Agenta vs Blueberry
Side-by-side comparison to help you choose the right AI tool.
Agenta
Agenta is an open-source platform that helps teams build and manage reliable LLM apps together.
Blueberry
Blueberry is an all-in-one Mac app that unifies your editor, terminal, and browser for seamless web app development.
Feature Comparison
Agenta
Unified Playground for Experimentation
Agenta provides a central playground where developers and domain experts can safely experiment with prompts, parameters, and different LLM models from various providers. You can compare multiple configurations side-by-side in real-time, using real production data to see immediate impacts. This model-agnostic approach prevents vendor lock-in and allows you to use the best model for each specific task, all within a single, collaborative interface.
Automated Evaluation Framework
Replace guesswork and manual "vibe checks" with evidence-based validation. Agenta's evaluation system lets you create a systematic process to test your LLM applications. You can integrate LLM-as-a-judge setups, use built-in evaluators, or write your own custom evaluation code. Crucially, you can evaluate the full trace of an agent's reasoning, not just the final output, and even incorporate human feedback from domain experts directly into the evaluation workflow.
Production Observability & Debugging
Gain full visibility into your live LLM applications. Agenta traces every single request, allowing you to pinpoint the exact failure points when things go wrong. You can annotate these traces with your team or gather feedback from end-users. A powerful feature lets you turn any problematic trace into a reproducible test case with one click, closing the feedback loop between production issues and development fixes.
Centralized Collaboration Hub
Agenta breaks down silos by bringing product managers, developers, and subject matter experts into one unified workflow. It provides a safe, no-code UI for domain experts to edit and experiment with prompts without touching the codebase. Everyone can run evaluations, compare experiment results, and debug issues from the same platform, ensuring alignment and speeding up the iteration cycle with integrated, real-world data.
Blueberry
Integrated Workspace
Blueberry combines a code editor, terminal, and preview browser into one cohesive environment. This integration allows developers to work more efficiently without the constant need to switch between different applications, enhancing focus and productivity.
Live Context with AI
The platform's built-in MCP server enables AI models to access your entire workspace. This means your AI can see open files, terminal output, and running applications, giving it the full context needed to assist you effectively, whether it's answering questions or suggesting code snippets.
Preview Across Devices
Blueberry comes equipped with built-in desktop, tablet, and mobile view previews. This feature allows you to see exactly how your application will look across different devices, ensuring a consistent user experience without leaving the Blueberry workspace.
Pinned Apps and Customization
You can keep essential tools like GitHub, Linear, Figma, and PostHog docked within your workspace. These pinned apps load with your project and share live context with your AI, allowing for a more integrated and efficient workflow. Additionally, you can customize your workspace setup per project, saving time and effort.
Use Cases
Agenta
Building and Refining Customer Support Agents
Teams developing AI-powered customer support chatbots can use Agenta to rapidly prototype different response tones and information retrieval strategies. Product managers and support experts can collaborate in the playground to tweak prompts for clarity and empathy, then use automated evaluations to ensure the agent consistently provides accurate, helpful answers before any deployment.
Developing Reliable Content Generation Tools
For teams creating marketing copy, blog post generators, or other content creation aids, Agenta is ideal for managing prompt variability. Writers and marketers can experiment with different creative directions, while developers systematically evaluate outputs for brand voice adherence, SEO quality, and factual correctness using custom evaluators, ensuring only high-quality variations move to production.
Debugging Complex AI Agent Workflows
When a multi-step agent (e.g., for data analysis or research) behaves unexpectedly in production, engineers can use Agenta's observability to trace the exact step where the reasoning failed. They can save this error as a test case, debug it in the playground by adjusting the prompt or logic for that specific step, and re-evaluate the entire chain to confirm the fix.
Validating LLM Application Upgrades
Before upgrading to a new, more cost-effective LLM model or a major new version of an existing one, teams can use Agenta to run comprehensive comparative evaluations. They can test the new model against a golden dataset of critical user interactions, using both automated and human-in-the-loop evaluations to ensure the upgrade doesn't cause a regression in performance or quality.
Blueberry
Streamlined Development
Developers can use Blueberry to streamline their coding process by having access to their terminal, code editor, and browser in one workspace. This allows for quick edits, testing, and debugging without losing focus or context.
Collaborative Product Building
Product teams can collaborate more effectively by using Blueberry's integrated features. The ability to share live project contexts with team members and AI assistants enhances communication and collaboration, leading to better product outcomes.
Rapid Prototyping
Designers and developers can quickly prototype applications using Blueberry's live preview feature. By seeing changes in real-time across different devices, teams can iterate faster and make informed design decisions, ultimately speeding up the development cycle.
Enhanced Learning and Experimentation
For those learning to code or experimenting with new technologies, Blueberry offers an intuitive environment where users can easily test out code snippets and receive AI-assisted guidance. This feature helps new developers to learn through practice while maintaining an organized workspace.