ChatGPT produces working code. Fast. For an Engineering team that’s struggling to meet demand, our prompt engineering service is a cost-effective alternative to recruiting talent, giving you the extra hands you need to ship on deadline.
Prompt Applications
ChatGPT produces working code. Fast. For an Engineering team that’s struggling to meet demand, our prompt engineering service is a cost-effective alternative to recruiting talent, giving you the extra hands you need to ship on deadline.
Ah, GPT’s bread & butter. But what a difference expert prompt engineering can make. We engineer AI inputs to run the gamut for a scrappy marketing team at lightning speed, from generating ad copy that actually converts to SEO content that actually ranks.
We’re shameless process evangelists. Get serious about your operations org. Everything you do needs a process, documentation, and a flowchart that’s visible company-wide. We ask Large Language Models (LLMs) the right questions so you can focus on the answers.
Ah, GPT’s bread & butter. But what a difference expert prompt engineering can make. We engineer AI inputs to run the gamut for a scrappy marketing team at lightning speed, from generating ad copy that actually converts to SEO content that actually ranks.
Prompt Applications
We’re shameless process evangelists. Get serious about your operations org. Everything you do needs a process, documentation, and a flowchart that’s visible company-wide. We ask Large Language Models (LLMs) the right questions so you can focus on the answers.
Prompt Applications
1. Be clear and concise: LLMs perform best when given clear and concise prompts that clearly define the task and provide all necessary information.
2. Use natural language: LLMs are designed to work with natural language. Use it!
3. Provide context: Context ensures that the model can accurately interpret the prompt and generate the desired output.
4. Use examples: Providing examples that are representative of the desired output and provide enough variation ensures that the model can generalize to new inputs.
5. Use iterative refinement: Creating effective prompts often requires an iterative process of trial and error. Start with simple prompts and gradually add complexity and nuance in conversation with your chosen model until the desired output is achieved.
1. Be clear and concise: LLMs perform best when given clear and concise prompts that clearly define the task and provide all necessary information.
2. Use natural language: LLMs are designed to work with natural language. Use it!
3. Provide context: Context ensures that the model can accurately interpret the prompt and generate the desired output.
4. Use examples: Providing examples that are representative of the desired output and provide enough variation ensures that the model can generalize to new inputs.
5. Use iterative refinement: Creating effective prompts often requires an iterative process of trial and error. Start with simple prompts and gradually add complexity and nuance in conversation with your chosen model until the desired output is achieved.
Reinforcement Learning From Human Feedback is why ChatGPT is so powerful. Learn more about the technique and why experts trust Invisible to do it.
Invisible CTO Scott Downes joined DataFramed recently to discuss how ChatGPT and Generative AI are augmenting workflows and scale operations.
Invisible has done outstanding work that has materially increased the team’s productivity...we plan to expand our services with invisible.
Invisible is our strategic growth partner providing us with business intelligence to expand into new markets. They exceeded our expectations in both cost and quality while improving our outcomes.
