Okay.
So as we were saying in the article, Long Chain has described the full professional LM application
development cycle and they have identified three main main phases.
Prototyping.
When we develop the first prototype of our application.
Beta testing.
When we test our prototype with real users and get their feedback to make improvements and production.
When we monitor the performance of our application and keep improving it.
Let's see the details that Land Chain shared about each of these, uh, phases.
About prototyping.
They say it involves quick experimentation between prompts, model types, retrieval strategy, and
other parameters.
The ability to rapidly understand how the model is performing and debug where it is failing is incredibly
important for this phase.
What do they say about the beta testing?
Face.
Beta testing allows developers to collect more data on how their LM applications are performing in real
world scenarios.
In this phase, it is important to develop an understanding for the types of input the app is performing
well or poorly on, and how exactly it is breaking down in those cases.
Both feedback collection and run annotation are critical for this workflow.
This will help in creation of test cases that can help track regressions or improvement and development
of automatic evaluations.
What do they say about the production phase?
Closely inspecting key data points, growing benchmarking data sets, annotating traces, and drilling
down into important data.
In Trace View are workflows you will also want to do once your application hits production.
However, especially at the production stage, it is crucial to get a high level overview of application
performance with respect to latency, cost and feedback scores.
This ensures that it is delivering the desirable results at the scale.
This is how the launching team describes a the full professional LM application development cycle on
a high level.
In the next lessons, we are going to see the details of these phases and especially the main challenges
that developer teams are finding and how long Smith is helping us to solve these problems.