Intent vs Cline: Spec-Driven Orchestration or Per-Action Approval in 2026?

Two AI coding tools, two completely different theories about how much control a developer should keep over the machine. Cline is an open-source, bring-your-own-key agent that runs inside VS Code and asks permission before nearly every file edit or tool call. Intent is a standalone workspace that takes a feature spec, fans out parallel agents, and comes back when the work is done.

The tradeoff is real: Cline gives you a veto on every action at the cost of constant babysitting. Intent gives you hands-off delegation at the cost of visibility into what is happening step by step. This post breaks down architecture, approval models, agent orchestration, pricing, and where each tool falls apart so you can pick the right one for the way you actually work.

Architecture: Extension vs. Standalone Workspace

Cline lives inside VS Code. You install it from the marketplace, wire up an API key (OpenAI, Anthropic, or a local endpoint through Ollama), and it operates inside your existing editor. It reads your open files, runs terminal commands, and edits code, but every action goes through an approval gate in Plan & Act mode. The upside: it integrates with your git workflow, your existing extensions, and your terminal. The downside: the agent can only do one thing at a time in a single sequential loop.

Intent takes the opposite approach. It runs as a standalone workspace in the browser, separate from your editor. You write (or approve) a living spec that describes what you want built. Intent then spins up multiple agents in parallel, each working on a piece of the spec. The workspace manages its own file system and version state. You get back a completed feature branch rather than watching each line appear.

For developers who live in VS Code and want AI to feel like a very capable pair programmer, Cline fits naturally. For teams that want to hand off an entire feature and review the output as a diff, Intent makes more sense.

Approval Models: The Core Philosophical Split

This is the biggest difference between the two tools and the one most likely to determine which you prefer.

Cline: approve everything, trust nothing. In Plan mode, Cline outlines a course of action. You review and adjust until you are satisfied, then switch to Act mode. Even in Act mode, Cline pauses before writing files, running shell commands, or calling external tools. You confirm each step. This is deliberate: Cline's design philosophy treats human oversight as the safety layer. The cost is friction. On a complex refactor touching 15 files, you may click "approve" dozens of times. Prompt fatigue is real.

Intent: approve the spec, delegate the implementation. You define what should happen at the feature level (a living spec that describes behavior, constraints, and acceptance criteria). Once you sign off on the spec, Intent's agents execute without per-action interrupts. You review the result as a whole, not step by step. The cost is that if the spec is ambiguous or wrong, the agents may build something internally consistent but not what you wanted, and you only discover that at the end.

Neither model is categorically better. Per-action approval catches mistakes early but scales poorly. Per-spec approval scales well but demands precise specs up front.

Agent Orchestration: Sequential vs. Parallel

Cline runs a single agent loop. It reads context, plans, acts, reads the result, plans the next step, acts again. This means it can reason about intermediate outputs (if a test fails mid-flow, it can adjust). But it also means that a task touching multiple modules happens sequentially. A feature that needs frontend changes, backend changes, and migration updates runs as one long chain.

Intent orchestrates multiple agents in parallel. Its architecture (as described by Augment Code's comparison) coordinates agents through the living spec so they can work on separate parts of the codebase simultaneously. For large, well-scoped features, this cuts wall-clock time significantly. The tradeoff: parallel agents can step on each other if the spec does not properly partition the work, and debugging coordination failures is harder than debugging a single sequential chain.

Model Flexibility

Cline is fully BYOK. You can point it at OpenAI's API, Anthropic's API, Google's Gemini, or a local model served through Ollama or LM Studio. This matters for cost control (use a cheap model for boilerplate, an expensive one for complex logic) and for privacy (run everything locally if your codebase cannot leave your machine). Cline's model-switching workflow is one of its genuine strengths.

Intent manages its own model infrastructure. You get less control over which model runs under the hood, but you also do not have to manage API keys, rate limits, or per-token billing across providers. For teams that do not want to think about model selection, this is simpler. For developers who want to optimize cost per task or run air-gapped, it is a limitation.

Context Management

Cline relies on you to manage context. You can use .clinerules files to set project conventions, feed it specific files, or connect MCP servers for external data. This is flexible but manual. On a large codebase, getting the right context into the agent's window is half the battle.

Intent's living specs serve double duty: they define the task and carry the context. Because the spec persists and updates as the feature evolves, agents always have a single source of truth. This is cleaner for multi-session work on the same feature, but it means your context is locked inside Intent's format and workspace.

Where Each Tool Breaks Down

Cline struggles with scale. A 40-file refactor in Cline means 40+ approval prompts and a single sequential chain. By the time you are done approving, you might have been faster doing it yourself. Cline also leans heavily on the context window of whatever model you connect. Hit the token limit and the agent loses track of earlier decisions.

Intent struggles with precision. If your spec says "add a user settings page" but does not specify the state management pattern, the routing convention, or the component library, Intent's agents will make choices you may not agree with. Fixing those choices after the fact can mean rewriting the spec and re-running, which burns time and tokens. Intent is also less useful for small, targeted edits (fix this one function, rename this variable) where the overhead of writing a spec outweighs the work.

If you are exploring how other AI coding CLIs compare, our breakdown of Aider vs Claude Code covers two more terminal-first approaches, and the Claude Code vs Cursor comparison tackles agent vs. editor-integrated workflows from a different angle.