Which Prompts to Use for Business Automation with AI Models?

Introduction: Why the right prompts unlock business automation

This guide immediately answers the key question:What prompts should you use for business automation with the latest AI models?You’ll find practical examples, advanced techniques, and best practices that leverage cutting-edge innovations, such as Exa’s Agent Ultra, Liquid AI’s LFM2.5-VL-3B-DSpark, and Supersonic Labs’ Julia 1.

Overview of the latest AI models relevant to automation

The automation tools landscape has undergone significant changes this year. Three notable releases dominate the market:

• Exa Agent Ultra
• Liquid AI LFM2.5-VL-3B-DSpark
• Supersonic Labs Julia 1

Understanding each model’s capabilities helps in creating prompts that leverage each tool’s strengths, maximizing efficiency and accuracy.

Exa Agent Ultra: Deep research and list building

When you need detailed market data or a verified contact list, Agent Ultra excels at coordinating sub-processes across thousands of sources. An effective prompt must specify the objective, target audience, and desired format.

Prompt: "Generate a list of 50 qualified prospects in the Italian healthcare sector, including company name, sector, size, and verification source. Use Agent Ultra for deep research and format the results in CSV."

This prompt instructs Agent Ultra to target the healthcare sector, specify the number of records, and output the results in CSV format, ensuring a result that is immediately usable for sales teams.

LFM2.5-VL-3B-DSpark: Information extraction from images

If you need to extract text, tables, or product details from scanned images, LFM2.5-VL-3B-DSpark offers unparalleled speed thanks to speculative decoding. The prompt should include the type of information desired and the context.

Prompt: "Analyze this purchase order screenshot and extract order number, date, product lines, and total amount. Use LFM2.5-VL-3B-DSpark for rapid processing and return the data in JSON."

By specifying the objective (purchase order) and format (JSON), you eliminate the need for post-processing and speed up billing and inventory management processes.

Julia 1: CPU-based decision evaluation

For quick decisions that need to run on limited hardware, Julia 1 offers efficient processing. The prompt should present the options and evaluation criteria.

Prompt: "Evaluate the following staff deployment options (Shift A, Shift B, Shift C) based on productivity scores, employee availability, and cost impact. Use Julia 1 to generate a ranking and a brief justification for each."

This prompt leverages Julia 1’s ability to handle multiple variables and return a clear decision ranking, making it ideal for resource planning.

Advanced prompt engineering techniques for automation

• Contextual specificity:Include industry, tone, and desired format to reduce ambiguity.
• Data chunking:Break complex tasks into sub-tasks to be assigned to specialized models (e.g., research + extraction).
• Feedback loops:Add instructions for human validation, such as “If the total exceeds €10,000, request approval.”
• Dynamic prompts:Use variables to make the same prompt reusable in different contexts (e.g., {industry}, {period}).

By adopting these techniques, IT teams can create reusable prompt libraries that adapt to new scenarios without having to recreate them from scratch.

Workflow examples for common business use cases

Objective:Gather competitor information and generate an initial briefing.

Prompt: "Use Agent Ultra to collect the latest industry articles on [company name], extract strengths/weaknesses, market size, and pricing trends. Deliver a Markdown briefing with an executive summary."

Objective:Extract data from PDF invoices to automatically update the ERP system.

Prompt: "Process this invoice PDF: extract invoice number, date, supplier, item lines, and total amount. Use LFM2.5-VL-3B-DSpark for high-speed extraction and return the data in JSON for ERP import."

Objective:Create a balanced shift schedule that complies with regulations and maximizes efficiency.

Prompt: "Evaluate these shift options (Morning, Afternoon, Night) based on productivity, employee availability, and costs. Use Julia 1 to produce a ranking and a brief justification for each."

Best practices and tips for optimal results

• Test prompts on small samples before deploying them at scale.
• Document the purpose, parameters, and expected output format for each prompt.
• Monitor performance and update prompts based on feedback.
• Use variables to make prompts reusable across different departments.
• Combine multiple models when a single prompt cannot cover all aspects.

By implementing these best practices, companies can create reliable automation pipelines that deliver consistent and scalable results.

Conclusions

The right prompts serve as the bridge between the advanced AI models of 2026 and real-world business processes. By leveraging tools like Agent Ultra, LFM2.5-VL-3B-DSpark, and Julia 1 with well-structured prompts, organizations can automate deep research, extract data from images, and make quick CPU-based decisions, all while maintaining high quality and compliance.

Use the examples and techniques presented in this guide to create a customized prompt library. Start with a single use case, measure results, and scale automation across the enterprise. The future of business automation is already here, and the right prompts will enable you to harness its full potential.

Actionable takeaways

1. Identify one or two business processes that can benefit from AI automation.
2. Write a specific prompt using one of the example templates above.
3. Test the prompt on a small sample and evaluate accuracy, speed, and output format.
4. Document the prompt in a shareable library for your IT team.
5. Iterate based on feedback and scale automation to other departments.

By following these concrete steps, you will transform prompts into a strategic asset for business automation in 2026 and beyond.

IMPORTANT: We are in 2026. All temporal references must be current. Do not mention past years such as 2024, 2023, etc. The content must be fresh and relevant to the present. CURRENT CONTEXT (September 2026): Here are some recent trends and news stories to inspire you: - Supersonic Labs Releases Julia 1: A 144.3M-Parameter Open Decision Model That Runs on a CPU: Supersonic Labs has released Julia 1, a 144.3M-parameter decision model built on mmBERT-small. It takes context, a question, and 2 to 20 options, then... [2026-09-26] - End-to-End Multimodal Data Augmentation and Adversarial Robustness Benchmark with AugLy for Images, Text, Audio, and PyTorch: Discover how to build a comprehensive multimodal augmentation and adversarial robustness workflow using AugLy for images, text, audio, and PyTorch dat... [2026-09-26] - Liquid AI Releases LFM2.5-VL-3B-DSpark: Speculative Decoding for Vision-Language Models With Up to 3.13x Faster Decoding: Liquid AI has released LFM2.5-VL-3B-DSpark, a 279.5M-parameter draft model that brings speculative decoding to its LFM2.5-VL-3B vision-language model.... [2026-09-26] Use this current information as inspiration to create an original and relevant prompt for 2026.