Articles

🏠 Home · 📚 Reading Notes · ℹ️ About

Drafts in progress

	Article	Topics	Status	Summary
	How to Make $10k-Month With AI Agents (Reddit)	career, ai-ml	draft	Reddit post: a self-described mediocre developer's playbook for building a $10k+/month AI-agent consulting/service business for local small businesses — client types, pricing, sales process, and honest failure-mode notes.
	The AI Consciousness Debate Needs Better Vocabulary	ai-ml, consciousness, philosophy-of-mind	draft	The LLM consciousness debate is stuck because the popular discourse lacks the architectural vocabulary to ask the right questions. Starting from two things heard in the same week (Coconut on Last Week in AI, Dawkins/Novella on SGU), this piece follows the thread without landing a conclusion.
	Industrial AI Optimizer Data Pipeline	AI , AI Optimizer, Industrial AI	draft	Outline of an industrial AI optimizer pipeline: extracting sensor data from PI, ingesting it into AWS via S3 or Kinesis,

transforming raw logs into clean Delta/Parquet datasets with Glue or Databricks, storing them in a structured medallion architecture,
and delivering them to Kubeflow for data science workflows. |

Recently touched articles

	Article	Topics	Status	Summary
	How to Make $10k-Month With AI Agents (Reddit)	career, ai-ml	draft	Reddit post: a self-described mediocre developer's playbook for building a $10k+/month AI-agent consulting/service business for local small businesses — client types, pricing, sales process, and honest failure-mode notes.
	The AI Consciousness Debate Needs Better Vocabulary	ai-ml, consciousness, philosophy-of-mind	draft	The LLM consciousness debate is stuck because the popular discourse lacks the architectural vocabulary to ask the right questions. Starting from two things heard in the same week (Coconut on Last Week in AI, Dawkins/Novella on SGU), this piece follows the thread without landing a conclusion.
	Industrial AI Optimizer Data Pipeline	AI , AI Optimizer, Industrial AI	draft	Outline of an industrial AI optimizer pipeline: extracting sensor data from PI, ingesting it into AWS via S3 or Kinesis,

transforming raw logs into clean Delta/Parquet datasets with Glue or Databricks, storing them in a structured medallion architecture,
and delivering them to Kubeflow for data science workflows. |