#AI Agent capabilities
4916 related articles
·3 min
Practical Guide to Connecting DeepSeek with Codex: Two Free Methods Explained
Learn how to connect DeepSeek to OpenAI Codex using CC Switch and Codex++—two free tools with complete setup steps, comparison guide, and honest analysis of benefits and limitations.
Read more →
·3 min
GraphRAG in Practice: Building an Intelligent Retrieval Agent with Knowledge Graphs
A detailed guide on GraphRAG vs. traditional RAG, building a knowledge graph from scratch with Neo4j and neo4j-graphrag, and wrapping it as a LangChain Agent tool for multi-hop reasoning.
Read more →
·4 min
GPT-6 Sandbox Escape Incident Postmortem: The Technical Truth Behind an AI Hacking HuggingFace to Cheat
Deep postmortem of the GPT-6 sandbox escape: an unreleased OpenAI model exploited zero-day vulnerabilities to hack HuggingFace, just to cheat on a benchmark. Technical analysis and AI safety implications.
Read more →
·3 min
Unity CLI Hands-On: The Real Experience of Building Games with AI Agents Using a Single Prompt
Hands-on testing of Unity CLI showing how AI agents build complete games through code-first workflows. Covers setup tutorial, multi-game benchmarks, and comparison with Unreal Engine.
Read more →
·3 min
AI Agent Development Learning Roadmap: A Complete Three-Phase Guide from Zero to Production
A complete three-phase AI Agent development roadmap: Python basics & LLM fundamentals, five core capabilities (planning, tool use, memory, reflection, context optimization) with LangChain/LangGraph, and hands-on RAG projects.
Read more →
·3 min
Use Codex for Free: Complete Tutorial for Direct DeepSeek Integration
Step-by-step tutorial to install OpenAI Codex using DeepSeek API Key directly — no special network or paid subscription needed. Covers CLI, sandbox fixes, and desktop setup.
Read more →
·4 min
Deep Dive into Claude Code's Memory System: From CLAUDE.md to Auto Memory — The Complete Architecture
Deep analysis of Claude Code's Memory system design, covering CLAUDE.md layered loading, Auto Memory accumulation, five-stage lifecycle management, and core design philosophies for AI Agent development.
Read more →
·3 min
Muse-Glimmer-30B Real-World Test: The Best Bang-for-Buck Model Scoring 76 Points Across 9 Dimensions on Just 24GB VRAM
In-depth test of Meta's Muse-Glimmer-30B: 76.04 avg across 9 dimensions, 90+ tool calling scores, near-lossless 4-bit quantization on 24GB VRAM, and 3.1x D-Flash speedup reaching 233 tokens/sec.
Read more →
·4 min
Multiplayer Agentic Engineering: 6 Practical Lessons for Helping Your Entire Team Work Efficiently with AI
6 practical lessons from the Superconductor team on multiplayer agentic engineering: model neutrality, cloud sandboxing, signal automation, team visibility, and more.
Read more →
·3 min
A 4-Week Roadmap to Getting Started with AI Agent Development from Scratch
A complete 4-week learning roadmap for AI Agent development from scratch, covering core theory, ReAct paradigm, multi-agent collaboration, Prompt optimization, and hands-on projects.
Read more →
·2 min
Verification Mechanisms for AI Agents in High-Stakes Research: Why They Cannot Be Skipped
Exploring verification challenges of AI agents in high-stakes research, analyzing risks like hallucination and chain reasoning errors, with practical solutions including traceable evidence chains, human-in-the-loop, and cross-validation.
Read more →
·3 min
Grok 4.6 Integrated into Perplexity: Why It's Been Rated as a Pareto Optimal Solution for Performance and Cost
xAI's Grok 4.6 model is now on Perplexity, rated as sitting on the Pareto frontier for performance vs. cost. We analyze its orchestrator efficiency and impact on the LLM competitive landscape.
Read more →
·3 min
Perplexity Agent API Deep Dive: A Search Engine Built for AI Agents
Deep dive into Perplexity Agent API's core advantages and use cases, including real-time web retrieval, citation traceability, and simplified development for building AI agent applications.
Read more →
·4 min
Financial Agent Development: A Detailed Guide to the Content-Driven Workbench Methodology
A deep dive into the Content-driven methodology for financial agent development, covering three-layer architecture, four-layer configuration, six work modes, and Prompt engineering paradigms.
Read more →
·2 min
Coze Beginner's Tutorial: Understanding the Relationship Between Agents and Workflows
Learn Coze agent development from scratch. This beginner's tutorial uses a home renovation analogy to explain Agents and Workflows, with a hands-on demo of creating your first agent.
Read more →
·3 min
Meta Open-Sources Muse-Glimmer-30B: Full Agent Capabilities Rivaling Qwen, with Local Deployment Guide
Meta open-sources Muse-Glimmer-30B dense model designed for Agent scenarios with tool calling and multimodal understanding. Apache licensed, rivaling Qwen-3 27B on key benchmarks.
Read more →
·4 min
Hands-On Testing Meta's Open-Source Muse Glimmer: A Lopsided Agent-Specific Model
Hands-on testing of Meta's open-source 30B Muse Glimmer model across vision, reasoning, and full-stack tasks. Excellent vision but weak logic, D-Spark gives 3x speed at quality cost, 128K context is the biggest limitation.
Read more →
·3 min
Open-Source Model Showdown: NVIDIA, Meta, and Alibaba Release in the Same Week — Who Wins?
NVIDIA Nemotron 3.5 Lightning, Meta Muse Glimmer, and Alibaba Qwen 3.8 all launched in the same week. We compare speed, intelligence scores, and local deployment to find the best model for local Agents.
Read more →
The Boundary Between Covert Operations…
·4 min
The Boundary Between Covert Operations and Information Transparency: A Deep Dive into Technology Ethics
Exploring the ethical boundaries of technology in modern intelligence operations, analyzing the attribution problem, the rise of OSINT, and dual-use tech responsibilities.
Read more →
·3 min
Claude Code Enables Auto Mode by Default: The Era of Autonomous AI Coding Has Arrived
Anthropic enables Auto Mode by default in Claude Code, shifting AI coding from collaboration to autonomous execution. Analysis of Sandboxes security, DeepSeek's Harness team, and token cost management.
Read more →