How an AI agent for invoice processing keeps a human in control
Invoice processing is high volume, rule-bound, and unforgiving of errors. A governed AI agent can read, match, and code invoices while routing every payment decision to a person.
Author
Nishkarsh Gupta
Articles by Nishkarsh Gupta
8 articles, newest first.
How an AI agent for expense reports keeps approvals in place
Expense reports are repetitive, rule-bound, and easy to get wrong. A governed AI agent can read receipts, apply policy, and route the judgment calls to a human, while recording every step.
Designing a multiplayer AI workspace for human teams and agents
Adding an assistant to a chat window does not make a workspace where humans and AI agents work together. Six design decisions do, and most of them are about control rather than capability.
AI agent collaboration platform: how to evaluate multiplayer AI
Three very different products are sold under the same name. Only one of them is somewhere a team can actually work, and six questions tell you which is which.
Designing with AI tools without shipping slop
AI can generate a hundred screens in a minute. Most of them are slop. Here is the working method I use to keep AI in the loop without letting it flatten the product.
Multiplayer AI: what changes when a whole team works with agents
Google Docs beat Word by going multiplayer. Figma beat Photoshop. AI has not had that moment yet, and the missing piece is not shared context. It is shared control.
Approvals are a feature, not a friction
Approval is often treated as the thing slowing automation down. In business AI execution, it is the mechanism that lets more work move without pretending every action has the same risk.
Designing human checkpoints for AI agents
Human-in-the-loop design can be precise rather than performative. The checkpoint should appear at the moment risk changes, with enough context for a fast decision.