Anthropic Unveils Tools to Enhance Prompt Engineering for Enterprise AI Efficiency

Anthropic has rolled out a new set of tools to help automate and improve prompt engineering in its developer console. This move aims to boost the efficiency of enterprise AI development.

The new features include a “prompt improver” and advanced example management. They’re designed to assist developers in creating more reliable AI applications by refining the instructions—known as prompts—that guide AI models like Claude in generating responses.

At the heart of these updates is the Prompt Improver. This tool applies best practices in prompt engineering to automatically enhance existing prompts. It’s especially useful for developers who work across different AI platforms because prompt techniques can vary between models.

“Writing effective prompts is one of the toughest parts of working with large language models,” said Hamish Kerr, product lead at Anthropic, in an interview with VentureBeat. “Our new prompt improver tackles this issue by automating advanced prompt engineering techniques. It makes it much easier for developers to get high-quality results with Claude.”

Kerr also noted that this tool is particularly helpful for developers moving workloads from other AI providers. It automatically implements best practices that usually require extensive manual tweaking and deep knowledge of different model architectures.

These new tools respond to the growing complexity of prompt engineering, which has become a vital skill in AI development. As companies increasingly rely on AI for tasks like customer service and data analysis, the quality of prompts significantly impacts how well these systems perform. Poorly written prompts can lead to inaccurate outputs, making it hard for businesses to trust AI in critical workflows.

The Prompt Improver enhances prompts using various techniques. One of these is chain-of-thought reasoning. This instructs Claude to tackle problems step by step before generating a response. This method can greatly improve the accuracy and reliability of outputs, especially for complex tasks.

The tool also standardizes examples in prompts, rewrites unclear sections, and adds pre-filled instructions to better guide Claude’s responses.

“Our testing shows significant improvements in accuracy and consistency,” Kerr said. He highlighted that the prompt improver boosted accuracy by 30% in a multilabel classification test and achieved 100% adherence to word count in a summarization task.

Anthropic’s latest release includes an example management feature. This allows developers to manage and edit examples directly in the Anthropic Console. It's particularly useful for ensuring Claude follows specific output formats, which many business applications require for consistent and structured responses.

If a prompt lacks examples, developers can use Claude to generate synthetic examples automatically. This further streamlines the development process.

“Both humans and Claude learn well from examples,” Kerr explained. “Many developers use multi-shot examples to show ideal behavior to Claude. The prompt improver will use the new chain-of-thought section to fill in the gaps between input and output with high-quality reasoning.”

Anthropic's introduction of these tools comes at a crucial time for enterprise AI adoption. As businesses integrate AI into their operations, they face the challenge of fine-tuning models to meet specific needs. These new tools aim to simplify that process, enabling enterprises to deploy AI solutions that work reliably and efficiently right from the start.

Anthropic emphasizes feedback and iteration. This allows developers to refine prompts and request changes, such as shifting output formats from JSON to XML, without extensive manual work. This flexibility could set them apart in a competitive AI landscape, where companies like OpenAI and Google are also vying for attention.

Kerr pointed out the tool’s impact on enterprise workflows, especially for companies like Kapa.ai. They used the prompt improver to migrate critical AI workflows to Claude. “Anthropic’s prompt improver streamlined our migration to Claude 3.5 Sonnet and helped us get to production faster,” said Finn Bauer, co-founder of Kapa.ai.

Beyond improving prompts, these tools signal a broader ambition: securing a leading role in the future of enterprise AI. Anthropic has built its reputation on responsible AI, focusing on safety and reliability—two key needs for businesses navigating AI adoption.

By lowering the barriers to effective prompt engineering, Anthropic is helping enterprises integrate AI into their operations with fewer headaches.

“We’re delivering measurable improvements—like a 30% accuracy boost—while giving technical teams the flexibility to adapt and refine as needed,” Kerr stated.

As competition in the enterprise AI space heats up, Anthropic’s approach stands out for its practical focus. Their new tools don’t just help businesses adopt AI; they aim to make AI work better, faster, and more reliably. In a crowded market, that could be the edge enterprises are looking for.