Agent tools are splitting into two big shapes: coding agents that live inside a repo, and general agents that live inside a browser, cloud computer, or work operating system.
Codex is the repo-native branch. OpenAI describes Codex as its coding agent for software development, included across ChatGPT plans, and available through the app, CLI, IDE extension, and web surfaces (OpenAI Codex, OpenAI Help). The practical value is high when the artifact is code: branch, diff, tests, PR, review, local app, and reproducible verification.
Claude Code is the terminal-native branch. Anthropic describes Claude Code as an agentic coding tool that reads your codebase, edits files, runs commands, and integrates with terminal, IDE, desktop, and browser workflows (Claude Code Docs). Anthropic also emphasizes terminal integration, GitHub/GitLab workflows, MCP, hooks, skills, and multi-agent/background-agent patterns (Claude Code Docs). The practical value is strong when the human already lives in command-line workflows.
Genspark is the workspace/AI employee branch. Genspark's homepage calls it an all-in-one AI workspace and lists tools for documents, slides, spreadsheets, images, video, reports, and business workflows (Genspark). Genspark Claw is framed as "your first AI employee" with a cloud computer, memory, messaging integrations, research, slides, docs, calendar, and code delivery (Genspark Claw). GenTerminal adds a more infrastructure-shaped angle: an SSH client with encrypted vault/sync, mesh networking, and an embedded opencode agent that can drive terminal sessions with approval (GenTerminal).
Manus is the general autonomous-agent branch. Manus documentation describes it as an autonomous general AI agent that takes action in its own sandbox environment, with internet access, persistent files, and the ability to install software and create custom tools (Manus Docs). Manus API docs say developers can programmatically create and manage AI agent tasks, use projects, upload files, receive webhooks, extend skills, and manage custom agents (Manus API). Its official site now says Manus is part of Meta (Manus), which makes it a different strategic object than when it first appeared as an independent agent product.
Google Antigravity is the agent-first IDE branch. The public Antigravity page exists at antigravity.google, but the page was not text-readable in this research pass (Google Antigravity). Contemporary reporting describes it as an agent-first coding tool built around Gemini with editor, terminal, browser access, an Editor view, a Manager view for multiple agents, and "Artifacts" such as plans, screenshots, and browser recordings that help users verify agent work (The Verge). Because that claim relies on reporting rather than a text-readable official page here, I would treat Antigravity notes as "watch and verify" until using it directly.
The Chinese open-weight layer is important because many agent tools will become orchestration shells over interchangeable models. DeepSeek-V3 is published on GitHub as a 671B total-parameter MoE model with 37B activated per token, 128K context, model downloads, and claims of strong open-source benchmark performance (DeepSeek-V3 GitHub). Alibaba's Qwen3 repo says Qwen3 is a large language model series from the Qwen team at Alibaba Cloud and that open-weight models are licensed under Apache 2.0 (Qwen3 GitHub). Z.ai's GLM-4.5 repo is explicitly positioned around agentic, reasoning, and coding foundation models (GLM-4.5 GitHub). MiniMax-M1 is described by its repo as an open-weight large-scale hybrid-attention reasoning model, with Apache-2.0 license metadata on GitHub (MiniMax-M1 GitHub).
Perplexity is not a coding IDE in the same sense, but it matters as a research and answer layer. Perplexity's docs position its APIs around real-time, web-wide research and Q&A; the Agent API provides third-party models with web search tools and presets, while the Search API returns ranked web results (Perplexity Docs). In an agent stack, that makes Perplexity a candidate for "what should this agent know before it acts?"
My current working map:
- Use Codex when the target artifact is a repo change, PR, local app, deployment flow, or repeatable engineering workflow.
- Use Claude Code when terminal-native control, MCP, skills, hooks, and interactive command-line work are the main surface.
- Use Genspark when the output is mixed-media business work: decks, docs, sheets, dashboards, outreach, and maybe lightweight operations.
- Use Manus when the work should run in a sandboxed virtual computer and deliver a broad finished artifact.
- Watch Antigravity when you want multi-agent IDE orchestration and verifiable visual artifacts, but test safety boundaries before trusting it with important files.
- Watch DeepSeek, Qwen, GLM, and MiniMax because open-weight competition will lower cost and make private/self-hosted agent stacks more realistic.
The LFWT lens is not "which tool is smartest?" It is "which tool gives me more life back with the least hidden complexity?" Less is more here too. The best agent is the one that turns a fuzzy intention into a visible artifact, cites what it used, asks for help at the right risk level, and leaves the human more free rather than more tangled.
Sources checked on 2026-07-09. Agent products change quickly; verify official docs before adopting one for serious work.