Compare/Goose v1.29 vs Intent

AI tool comparison

Goose v1.29 vs Intent

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

G

AI Agents

Goose v1.29

The open-source AI agent that uses your Claude, Gemini, or ChatGPT subscription

Skip

25%

Panel ship

Community

Free

Entry

Block's open-source on-machine AI agent just hit v1.29, introducing Gemini ACP (Agent Client Protocol) support so you can run the full Goose agent stack using your existing Google subscription — no separate API key needed. It also added orchestration for sub-agents, adversarial agent mode to prevent information leaks, delegate sub-agent log display, and macOS sandboxing. With 35k+ GitHub stars and Rust-based architecture, Goose goes far beyond autocomplete: it builds projects, writes and executes code, manages files, and calls external APIs autonomously. The ACP approach means your Goose extensions are passed directly to Gemini, deepening the connection compared to plain CLI usage.

I

Agent/Automation

Intent

Describe a feature. AI agents build, verify, and ship it.

Ship

75%

Panel ship

Community

Free

Entry

Intent is Augment Code's multi-agent software development workspace. You describe what you want built — a feature, a fix, a refactor — and a coordinated team of AI agents takes it from spec to shipping code. The system maintains living specifications that stay current throughout the development process, so requirements don't drift as agents work. Under the hood, Intent runs agents in isolated workspaces so different tasks can't interfere with each other. A coordinator agent manages task delegation, routing work to specialized agents for code generation, design review, mobile implementation, and other concerns. The spec panel tracks project requirements and progress in real time, giving you a single pane of glass over what agents are doing and what remains. Augment Code has been quietly building toward this for a while — their IDE Agents and CLI products form the underlying layer, with Intent sitting on top as the higher-level orchestration product. It's positioned squarely against Devin and SWE-agent-style autonomous coding, but with more emphasis on keeping humans in the loop through living specs rather than handing off completely.

Decision
Goose v1.29
Intent
Panel verdict
Skip · 1 ship / 3 skip
Ship · 3 ship / 1 skip
Community
No community votes yet
No community votes yet
Pricing
Free / Open source (Apache 2.0). Use your own AI subscription (Claude, Gemini, ChatGPT) — no additional per-token cost.
Freemium
Best for
The open-source AI agent that uses your Claude, Gemini, or ChatGPT subscription
Describe a feature. AI agents build, verify, and ship it.
Category
AI Agents
Agent/Automation

Reviewer scorecard

Builder
80/100 · ship

This is exactly the architecture I want: a local agent that doesn't lock me into one AI provider's billing. The Gemini ACP integration means my Google One subscription now funds actual dev automation. The adversarial agent mode is also clever — finally an agent that polices itself before it nukes your filesystem.

80/100 · ship

The living specs concept is the right idea — autonomous coding agents fail because requirements get lost mid-task. Keeping a maintained spec that agents reference throughout solves the context drift problem. Isolated workspaces mean you can run parallel feature development without race conditions. This is a serious tool for serious teams, not a toy.

Skeptic
45/100 · skip

Multi-agent orchestration sounds great until you're debugging a cascade failure at 2am wondering which sub-agent hallucinated first. The 35k stars are real but so is the complexity overhead. Claude Code and Cursor 3 have more polish for day-to-day use — Goose still feels like a power-user project.

45/100 · skip

Every multi-agent coding tool in 2026 promises to 'build, verify, and ship' features autonomously. Most of them generate plausible-looking code that compiles but doesn't actually work as intended. Augment Code has solid underlying models but 'coordinated agent teams' still means you're debugging AI-generated code at the seams between agents. Until I see real production deployments with zero-intervention feature shipping, this is glorified autocomplete with extra steps.

Futurist
45/100 · hot

The ACP subscription model is the thin edge of a wedge that eventually makes AI provider lock-in irrelevant. When agents can switch between Claude, Gemini, and GPT seamlessly based on cost and availability, the moat moves to the orchestration layer. Block is quietly building that layer in the open.

80/100 · ship

Intent represents the transition from AI-assisted coding to AI-directed development. The living spec paradigm is a genuine architectural insight — specs as shared context between agents and humans is how autonomous software teams will be organized. Augment's bet on coordination over raw capability is the right design philosophy as models plateau in coding benchmarks.

Creator
45/100 · skip

The MCP Apps and rich UI stuff is interesting for creative workflows, but Goose is fundamentally a developer tool. The learning curve before it does anything useful for non-devs is steep. I'll check back when the Neighborhood Extension for ordering food is the least niche thing it can do.

80/100 · ship

The spec panel that tracks requirements in real time is a design win — it makes AI development legible to product managers and designers, not just engineers. Seeing what agents are doing across isolated workspaces without reading logs is the kind of transparency that actually builds trust in AI tooling.

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