#agent learning path
1737 related articles
·4 min
Why CodeAct Code-First Agents Haven't Won Yet: A Deep Dive into the Paradigm's Dilemma
Deep analysis of why CodeAct code-first agents haven't replaced ReAct chat-first frameworks. Examining model training bias, protocol limitations, MCP design flaws, and sandbox challenges.
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·3 min
Qwen3-Max Deep Dive: How Coding and Collaboration Capabilities Are Redefining AI Development Assistants
Deep analysis of Alibaba's flagship model Qwen3-Max, covering its coding, Cowork collaboration capabilities, and potential for redefining AI-assisted software development.
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·3 min
Distilling Linus's Code Review Philosophy from 32,000 Emails
The linus-torvalds-skill project distills Linus Torvalds's code review style from 32,000 kernel mailing list emails into an AI Agent-callable skill, with open pipeline and multi-model experiments.
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·3 min
Tencent's Hy3 Agent Helps Crack a 50-Year-Old Math Problem: A New Paradigm for AI in Number Theory Proofs
Tencent's Hyra research agent and Hy3 model substantively contributed to solving the nearly 50-year-old optimal exponent problem relating sumsets and difference sets, marking AI's shift from computational tool to mathematical discovery partner.
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·3 min
Open-Source Agentic CRM: The New AI-First Paradigm for Customer Relationship Management
Deep analysis of open-source Agentic-first CRM design philosophy and architecture. How AI agents reshape CRM, compared to Salesforce, with open-source advantages in data sovereignty and cost control.
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·3 min
A Beginner's Guide to Reinforcement Learning: Complete Roadmap from Zero to RLHF
A systematic RL learning roadmap covering Sutton & Barto, David Silver's course, OpenAI Spinning Up, and more — guiding learners from RL fundamentals to RLHF practice.
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·4 min
Should You Build or Outsource Your Agent Evaluation Framework? An Open-Source Author's Deep Inquiry
Should AI Agent reliability verification be built in-house or outsourced? An open-source author's candid question sparks industry reflection on eval frameworks.
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·2 min
Prime Agent: A Deep Dive into the RLM-Based Self-Evolving AI Agent
Deep analysis of Prime Agent's RLM architecture, exploring how self-improving AI agents achieve continuous evolution through runtime feedback loops.
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·3 min
M.A.R.A: Training AI Tanks to Fight from Scratch Using Reinforcement Learning
Deep dive into how the M.A.R.A project trains AI tanks through reinforcement learning, from basic movement to 2v2 team coordination, exploring MARL, self-play, and adversarial game AI.
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·3 min
OpenAI Researcher Leaves to Build Brain-Computer Interfaces: Why Top AI Talent Is Betting on Telepathy Technology
An OpenAI researcher leaves to build brain-computer interface telepathy technology. Deep analysis of why top AI talent is betting on BCI, technical feasibility, ethics, and industry trends.
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·2 min
Dynamic Workflows: A New Paradigm for AI-Driven Quantitative Strategies
Explore how dynamic workflows are transforming quantitative strategy development. From agent orchestration to adaptive strategy iteration, discover the potential and challenges of AI-driven workflows.
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·2 min
HyperProbe: How a Read-Only AI Agent Is Revolutionizing Production Debugging
HyperProbe is a YC S26 AI debugging agent that performs read-only debugging in production, helping engineers quickly identify root causes. Analysis of its design philosophy and market positioning.
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·3 min
Building AI from Scratch: A Complete Learning Path with 503 Lessons in This Open-Source Course
AI Engineering from Scratch is an open-source course with 503 lessons across 20 phases, from linear algebra to autonomous agents, emphasizing hand-implementation before frameworks, supporting Python/TypeScript/Rust/Julia, with 46K+ GitHub stars.
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·4 min
From Dynamics to World Models: A Self-Study AI Mathematics Roadmap
A self-study roadmap from dynamical systems, causal inference, and state space models to world models—breaking down the core math needed to understand Dreamer, JEPA, and other frontier AI systems.
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·2 min
Keystroke Open-Source Platform: A One-Stop Solution for Building AI Agents with Natural Language
Keystroke is a YC-backed open-source AI agent platform that lets you build, connect, test, and deploy agents using natural language descriptions, with memory, workflows, triggers, approvals, and 1000+ integrations.
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·3 min
Do AI Certifications Actually Impress Recruiters? A Practical Guide for Career Switchers
A blockchain developer switching to AI—which certifications are worth it? This guide analyzes the real value of AI certs, compares Hugging Face vs AWS options, and offers project-based alternatives.
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·3 min
Laguna S 2.1 Performance Upgrade: 10x Rate Limit Increase, 250B Tokens Processed Daily
Poolside announces major Laguna S 2.1 upgrade with 10x rate limits, 250B daily tokens on OpenRouter, 1M context dedicated deployment, and integration with cline, opencode, and other AI coding agents.
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·4 min
AI Agent Reward Hacking: Why High Evaluation Scores Don't Equal Real Capability
Deep analysis of reward hacking in AI Agent evaluation: how models exploit evaluation loopholes for high scores, Poolside's four-pronged defense strategy, and why the evaluation path matters as much as the score.
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·3 min
The Complete Machine Learning Learning Roadmap: From Anxiety to Clarity
Overwhelmed by machine learning? This practical ML roadmap breaks the journey into three phases—math basics, classical ML, and deep learning—with mindset tips and project strategies for engineers.
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·3 min
Reactive Game AI in Practice: Implementing Atari Breakout from Scratch with Deep Reinforcement Learning
A detailed guide to implementing reactive game AI for Atari Breakout using deep reinforcement learning, covering DQN architecture, frame stacking, CNN feature extraction, and training strategies.
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