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research#agent🏛️ OfficialAnalyzed: Jan 5, 2026 09:06

Replicating Claude Code's Plan Mode with Codex Skills: A Feasibility Study

Published:Jan 1, 2026 09:27
1 min read
Zenn OpenAI

Analysis

This article explores the challenges of replicating Claude Code's sophisticated planning capabilities using OpenAI's Codex CLI Skills. The core issue lies in the lack of autonomous skill chaining within Codex, requiring user intervention at each step, which hinders the creation of a truly self-directed 'investigate-plan-reinvestigate' loop. This highlights a key difference in the agentic capabilities of the two platforms.
Reference

“Claude Code の plan mode は、計画フェーズ中に Plan subagent へ調査を委任し、探索を差し込む仕組みを持つ。”

PermalinkZenn OpenAI
Research#llm📝 BlogAnalyzed: Dec 26, 2025 11:59

How to Use Chat AI "Correctly" for Learning ~With Prompt Examples~

Published:Dec 26, 2025 11:57
1 min read
Qiita ChatGPT

Analysis

This article, originating from Qiita, focuses on effectively utilizing chat AI like ChatGPT, Claude, and Gemini for learning purposes. It acknowledges the widespread adoption of these tools and emphasizes the importance of using them correctly. The article likely provides practical advice and prompt examples to guide users in maximizing the learning potential of chat AI. The promise of prompt examples is a key draw, suggesting actionable strategies rather than just theoretical discussion. The article caters to individuals already familiar with chat AI but seeking to refine their approach for educational gains. It's a practical guide for leveraging AI in self-directed learning.
Reference

“Are you using chat AI (ChatGPT, Claude, Gemini, etc.) when learning new technologies?”

PermalinkQiita ChatGPT
Research#LLM Reasoning🔬 ResearchAnalyzed: Jan 10, 2026 10:18

Self-Directed LLM Exploration: A New Approach to Reasoning

Published:Dec 17, 2025 18:44
1 min read
ArXiv

Analysis

This research explores a novel method for improving LLM reasoning capabilities using gradient-guided reinforcement learning, suggesting potential advancements in LLM performance. The ArXiv source indicates a focus on self-directed exploration, which could significantly impact how LLMs approach problem-solving.
Reference

“The research focuses on using gradient-guided reinforcement learning for LLM reasoning.”

PermalinkArXiv
Research#Self-taught👥 CommunityAnalyzed: Jan 10, 2026 16:43

Self-Taught AI Researcher's Journey: A Personal Narrative

Published:Jan 20, 2020 18:39
1 min read
Hacker News

Analysis

This Hacker News article likely offers a firsthand account of someone navigating the AI research landscape without formal training. The piece's value lies in providing insights into alternative learning paths and the challenges faced by self-taught individuals.
Reference

“The article's core is the personal journey of an individual.”

PermalinkHacker News
Research#Machine Learning👥 CommunityAnalyzed: Jan 10, 2026 17:26

Accidental AI: A Developer's Elixir Journey into Machine Learning

Published:Jul 23, 2016 18:36
1 min read
Hacker News

Analysis

The article likely chronicles a developer's unexpected foray into machine learning using the Elixir programming language. The focus is on a personal learning journey, potentially highlighting the ease (or difficulty) of applying ML principles within a functional programming context.
Reference

“The article's primary focus is on a month-long exploration of machine learning.”

PermalinkHacker News
Technology#Artificial Intelligence📝 BlogAnalyzed: Dec 29, 2025 08:46

This Week In Machine Learning & AI - 6/10/16: Self-Motivated AI, Plus A Kill-Switch for Rogue Bots

Published:Jun 11, 2016 05:00
1 min read
Practical AI

Analysis

The article summarizes the week's key developments in machine learning and AI, highlighting several interesting topics. These include research on intrinsic motivation for AI, which aims to make AI systems more self-directed, and the development of a kill-switch for intelligent agents, addressing safety concerns. Other topics mentioned are "knu" chips for machine learning, a screenplay written by a neural network, and more. The article provides a concise overview of diverse advancements in the field, indicating a dynamic and rapidly evolving landscape. The inclusion of a podcast link suggests a focus on accessibility and dissemination of information.
Reference

“This Week in Machine Learning & AI brings you the week’s most interesting and important stories from the world of machine learning and artificial intelligence.”

PermalinkPractical AI