opencode VS forgecode

Dax, the creator of OpenCode — an open-source coding agent, of all the people one might expect to disagree — put the case for hand-coding cleanly in a recent interview about Spec-Driven Development:

Pipa is our agent for studio operations at Lunch Pail Labs. She lives in Slack, is powered by E2B sandboxes, and uses OpenCode for the harness.

One reason I liked OpenSpec more than others, such as Kiro and SpecKit, is that OpenSpec is highly portable between coding assistants, codebases and stages of development. I've plugged OpenSpec into all sorts of projects, from infrastructure to Python libraries. I also work on diverse codebases, with a variety of AI friends that OpenSpec supports: OpenCode, Codex and Claude Code.

Beyond the big names, I would also keep an eye on OpenCode and T3 Code. OpenCode is a solid open-source, terminal-first option if you want a model-agnostic agent and bring your own provider setup. T3 Code is interesting for the opposite reason: it gives you an open-source GUI on top of the agents you may already pay for, like Claude Code, Codex CLI, OpenCode, or Cursor.

Brought to you by the infamous creator of OpenCode, who will exfiltrate all your data, then feign ignorance:

https://github.com/anomalyco/opencode/issues/10416

I'm using forge code (https://forgecode.dev/) with various local and cloud models and I really like it. MiniMax 2.7 is really great with it, and the new Qwen 3.6 35B A3B feels much stronger, after some testing, than the 3.5 version.

ForgeCode is not an AI model. It's a model-agnostic agent harness, open source under Apache 2.0, written in Rust, that wraps any LLM through OpenRouter or direct API keys. It launched in late January 2025 and hit v2.8.0 on GitHub by April 2026 with over 6,000 stars.

Or maybe this is the push to try something else entirely. ForgeCode currently tops TermBench 2.0 and has been getting a lot of attention. I haven't switched yet, but I'd be lying if I said I wasn't curious.

I tested these models using Forgecode. Want to run them in your own terminal? Install Forgecode⛵

Documentation - Setup guides and API reference GitHub Repository - Source code and issues Discord Community - Support and discussions Release Notes - Complete changelog

What's interesting is that our architectural constraints don't just make code review faster, they actively teach our Agent to generate better code. Every time agent sees our patterns, it learns and add them in memory. In Forge we call it custom rules. Other agents call them memory, rules etc.

👨‍🚀 From Moon Missions to Your Codebase Let your own coding assistant land your next software mission. 👉 Access your Forge dashboard

Shell-based agents respect the developer’s autonomy and expertise. They expose each step they take (just as normal shell commands do) and invite you to refine or approve actions. Using a shell agent feels like collaborating with a teammate in the terminal, rather than outsourcing tasks to a black box. In a shell environment, you can inspect and modify every command the agent runs. For example, if the AI suggests a code change via a script or regex, you see exactly what it does (and can tweak or undo it). This transparency means nothing happens without your knowledge. The developer remains in control: you issue the query, then fine-tune or approve the AI’s suggestions, rather than being bound to a hidden process.