Building UseGlic
The best AI teammate starts with a job description.
What building a command centre taught us about turning an impressive AI answer into useful, repeatable work.
3 min read · 29 Oct 2026
The UseGlic blogFrom the team building it
Lessons from
building UseGlic.
Business lessons and engineering decisions behind AI teammates.
Explore reporting, support, service operations, finance and team communication: the work a role can prepare, the decisions people keep and how to judge the result.
Explore the business lessonsBusiness questions.Engineering decisions.Shared lessons.
The idea behind UseGlic
Start here · Building UseGlic
The best AI teammate starts with a job description.
What building a command centre taught us about turning an impressive AI answer into useful, repeatable work.
Read the story ↗What the capabilities mean for a business
All articles ↓Start with the work your team knows.
Each note connects a business lesson to a practical workflow, the relevant product capability and a way to assess the result. Explore how to put AI teammates to work across your team.
Project reporting
The reporting bottleneck often comes before the writing.
Role instructions, selected connections and a named owner give repeatable preparation work a defined scope.
Explore the lesson ↗Customer supportA faster answer only helps if the team can trust the policy behind it.
Source versions, document review and collections organise the information employees and AI teammates need to answer business questions.
Explore the lesson ↗Service operationsOptimize the cost of a usable result, including the work people do afterwards.
Model selection and usage visibility let teams match an AI teammate to the quality, response time and operating cost its job requires.
Explore the lesson ↗Finance operationsPrepare the decision before asking someone to approve it.
Role ownership, working instructions and review points help teams separate preparation from decisions that need a person.
Explore the lesson ↗Team communicationA finished draft creates value when the intended person can use it.
Conversation activity, tool results and actionable errors help an operator follow a task through to its destination and resolve blocked handovers.
Explore the lesson ↗Ideas from the inside
Notes from the work.
5 notes to explore
Knowledge & context
An answer is only as useful as the context behind it.
Why connecting documents is only the beginning—and why source, ownership and access belong in the same conversation.
Knowledge for employees and AI teammates is in development. This note describes the design direction, not live availability.3 min read · 29 Oct 2026
Under the hood
Model choice is an operating decision.
What separating the role from the model taught us about quality, cost and changing a system without losing its purpose.
3 min read · 29 Oct 2026
People & control
Human review belongs inside the workflow.
How a clear proposal, supporting context and a named reviewer make human-in-the-loop AI useful for business teams.
3 min read · 29 Oct 2026
Lessons in reliability
A healthy system can still leave the work unfinished.
What tracing requests from the first message to the final handover taught us about measuring the outcome people actually need.
3 min read · 29 Oct 2026
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