Bullet

Bullet is a macOS coding agent built for developers who are frustrated by how slow most AI coding assistants feel. Built on Anthropic's Claude models, it rethinks the standard agent loop where each step waits for the previous one to finish. The result is smart routing between models, parallel execution of independent tool calls, and loop prevention that intercepts stuck processes before they waste your time. If you have used other coding agents and found yourself staring at a spinner for minutes while the system churns through sequential operations, Bullet is designed to eliminate that wait.

The core problem Bullet addresses is infrastructure overhead. Even capable AI models get bogged down by the machinery around them. You ask an agent to make a code change, and it spends minutes scanning your entire repository, queuing tool calls one after another, and occasionally repeating the same action multiple times before returning a result. Bullet attacks each of those bottlenecks directly. In demonstrations, the agent uses only about eight percent of repository context because it performs targeted searches to find the relevant code files rather than embedding the entire codebase. Independent tool calls run simultaneously instead of waiting in a queue. When the agent detects it is about to repeat a call or enter an infinite loop, it intercepts the duplicate request and moves forward. These optimizations compound into noticeably faster iteration cycles.

The routing layer is where Bullet differentiates itself most clearly. Not every coding task requires the same model capability. A quick variable rename does not need the full power of a heavyweight model, but a complex refactor across multiple files might. Bullet categorizes work by complexity and routes straightforward tasks to faster, lighter models while escalating sophisticated problems to more capable ones only when necessary. You avoid paying the latency cost of a heavy model for tasks that do not require it. The system aims for a tighter loop around the model-tools-results pattern, shrinking the overhead between each step to a minimum.

On benchmarks, Bullet claims 95.8 percent accuracy on SWE-bench verified tests. That puts it in competitive territory with the best coding agents currently available. As with any self-reported benchmark, the number deserves some caution. Test conditions, prompt formatting, and evaluation methodology all affect results. But the figure suggests that the speed optimizations do not come at the expense of correctness. The agent is not sacrificing quality for velocity. It is restructuring how work gets done to achieve both.

The target audience is software engineers and development teams who prioritize velocity and find themselves waiting too long during agent execution cycles. If you have adopted AI assisted development but feel like the tools introduce more friction than they remove, Bullet is built for that exact frustration. It runs as a native macOS application, currently in private beta, with no subscription model during this phase. You bring your own Anthropic API key, and the agent handles everything else. The app is free to download and use. You pay only for the API calls to Claude, which you would pay regardless if you use Anthropic's models elsewhere. There are no seat fees, no monthly charges, and no premium tiers to unlock features.

Because Bullet is still in private beta, the community and documentation are smaller than you would find with more established tools. The focus on Claude also means you are locked into Anthropic's ecosystem. If you prefer OpenAI, Google, or open source models, there is no option to swap them in. That constraint matters if you need multi-provider flexibility or have organizational requirements around model selection. The macOS exclusivity is another factor. Windows and Linux support have not been announced, so developers on those platforms will need to wait or look elsewhere.

For macOS developers already using Claude who want a faster coding agent experience, Bullet offers a compelling alternative to the default workflows. The combination of intelligent routing, parallel execution, and loop prevention produces a meaningfully snappier experience without requiring you to change how you think about tasks. You describe what you want, and the agent figures out how to deliver it quickly. The private beta is accessible through the official site, and the only ongoing cost is your existing Anthropic API usage.