Once agents pick up tasks, write code, review it and deploy on their own, almost every engineering team asks the same thing: why do we still need Jira, Linear, Azure Boards or any other work tracker?

It is a fair question. Part of what lives in tickets today really does go away. Another part matters more than ever. If you separate the two cleanly, you get the frame in which agents can work safely.

What goes away

Many tickets are pure execution tracking: "implement function X", "fix bug Y". One person writes down what they are about to do anyway, so that someone else can see it got done. That layer was always closer to bookkeeping than to value creation, and it is exactly the layer agents take over.

A team that still produces the same volume of micro-tickets in a few years is using agents as faster keyboards.

What stays and grows in importance

The moment agents execute, you need a layer where people assign work, approve results and later trace what happened. The work tracker is the obvious place for it, because it already holds tasks, ownership and status in a structured form.

### Approval and audit trail

Which agent wrote the patch, with which model, on which branch, with what reasoning, and who approved it? In banking, insurance, pharma or automotive this is not optional. The EU AI Act requires high-risk AI systems to log events automatically (Article 12), and in financial services DORA requires traceable ICT risk management. Every one of these frameworks wants to know who or what decided, and when. A ticket with an agent as assignee, a human approval and a linked result gives you that trail.

### Handover between people and agents

An agent needs a clear goal, acceptance criteria, a definition of done, links to context and an explicit out-of-scope list. That is the description of a good ticket. A well-kept backlog becomes the interface format. Poor tickets used to produce poor pull requests; now they produce poor agent output.

### Coordinating many agents

When three, five or ten agents work in parallel, they need one shared source: who is working on what, which agent may do what, where do they collide? A chat thread does not solve that. A queryable task layer with permissions does.

### Connecting strategy and execution

Agents execute, people set direction. The faster execution runs, the more an unclear direction costs. Epics, goals and roadmaps are how a company steers, and they belong in the same structure as the tasks agents work through.

### Visibility for decision-makers

Boards, customers and supervisors do not read agent logs. They want to know whether a program is on track, which risks are open and where dependencies are stuck. That view comes from the tracker, not from the agents.

Context is the real bottleneck

Language models have become largely interchangeable. The model you license today can be swapped for another tomorrow. What cannot be swapped is your company's context: every ticket, wiki page, pull request, architecture decision and retro. In many companies, the work tracker and the wiki are the largest structured store of that institutional knowledge.

An agent without that context works like a new hire without onboarding. In practice we keep seeing the same gaps:

• Wikis with lots of pages but no ownership and no upkeep.
• Trackers that are not connected to the code repository, chat and documents, so context falls apart.
• Knowledge in silos that were never connected.
• Agent pilots on generic models without company context, with answers to match.

What matters is that context is available in a permission-aware way: what a person may not see, their agent may not see either. Without that rule, no agent gets past the first security review.

What you can do now

• Rework your ticket hierarchy: fewer micro-tasks, more outcomes with acceptance criteria.
• Give agents their own identities with clear permissions, so every action maps to an agent and an approving person.
• Put approval gates wherever an agent does something with effect: merge, deployment, customer communication.
• Treat your wiki and documentation as a knowledge base, with owners, a lifecycle and a review cadence. Upkeep here is preparation for AI.
• Connect your sources: repository, chat, documents. Every place where business-relevant knowledge is created belongs in the context layer.
• Strengthen reporting upward, because decision-makers need more explainability with agents, not less.

Conclusion

Agents do not make the work tracker obsolete. They shift its focus from logging individual steps to approval, traceability, coordination and context. Build that layer now and you can give agents more responsibility without giving up control. Remove it and you build up compliance and coordination debt.