What is EmployeeWorks? | Build EmployeeWorks plugins with ToolSmith (Part 1)

What is EmployeeWorks? | Build EmployeeWorks plugins with ToolSmith (Part 1)

2026-10-23

This is the first video in the Build EmployeeWorks plugins with ToolSmith series on the ServiceNow Dev Program channel. The video covers the following topics:

  • What we’ll build with ToolSmith: describe a workflow (like cancelling a travel booking), review the plan ToolSmith proposes, and let it build the plugin once you approve it
  • The problem employees face when they have to move between different systems and apps to find information or get something done
  • Searching company knowledge by asking a policy question with Enterprise Search
  • Cancelling a travel booking through a plugin
  • Looking inside the travel plugin to see what it defines behind the conversation
  • Where EmployeeWorks shows up: Slack, Microsoft Teams, and the EmployeeWorks Web App

The full written series is on the ServiceNow Community.

Related Content

Build EmployeeWorks plugins with ToolSmith

Build EmployeeWorks plugins with ToolSmith

2026-10-23 · 1 min ServiceNow

Employees shouldn't need to know which system handles their request, jump between portals, or learn how every application works to get something done. This series introduces EmployeeWorks and shows how to plan, build, review, and test well-governed plugins with ToolSmith.

The Jury Pattern: a mixture of critics for AI code review

The Jury Pattern: a mixture of critics for AI code review

2026-06-03 · 15 min

One model reviewing its own plan tends to agree with itself. So I built a cleanup workflow shaped like a jury: separate critics from a deliberate mix of model families weigh the evidence, with a simple forcing function that keeps neighbouring reviewers off the same family. The orchestrator presides as judge, refuting rather than merging, votes promote shared findings, and a post-approval diff check can overrule a verdict that was unanimous and still wrong.

Agentic memory: what agents should and shouldn't remember

Agentic memory: what agents should and shouldn't remember

2026-04-10 · 11 min

Conversation state and retrieved context lead naturally into memory, but only if we're clear about what memory is for. Rules, skills, and instruction files package what you already know. Memory should capture what the work itself teaches the system, and that means reflection, verification, and forgetting matter just as much as recall.