LLM governance
ownership and traceability
1. LLM governance
Agentic workflow is shifting the paradigm from running operations to monitor the operativity of agents. The system should define clear ownership across all the components to allow proper decision making. The key component is traceability: the system should be built so any agent decision is more or less reproducible and we can spot where the issue was initiated. There are as well few main areas where different stakeholders need to monitor and control the status and the success of the system. Those areas should properly define metrics, KPIs, indicators, logs, checks, evaluations… so each owner can control and act on the system. The system should follow some guidelines and all the components should be consider them. The main areas are:
- 2
- cost and performance control
- 3
- how much the results are aligned with the goals
- 4
- checks on model performances and edge cases, data drifts and models evaluation
- 5
- is the overall system performing correctly and delivering value
Define the key metrics is the most relevant activity
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Many stakeholders get lost in defining a proper governance method especially regarding some terms:
- traceability
- rebuild the actions done by the agents using accurate logs
- observability
- a much generic term to indicate the collection of metrics around a running system
- evaluation
- check model performances against typical metrics like: hallucination,
- KPI
- more business oriented indicators, they should comprise multiple quantities and
(org-html-export-to-html)
Figure 1: example of a flow of responsibilities
2. backend
3. fitness
4. goodness
5. business
6. commands
echo "This is my configuration script" echo "..do something interesting here.."