Every team has that person who just knows where to look. They remember the unusual failure from two years ago, and they understand why a configuration differs from one region to another. Or, they know when an apparently minor alarm points to a wider problem and can quickly identify the underlying issue.
That experience is highly valuable, but it is difficult to distribute. Documents capture approved procedures and OSS platforms hold the underlying data, however the reasoning that connects them often remains with individual engineers.
When these team members retire or change jobs (or just go on holiday), they take their knowledge with them. Some of it may already exist in engineering logs, incident records or other internal documents, but colleagues may not know where to look or even that the relevant information was recorded.
AI agents can make this knowledge easier to retain and share across teams. By searching historical records and documents together, an agent can connect the current situation with relevant past incidents. It can also surface useful details beyond the user’s original query, helping them benefit from experience that might otherwise remain buried.
Supporting individual use cases
A network engineer who has moved from one operator to another may need guidance on which checks to run and why they matter to their new employer. They have experience managing a network but may not be familiar with their new employer’s internal processes. Their AI agent can recommend an approved sequence, explain the purpose of each step and retrieve the evidence required to complete the task.
Or a network engineer who has been with their employer for years may have been transferred to a new region. They know the network and their employer’s internal processes, but are unfamiliar with the new region and don’t know which sites are underperforming. They might ask for a comparison across sites, search for similar patterns or automate a routine diagnostic workflow. Their agent reduces repetitive information retrieval and leaves room for a more directed investigation.
Both engineers benefit from knowledge that they may not otherwise have access to as the AI agent reflects their needs and shares the knowledge.
Expertise remains active
The aim is not to encode an expert once and reuse their answers forever. Networks change, procedures evolve and past decisions can become obsolete, so engineers still need to question the evidence and account for current conditions.
Our “everyone has an agent” approach gives each user quicker, more consistent access to the organisation’s available knowledge and allows that access to be tailored to the individual’s needs. The agent expands access to expertise, but the engineer still decides how that expertise should be applied.
Give every member of your team access to operational knowledge. Discover how Metricell can help your teams find and apply shared expertise while keeping engineers in control.
