Best AI Harnesses (2026)

The best OpenCode alternatives are the terminal coding agents developers say they moved to in blog posts and Hacker News threads, checked against independent hands-on reviews. If OpenCode feels bloated, get Pi, or oh-my-pi if you want Pi with the tools already built in. If you want one vendor's best models at a flat monthly price, get Claude Code or Codex CLI. That is the real OpenCode vs Claude Code difference: Claude Code runs only Claude models, OpenCode any provider. Codex sandboxes commands by default. For open source with any model and no single company in charge, get goose. For the nicest terminal interface, Crush. For an agent that asks before every edit, Cline CLI. To pay nothing for models, Freebuff, which shows ads. For a desktop app that runs any model, DeepSeek Harness. If you pay for GitHub Copilot, its CLI is included. OpenCode Go, the $10 model plan, also works in Pi, Claude Code and Codex. What the makers' pages won't tell you. On October 17, 2026 attackers broke into an older OpenCode system and reached provider keys saved in OpenCode Console, affecting 1.4% of Console users. TechCrunch reports charges above $1,000 on some accounts, and OpenCode's co-founder says the app and CLI were not affected. Revoke a saved key at the provider: deleting it in OpenCode doesn't stop a stolen copy. OpenCode 2 has a new plugin API, so OpenCode 1 plugins don't run on it. Crush grew out of an older Go project also called OpenCode, and its license is source-available, not open source. Gemini CLI stopped serving personal accounts on June 18, 2026; Antigravity CLI replaced it. Aider has had no commits since May 22, 2026. Kilo CLI is built on OpenCode, so switching to it changes little. A free agent still needs a model: you pay a provider per token or run one yourself. The list is ordered by how many independent developers and reviewers recommend each agent, then by GitHub stars, then by price. Prices checked October 24, 2026.

The best AI coding plans give your coding agent a month of strong models for a flat fee, often a tenth of Claude Max. These picks rest on hands-on reviews by KDnuggets, Bitdoze, Tony Reviews Things and Hacker News developers. For the most models for the least money, start with OpenCode Go at $10 a month. For one strong open model all day, the GLM Coding Plan or MiniMax's M Plan. For open models with zero data retention, Ollama Cloud. If you already pay for ChatGPT, Codex is included, and the same plan now signs in to OpenCode, Pi and Kilo Code. To reach Claude and GPT models from OpenCode for $10, GitHub Copilot Pro. The cheapest coding plans are Xiaomi MiMo at $6, Alibaba's Qwen Token Plan at $8 and Synthetic at $9. The open-model plans here also run inside Claude Code through an Anthropic-compatible endpoint. GLM vs Kimi vs MiniMax coding plan: in an April head-to-head in the Pi agent by Lotus Creation Concepts, GLM gave the best result and MiniMax ran fastest, and Reddit users say Kimi K3 burns its quota quickest. What the makers' pages won't tell you. Most of these plans changed in 2026. Z.ai moved the GLM plan to credits, and the quota works only in the tools it lists. MiniMax replaced its Token Plan with M Plan, whose text model is M3.1 Flash. Anthropic covers OpenCode, Pi and other agents only through a separate monthly credit billed at API rates. Copilot meters chat and agent work in AI credits. OpenCode Go, Ollama Cloud and Copilot give a dollar allowance at token prices, so a flagship like Kimi K3 drains it fastest. Z.ai's and Alibaba's discounted hours fall in the American daytime. Ordered by how many named hands-on reviews back each plan, then by how many developers recommend it on Hacker News and Reddit, then by price, lowest first. Prices checked October 24, 2026.

The OpenClaw skills worth installing, for email, code, notes and browsing, each checked against its source and its ClawHub security audit. For email and calendar, start with Gog. For code, GitHub. For long articles, videos and podcasts, Summarize. For notes, Obsidian or Notion. To stop the agent repeating a mistake, self-improving agent. For cleaner prose, Humanizer. Safety first. ClawHub, the registry, lets anyone with a GitHub account publish, and a skill acts with whatever access your agent has. Security firms have counted more than a thousand malicious skills there since January 2026, and in June Unit 42 and Trail of Bits each showed skills getting past its scanners. OpenClaw's own June data labelled 25,504 of 67,453 skill versions suspicious and 206 malicious. Every skill page now has a security audit with an outcome such as Pass or Review. Read it, and the SKILL.md, before you install. Older guides are out of date in three ways. Most of the skills they tell you to install now ship with OpenClaw and switch on when their command-line tool is present. Web search, self-learning and memory search are built in, and Tavily has a first-party plugin, so the Tavily and QMD skills are no longer needed. And names are copied: at least five publishers use the slug gog, so install with the owner, as in @steipete/gog. Capability Evolver is on most lists and left out here: ClawHub's audit marks it for review because it can run jobs handed to it by a remote server. Skills are ordered by how many independent reviewers and users recommend them, then by downloads or stars. All are free. Numbers checked October 18, 2026.

The best Pi extensions for subagents, web search, plan mode and permissions, picked from the setups developers publish, each with its pi install command. Pi is deliberately bare: no sub-agents, no plan mode, no permission prompts. You add what you miss with one command, pi install npm:<package>. If you are starting out, three cover most of the gap with Claude Code: pi-subagents for delegation, pi-web-access for search, and rpiv-ask-user-question so the model asks before it guesses. Add Plannotator if you want plan mode, and pi-permission-system or pi-landstrip if you don't want the agent free to run anything. Three things have changed that older guides miss. Pi 1.0 shipped on October 1, 2026, and every pick here has had a release since except context-mode and pi-simplify, which we couldn't confirm on 1.x. Pi has had MCP support built in since version 0.99, so pi-mcp-adapter is now an upgrade and no longer a requirement. And several popular names have lookalikes: npm has at least four other packages named pi-mcp-adapter under other people's scopes, and more than one /btw and /simplify extension, so install by the exact name shown here. Extensions run with the same access to your machine that Pi has. Pi's catalog lists more than 5,000 packages, so read the source of anything that touches your shell or credentials, and pin versions you depend on. Ordered by how many independent users and reviewers recommend each one (Kay Rhodes's setup guide, Composio's tested top ten, XDA's hands-on, developers on Hacker News and Pi's own GitHub discussions), then by npm downloads and GitHub stars. Downloads count automated installs too, so treat them as a rough signal. Numbers checked October 24, 2026.

The best Claude Code plugins are Superpowers, a language server plugin for your language and Frontend Design, judged by the setups developers publish after pruning their installs and by what Hacker News users say they kept. A plugin is a bundle. One install can carry skills, slash commands, subagents, hooks and MCP servers. A skill is a single instruction file Claude loads when it judges it relevant, and an MCP server is a connection to an outside tool, so a plugin can contain both. If you install one thing, make it Superpowers, plus the LSP plugin for your language. Add Security Guidance if you ship code you don't read line by line, Plannotator if you want to mark up plans in a browser, and Claude HUD to see how full the context is. For web work, Frontend Design shapes the look, and Playwright or Chrome DevTools MCP lets Claude check the page in a real browser. Every enabled plugin adds to the context on every turn, and several of the writers quoted here deleted more than they kept. Token savers promise more than they deliver: a JetBrains test cut Caveman's advertised 65% to 8.5%. Plugins run code on your machine with your permissions, and Anthropic doesn't review third-party marketplaces, so read what a plugin will install before you say yes. Two names trip people up. Claude Code has a built-in review command alongside the Code Review plugin. And Anthropic's claude-security plugin, in beta, is a whole-repository scan, separate from Security Guidance. The list is ordered by how many independent people recommend each plugin, then by installs and GitHub stars. Numbers checked October 24, 2026.

The best local LLM for coding depends on how much memory your machine has. This list ranks open-weight models you can run yourself, by independent benchmark runs and by developers who use them in coding agents. With 24 to 32 GB, start with Qwen3.8-27B. Its 17 GB 4-bit file matched the full model on Terminal-Bench 2.1 in Quesma's test. With 128 GB of unified memory, Qwen3.8-Flash-Next posted the top score in WonderRico's benchmark. With 16 GB, gpt-oss-20b fits whole on the card, and one developer reports useful work from a 2-bit Qwen3.8-27B. With 8 GB, try Qwen3.5-9B and keep the jobs small. At 64 GB, run the 27B models at 8-bit, a 29 GB file, with a longer context. The step above that needs about 100 GB. A coding agent only works if the model emits tool calls your server can parse. Gemma 4 shipped with broken tool calling that was fixed later, and Qwen chat templates have needed community fixes, so update Ollama, LM Studio or llama.cpp before blaming the model. Agents also need room: LM Studio loads models with an 8,192-token context unless you raise it. Scores on a model card are the maker's own. A mixture-of-experts model computes with a few billion parameters per token but still has to hold all of them in memory, and context takes memory on top of the file. Qwen3.8 thinks at its highest effort by default, which is slow on home hardware. Qwen3.8-Flash-Next is not Apache licensed. Older guides still recommend Qwen2.5-Coder, Qwen3-Coder and Devstral, which general-purpose models beat in the hands-on tests cited here. The list is ordered by how many independent testers and developers recommend each model for coding, then by downloads. Numbers checked October 11, 2026.