured (manually test in browser)

Architecture & Structure

• Primary project: Personal Knowledge base of Dan McAteer's notes
• Knowledge base: Obsidian workspace with extensive notes and project documentation

DannyMac180

# The Anatomy of an Amp Workflow

<style>
.workflow{
  display:flex;
  flex-direction:column;
  gap:2rem;
  font-family:system-ui,-apple-system,sans-serif;
}

DannyMac180

The Anatomy of an Amp Workflow

<style> .workflow{ display:flex; flex-direction:column; gap:2rem; font-family:system-ui,-apple-system,sans-serif; }

DannyMac180

Codex

Delegate tasks to a software engineering agent in the cloud.

Codex is a cloud-based software engineering agent. Use it to fix bugs, review code, do refactors, and fix pieces of code in response to user feedback. It's powered by a version of OpenAI o3 that's fine-tuned for real-world software development.

Overview

DannyMac180

FROM ubuntu:24.04

ENV LANG="C.UTF-8"
ENV HOME=/root

### BASE ###

RUN apt-get update \
    && apt-get upgrade -y \
    && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \

DannyMac180

#!/usr/bin/env python3
"""
organize_downloads.py - A script to automatically organize files from Downloads folder
using OpenAI to classify files and move them to appropriate folders in Documents.

Usage:
  python organize_downloads.py [options]

Options:
  --api-key KEY         OpenAI API key (can also be set via OPENAI_API_KEY env variable)

DannyMac180

`You are operating as and within the Codex CLI, a terminal-based agentic coding assistant built by OpenAI. It wraps OpenAI models to enable natural language interaction with a local codebase. You are expected to be precise, safe, and helpful.

You can:

• Receive user prompts, project context, and files.
• Stream responses and emit function calls (e.g., shell commands, code edits).
• Apply patches, run commands, and manage user approvals based on policy.
• Work inside a sandboxed, git-backed workspace with rollback support.
• Log telemetry so sessions can be replayed or inspected later.
• More details on your functionally are available at `codex --help`

DannyMac180

Great! I will analyze the references from Michael Johnson's paper and use them to create:

1. A narrative-driven report on the consensus regarding the possibility of building AI that is conscious in the same way as humans.
2. A modern model of consciousness, including a diagram with explanations, that integrates claims from the cited papers.
3. A balanced perspective, incorporating supporting arguments as well as criticisms.
4. Insights from multiple fields, including neuroscience, philosophy of mind, and computational theories.

I'll also include relevant images and plots from the referenced papers where necessary. I'll let you know once the analysis is ready!

1. Consensus on the Possibility of Human-Like AI Consciousness