Letting Kiro Drive - Autopilot and Hooks

Following on from my previous post, I thought I would dive a little deeper into two specific features with AWS Kiro that I use frequently. Two features that I feel work well for my use cases.

As I build trust with agentic workflows, I find myself delegating more tasks (of specific types) to Kiro’s agent. That trust is building through the spec-driven development nature of Kiro, and the approach that it takes.

Tasks are broken down into small, atomic pieces of work that have been defined and reviewed up front. This approach makes it much more comfortable to enable “autopilot” mode with Kiro, in combination with hooks to allow the agent to handle these tasks with confidence.

What Autopilot Actually Does

AI-driven software development workflows have came a long way from just a glorified autocomplete. The notion of allowing the agents to take the wheel, and have full control over tasks has became the norm and this has resulted in some higher-level observability and review settings:

• Autopilot mode is the more autonomous mode where Kiro can take a higher-level goal (like “add tests” or “refactor this module”) and then propose the concrete edits to get there.
• Supervised mode keeps the same underlying engine but requires stepwise approval, so you review changes in smaller slices instead of one giant diff dump.

Under the hood, autopilot leans on Kiro’s spec‑driven workflow: requirements, design, tasks, and the eventual diffs are all linked, which makes it possible to trace a change back to its origin.

Agent Hooks in Day‑to‑Day Dev

In contrast to autopilot, agent hooks are the little agents that quietly keep your house in order.

• Hooks are event‑driven triggers e.g. on save, on file created etc.
• Kiro also supports manual hooks using the userTriggered type, which you can fire on demand when you want a specific workflow to run.
• Common patterns include updating tests or documentation whenever a file changes, or running lint/security checks automatically on certain paths.

I think of hooks as new-gen scripts (Bash, PowerShell etc.) - very similar to pre/post build, compile, or lint scripts but more intelligent given the context that they can consume and act upon.

A Tiny Hook With Massive Impact: Conventional Commits

Not every use of Kiro (or agentic workflows as a whole for that matter) needs to be a big refactor. Some of the highest-leverage changes are the ones that shave 30 seconds off tasks you do dozens of times a day.

One of my most frequently used hooks in this setup is a manual, user-triggered hook that generates Conventional Commit style messages for the currently staged changes:

This uses Kiro’s userTriggered hook type, which makes the hook available as an on‑demand action in the IDE, which sends a structured prompt plus the current Git diff to the agent.

The prompt itself encodes the Conventional Commits rules - type(scope): description plus an optional BREAKING CHANGE footer - so in practice the workflow becomes:

• Stage changes as usual.
• Trigger the “Conventional Commit Message” hook.
• Let Kiro propose something like feat(api): support filtering by status or fix(auth): handle expired refresh tokens gracefully, complete with a breaking-change footer when necessary.

The result is that the repo gets consistently structured commit history, semantic versioning stays sane, and nobody has to mentally juggle the Conventional Commits spec while in the middle of a refactor.

A real example of this that I have used for one of my projects can be seen below:

This is a nice microcosm of how hooks work best: encode a convention once in a hook, and then reuse that decision every time with a single trigger.

Setting Boundaries For Autopilot

Letting an agent touch many files at once is liberating until it starts sprawling changes in areas that you might not have anticipated updating as part of the current item of work. This is where autopilot mode can begin to get out of hand, so it’s important to ensure that boundaries are clearly defined and set.

A few patterns that kept things sane:

• Scope autopilot by intent: As with all AI-driven development work, a significant amount of importance is on the prompt. With Kiro’s spec driven nature, I find it really easy to explicitly scope autopilot per task which works great for me.
• Prefer supervised flows for risky areas: Infrastructure, auth, and anything that touches external contracts are better run in supervised mode to force smaller, reviewable steps. For areas like this, I typically find myself using the agent as more of a Q&A partner rather than allowing it to control the direction.
• Align hooks with existing policies: If your team already has rules like “integration tests for new endpoints” or “docs for public APIs”, encode those as hooks instead of inventing new, opaque automation that nobody can reason about.

The goal isn’t to stop Kiro from making mistakes whenever you give it the keys, but to ensure those mistakes are easy to spot, easy to revert, and clearly tied to an explicit intent rather than vague prompts.

Kiro Take the Wheel: Pros and Cons

There’s a genuine trade-off in letting an autonomous agent loose on your production codebase. This isn’t a demo branch; the changes need to age well.

Where Kiro shines

• Velocity: Multi-file transformations, test generation, and doc updates happen in one pass at the time of writing rather than coming back to it in the future - even if it’s a PoC!
• Fewer boring tasks: The likes of boilerplate, and glue code, move out of your head and into hooks and autopilot tasks.
• Consistency: Hooks enforcing tests, docs, checks, and even commit message formats across the project helps to drive consistency.

The costs you have to own

• Review fatigue: Large, agent-generated diffs are tiring to read - even if they are scoped to an individual Kiro spec task. Without discipline, they encourage rubber-stamping.
• Over‑eager changes: autopilot will happily assist in adjacent areas if your intent is vague, which can introduce churn or subtle behaviour changes that may result in unintentional bugs.
• Trust gaps: You absolutely cannot blindly trust the code that the agent generates - it needs to be reviewed. This goes hand-in-hand with the first point around fatigue here.

Healthy use of Kiro looks less like fire and forget, and more like pairing with another engineer: give clear instructions, review carefully, and never merge something you wouldn’t defend in a post-incident review.

Observability Playbook

If you’re going to let Kiro drive on real work, a lightweight playbook helps keep both your repo and your attention span intact.

• Start in supervised mode on critical areas. Switch to autopilot for well-scoped, low-risk improvements like adding tests or aligning docs.
• Use hooks to automate what you already require (tests, docs, checks, Conventional Commits).
• Tie every autopilot run to a clear spec and make that spec part of the PR description, so reviewers see the why as well as the what.
• Keep CI, static analysis, and policy gates in front of production; agents make it easier to pass them, not optional to have them.

Done well, you end up with a workflow where Kiro handles the grind - tests, docs, type tightening, commit hygiene, repetitive refactors - while you stay responsible for intent, boundaries, and everything with real blast radius.

There is no doubt that it requires a shift in both mindset and hands-on working approach, but trying it out and being open to said changes might unlock some efficiencies in how you work on a daily basis.

Resources

If you’re interested, the full JSON definition for my conventional commit hook is as follows:

{
  "enabled": true,
  "name": "Conventional Commit Message",
  "description": "Automatically generates a commit message following conventional commit standards based on the current git diff",
  "version": "1",
  "when": {
    "type": "userTriggered"
  },
  "then": {
    "type": "askAgent",
    "prompt": "Review the current git diff and write a commit message following conventional commit standards. The format should be: type(scope): description. Common types include: feat, fix, docs, style, refactor, test, chore. Keep the description concise and in present tense. If there are breaking changes, include BREAKING CHANGE in the footer."
  }
}

Give it a try, and let me know what your experience with it is!