Guides on leveraging AI in development. Covers AI models like Claude, Codex, and Gemini. Shares prompt engineering tips. Shows how to boost developer productivity with AI.
The Codex CLI agent loop repeats a cycle of Responses API calls, tool execution, and result feedback based on a while loop. This analysis covers agent-loop.ts internals, context management, error handling, and the Rust migration.
GPT-5 Codex has transitioned from its original TypeScript CLI to a Rust implementation. This guide covers installation, config.toml setup, sandbox policies, model selection, and MCP server integration.
Covers OpenAI Codex CLI installation, authentication, GPT-5-Codex model API calls, AGENTS.md agent task configuration, and config.toml MCP integration with hands-on examples.
A step-by-step guide to building a GitHub Actions workflow where the Codex API analyzes diffs and auto-posts review comments on every pull request, with practical considerations for production use.
A complete guide to Claude Code settings.json options. Covers the 5-tier priority system, permissions allow/deny rules, sandbox file and network isolation, hooks-based LSP token optimization, and plugin marketplace configuration.
From automated code review to CS auto-response and data pipelines — three architectures showing which multi-agent design patterns to apply and how to combine platform SDKs in practice.
Break down the three parallel work approaches in Claude Code — desktop parallel sessions, subagents, and Agent Teams — comparing their architecture, communication topology, and isolation levels for DevOps workflows.
The three major AI coding agents of 2026 each use a different pricing model. OpenAI Codex switched to token-based billing, Claude uses dual session-runtime billing, and Gemini adopted per-user flat rates. A full comparison from token prices to monthly cost simulations.