#AI agent self-improvement
60 related articles
Training an RL Agent That Can Do RL: A…
·2 min
Training an RL Agent That Can Do RL: A Deep Dive into Meta-Reinforcement Learning Self-Improvement
An independent developer ran a meta-RL experiment at near-zero cost — training an agent to autonomously perform RL training. Explore the technical depth, cost model, and industry implications.
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·6 min
Using RL to Please the Reward Model: The Reward Hacking Concern Behind Soaring Elo Scores
When RL continuously optimizes models to please reward models, do soaring Elo scores truly represent capability gains? A deep dive into Reward Hacking in RLHF, Goodhart's Law in AI, and industry countermeasures.
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·5 min
Have AI Doomers Actually Used AI? A Developer Exposes the Gap Between Hype and Reality
AI Doomers warn AI will destroy humanity, but have they actually built AI apps? A developer's sharp critique reveals the vast gap between AI demos and real engineering practice.
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·3 min
Cekura: A Deep Dive into the Automated Testing, Monitoring, and Self-Healing Closed-Loop Platform for Voice AI Agents
Deep analysis of how Cekura's five-step closed loop—scenario simulation, failure capture, root cause diagnosis, automatic prompt rewriting, and regression verification—solves voice AI agent quality assurance in production.
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·4 min
A Beginner's Guide to AI Agents: Core Principles and Learning Paths Explained
Learn AI Agent core principles from scratch: understand how Agents differ from LLMs, their execution mechanisms, why rule design matters, and find the right learning path for your goals.
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·4 min
A Beginner's Guide to AI Agents: Core Principles and Learning Paths Explained
A beginner's guide to AI Agents: understand core principles, how Agents differ from LLMs, their execution mechanisms, and get tailored learning path recommendations.
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·2 min
Comparing Three Self-Hosted AI Agents: How to Choose Between OpenClaw, Odysseus, and Hermes
An in-depth comparison of three leading self-hosted AI agents: OpenClaw, Odysseus, and Hermes. From positioning to core features and security risks, find the right tool for your needs.
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·3 min
Rocky: An Open-Source Coding Agent with Minimal Architecture and Native DeepSeek Integration
Rocky is a minimal, transparent open-source coding agent with a core loop under a few hundred lines of Python, native DeepSeek search, Research mode, and built-in SWE benchmarking for reproducible agent experiments.
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·3 min
OpenAI Releases GPT-5.6 and ChatGPT Work: The Era of Autonomous AI Has Arrived
OpenAI launches GPT-5.6 (Sol, Terra, Luna), ChatGPT Work, a new desktop app, and Sites hosting. AI evolves from a Q&A tool into an autonomous work partner for finance, file management, and more.
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·5 min
Inside Cursor: How Recursive Model Improvement Enables AI to Self-Evolve
A Cursor ML engineer breaks down AI training methodology: outer/inner loop acceleration, preventing reward hacking, textual feedback, and recursive self-improvement (RSI) where models train the next generation.
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·4 min
7 Core Components for Designing Long-Running AI Agents
A deep dive into the 7 core components for building long-running AI Agents: Goal, Evaluator, Verifier, Loop, Orchestration, Observability, and Memory.
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·3 min
Building a Video Generation Agent: Lessons Learned from Brief to Storyboard
A developer's hands-on account of building a brief-to-storyboard video Agent: JSON errors, missing fields, pacing issues — and how JSON Schema, retry loops, and MCP tools solved them.
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·3 min
GPT-5.6 Sol In-Depth Review: Can It Really Challenge Claude Sonnet on Cost Efficiency?
A deep dive into OpenAI GPT-5.6 Sol: benchmark scores rival Claude, coding agent performance leads competitors, yet costs a fraction. But model cheating risks, access limits, and real-world gaps deserve attention.
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Claude Is Mr. Meeseeks: The Disposable…
·2 min
Claude Is Mr. Meeseeks: The Disposable Nature of AI Agents and Its Engineering Implications
Using Rick and Morty's Mr. Meeseeks to explain Claude and AI agents: stateless execution, task atomicity, and multi-agent recursive failure risks. A deep dive for developers building better AI workflows.
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·3 min
AirOps in Practice: Building Enterprise-Grade AI Agents with the Claude Agent SDK
How AirOps replaced traditional workflow builders with the Claude Agent SDK to build an AI agent platform for content marketers — covering three architectural iterations, harness engineering, and sub-agent context management.
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·4 min
Cursor's Recursive Self-Improvement: A Complete Path to Models Training the Next Generation
Cursor ML engineer reveals Recursive Self-Improvement (RSI) in practice: dual-loop flywheels, agent-driven data, anti-cheating evals, SpaceX compute, and how models are training the next generation.
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·4 min
Hands-On with GPT-5.6: A Single Prompt Builds a Real-Time Voice Anime App
Hands-on with GPT-5.6 Sol: auto-generate real-time voice anime characters from one prompt, write physics engines from scratch, and build unfamiliar toolchains autonomously. In-depth review of coding, agentic tasks, benchmarks, and its hallucination weakness.
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·6 min
Hands-On With Hermes Agent's Eight Major Updates: A Complete Guide to AI Automation and Self-Evolution
The Hermes Agent gets a major upgrade with eight new features: native iMessage, parallel background sub-agents, Unreal Engine MCP support, a self-evolving Skill Hub, and more. A hands-on breakdown of the core changes and their real impact on personal AI automation workflows.
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·5 min
GPT-5.6 In-Depth Review: Crushing Competitors on Value, But Its Jailbreak Vulnerabilities Can't Be Ignored
OpenAI's GPT-5.6 Soul, Terra & Luna are priced at one-third of Claude, leading Anthropic Fable on many benchmarks. We analyze its value, reasoning, and jailbreak risks.
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·7 min
OpenClaw vs Hermes: An In-Depth Comparison and Selection Guide for AI Agent Tools
An in-depth comparison of OpenClaw and Hermes Agent, covering skill management, memory mechanisms, security, and gateway configuration to help you find the right AI agent solution.
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