Your AI product value is driven by the system around the large language model (LLM), however model itself is not a product (in many cases)
As an AI practitioner, working with business applications of large language models, I have some advice for those looking to build new products based on them
The impressive capabilities of advanced language models can make it tempting to build simple wrappers around them. However, it’s wiser to focus on what makes your product unique and valuable to users, rather than depending too much on a specific model. Models change quickly and are the least durable part of your system
Concentrate on what will deliver persistent value, such as:
✨ 𝙐𝙣𝙞𝙦𝙪𝙚 𝙗𝙚𝙣𝙘𝙝𝙢𝙖𝙧𝙠𝙨 𝙖𝙣𝙙 𝙚𝙫𝙖𝙡𝙪𝙖𝙩𝙞𝙤𝙣
it’s important to create unique benchmarks and evaluation methods to measure your model performance on business tasks. These benchmarks may include specific content-generation tasks for selected domain, custom system protocol cases, and etc. Output validation is also essential to ensure the system responses quality and relevance. Finally, models evaluation plays substation role during development and further maintenance showing integral estimation of user interaction quality
✨ 𝙂𝙪𝙖𝙧𝙙𝙧𝙖𝙞𝙡𝙨
Implement guardrails to prevent undesired outputs. These guardrails help define and maintain the model’s scope, ensuring the generated content stays relevant and appropriate. By setting these boundaries, we can avoid outputs that fall outside the intended field, maintaining the product’s quality and reliability
✨ 𝙋𝙚𝙧𝙛𝙤𝙧𝙢𝙖𝙣𝙘𝙚
Good performance is key to providing quick responses for your users. This can be achieved through techniques such as caching frequently used responses and orchestrating smaller models when necessary. By optimizing these aspects, you can enhance the user experience by delivering fast and more efficient interactions with the model
✨ 𝘾𝙤𝙣𝙩𝙞𝙣𝙪𝙤𝙪𝙨 𝙞𝙢𝙥𝙧𝙤𝙫𝙚𝙢𝙚𝙣𝙩
Continuous improvement of your LLM app extends beyond the current capabilities of a model. Active collection of user feedbacks and usage of the PDCA (Plan-Do-Check-Act) framework are essential for refining and enhancing the product. This ongoing process ensures that the product evolves to meet user needs and adapts to new challenges, maintaining its relevance and effectiveness over time
