Beyond coding

The previous sections focused on agents writing, reviewing, and shipping code. However, there are a lot of actions involved in building a software project that is not coding itself, like triaging issues, answering support questions, synthesizing meeting notes or reacting to issues. Agents can also be of help in these, assumed they are given good context and their replies are verified.

Issue triage

Incoming issues accumulate fast and not every one of them can be treated the same. The engineer needs to decide which are duplicates, which are actionable, and which require more information. Because of these patterns, handling the triage of issues can be delegated to an agent.

A triage agent connected to your issue tracker can:

Tag and label issues automatically based on title and description
Identify duplicates and link them to existing reports
Ask clarifying questions in a comment before routing to a team member
Prioritize by severity, user impact, or affected component

For example, OpenAI uses scheduled triage automations for exactly this, as covered in the High-level harnesses chapter. The agent runs on a fixed schedule, processes new issues, and only escalates what really needs a human decision.

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Customer support

Most often, customers ask what has already been asked before, so support queues are repetitive and high-volume. Most of the incoming tickets can be handled by an agent provided with documentation, changelogs and previously resolved tickets.

Agents easily handle “how do I…” questions, drafting responses to common error messages or translating tickets into bug reports for engineers.

However, LLMs don’t like to admit that they don’t know something. Their goal is to provide an answer that seems plausible, but not always is. Therefore, it is important to include reflection in the agent’s workflow, like asking it “Does the documentation provide enough information for the user’s question?”.

If the agent cannot solve the issue, it should escalate it to the person in charge. To make the process easier, the agent can be asked to extract reproduction steps from the user’s problem.

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Meeting notes and action items

Meetings usually produce commitments that are woth remembering. Unless there is a person delegated to track them, some can be forgot. Agents connected to transcription services can analyze what was said and come up with a doc on relevant issues.

A typical setup:

A transcription tool produces a raw transcript.
An agent reads the transcript and extracts: decisions made, open questions, and action items with owners.
The output lands in a shared doc, a project management tool, or as comments on relevant issues.

The agent can handle these right after the meeting and is less prone to omit something in a noisy transcript than a person skimming it some days later.

Agents work best here when the meeting has a clear structure, more creative discussions can be harder to sum-up, as they hold value in their entirety.

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Observability and incident response

Production incidents are time-sensitive and require pulling context from many places at once: error logs, stack traces, recent deployments, related tickets. Agents can do a significant share of this triage automatically, as soon as the notification happens.

Agents wired into the observability loop can:

Read a stack trace, search the codebase for the relevant code path, identify the root cause, and propose a fix
Summarize the scope (“these three endpoints regressed after this PR”)
Correlate errors with recent commits and flag the likely culprit
Annotate alerts with human-readable explanations, not just threshold values

The engineer still reviews and approves changes, but the expensive initial investigation steps that they would perform anyways happens automatically.

You can also decide to gradually give the agents authority and have them prepare fix PRs. The process can be performed by the triage agent itself or delegated to a coding agent with the necessary context. An example of such functionality is the Autofix Sentry.

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Release notes and changelogs

Writing release notes is easy to skip and hard to do well under deadline. Agents can generate a draft from merged PRs and commit messages, filtered and grouped by audience, which you can later refine.

In order for this to work, the PR titles and descriptions should be written consistently. It’s good to include a template of what a release note should contain (for older projects, previous release notes can be used as examples) and specify the audience.

The result usually needs editing, but it is still faster than writing from scratch.

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Dependency and security hygiene

Larger projects can contain lots of dependencies, and keeping them up to date is often troublesome. An agent can review whether a major-version update is safe given your actual usage of the library before you spend time on it. Security scanners can be wired to an agent that triages CVEs and drafts upgrade paths.

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