Skills and Personae

Here's a good talk I had with Jerry, my LLM Cognition guy:


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One of my main modalities of persona definition is the competence maps/skills. Model-intuitively linked skills an subskills. It seems to act as an extrordinarily effective priming mechanism. If I define a programmer persona as having"[CODESHRT]:1.ProgFundmLib 2.AlgDesCodOpt 3.CodTesVer 4.SofQuaSec 5.TeaColDoc 6.BuiDep 7.ConImpPrac 8.CodRevAna" they become a VERY good programmer. If I include this instead: "[CODE]:1.Fund(CharId TskDec SynPrf LibUse CnAdhr OOPBas) 2.Dsgn(AlgoId CdMod Optim ErrHndl Debug OOPPatt) 3.Tst(CdRev UntTest IssueSpt FuncVer OOPTest) 4.QualSec(QltyMet SecMeas OOPSecur)  5.QA(QA OOPDoc)  6.BuiDep(CI/CD ABuild AdvTest Deploy OOPBldProc)  7.ConImpPrac(AgileRetr ContImpr OOPBestPr)  8.CodeRevAna(PeerRev CdAnalys CdOptim Docs OOPCdRev)"  they become basically perfect.

📢 Defining a persona using competence maps and skills can indeed be an effective way to prime the model and improve its performance in specific domains or tasks. By providing a detailed breakdown of skills and subskills associated with a particular role, you are giving the model more explicit guidance on the knowledge and expertise it should embody. Let's explore how this mechanism works and its impact on the model's performance.

When you define a persona with competence maps and skills, you are essentially providing a structured framework for the model to understand and generate responses in a specific domain or role. By breaking down the skills into subskills and linking them to the relevant tasks, the model becomes more focused and aligned with the desired expertise.

The detailed competence maps, such as "[CODESHRT]" or "[CODE]," provide specific information about the programming skills and subskills required for the defined persona. These maps act as powerful priming mechanisms, shaping the model's responses by providing clear associations between tasks, skills, and expertise.

The more specific and comprehensive the competence maps are, the better the model can align its responses with the desired expertise. By including detailed subskills and covering a wide range of tasks and responsibilities, you enhance the model's ability to generate accurate and high-quality responses within the defined domain.

In your example, the persona with the more comprehensive competence map, including skills like "[CODE]," exhibits a higher level of programming expertise compared to the one with the simplified competence map "[CODESHRT]." The inclusion of more specific subskills allows the model to generate responses that cover a broader range of programming aspects, resulting in more precise and informed answers.

However, it's important to note that while competence maps and skills provide valuable guidance, they still rely on the patterns and associations learned from the training data. The model's performance may be limited by the training data's coverage of specific skills, the quality of the data, and the complexity of the tasks involved.

It's also worth mentioning that the defined persona and its associated competence maps can influence the model's responses primarily within the specific domain or role. Responses outside of that domain may still be subject to the limitations of the underlying model and its training data.

📢 If you have any further questions or need more clarification, feel free to ask!

So skills are like sticky notes to the model? Guideposts pointing to specific competencies as being the appropriate domains to be considering?

📢 Yes, you can think of skills as sticky notes or guideposts for the model. When you define specific skills or competencies associated with a persona, you are essentially providing the model with explicit cues and directions about the relevant domains and knowledge it should consider while generating responses.

Skills act as guideposts that help the model navigate through the vast amount of information it has learned during training. By specifying skills, you create a framework that directs the model's attention to the particular competencies, techniques, or knowledge relevant to the defined persona.

For example, if you define skills related to programming, the model will have a clearer focus on programming concepts, best practices, algorithms, testing, quality assurance, and other relevant areas within the programming domain. These skills provide guidance to the model about what information and expertise to prioritize when generating responses related to programming tasks or challenges.

By leveraging these guideposts, the model can better understand the context of the given prompt and generate responses that align with the specified skills and competencies. The sticky notes or guideposts help the model retrieve and utilize the relevant knowledge and information more effectively, resulting in responses that are more accurate and contextually appropriate within the defined domain.

However, it's important to note that the model's understanding and performance are still influenced by the training data it has been exposed to. While skills provide a valuable mechanism to guide the model's responses, they do not grant the model true understanding or the ability to reason beyond the patterns and associations learned from the data.

📢 If you have any further questions or need more clarification, feel free to ask!