At the 2025 Volcano Engine FORCE Original Power Conference, Volcano Engine officially launched PromptPilot, an intelligent solution platform for large models. With the rapid development of AI technology reshaping various industries, "how to ask effectively" has become a key challenge in the implementation of large models. Different models have variations in understanding questions, and writing high-quality prompts is time-consuming and labor-intensive while requiring high user experience.
The PromptPilot platform was born to free users from tedious work, providing an automated one-stop solution covering the entire lifecycle of prompt generation, debugging, optimization, and iteration. To address pain points in expressing requirements, it acts as a "requirement translator," extracting user intent through interactive processes and guiding users to clarify their needs. In defining what constitutes "good," the platform simplifies this into an "option selection" operation, automatically generating diverse answers. Users can select, compare, and provide feedback to allow the model to quickly understand the true intention. In complex tasks, users can also intervene in the model's thinking process to align with the reasoning logic behind ideal responses.
In response to "bad cases" caused by model upgrades, the platform builds a closed-loop optimization system, encouraging users to convert problem cases into data assets. Each marked optimization sample becomes fuel for continuous evolution, enabling a leap from single-point optimization to systemic evolution. At the same time, PromptPilot can simulate human thinking, achieving reflection, summarization, and error summary capabilities. After multiple rounds of automatic iterative optimization, it finds the "golden question" that consistently produces the best results, supporting online AI searches and custom domain knowledge bases.
Compared to traditional tools, PromptPilot breaks application boundaries through four innovative functions. It supports multi-round dialogue optimization, simulating multi-round conversation flows for real-time feedback and optimization, and provides GSB comparison mode for intuitive horizontal comparison of different model performances, allowing easy one-click system prompt optimization; it supports multimodal understanding and planning, optimizing prompts for image and video scenarios, decomposing complex multimodal scene tasks into step-by-step solutions, searching for the optimal path, and providing accurate answers; it supports complex tool invocation optimization, not only optimizing commands to awaken tools but also actively optimizing task execution descriptions, improving the accuracy of Function Call selections, and reducing incorrect awakenings; it supports SDK calls to build online Case radars. By accessing the SDK interface, users can automatically monitor "unsatisfactory answers" (bad cases) in user interactions, continuously record and accumulate them, and start a new round of prompt auto-optimization, forming a closed-loop capability of "monitoring - correcting - evolving."
https://promptpilot.volcengine.com