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Agentic Engineering Platform

From developer self-service to agentic engineering.

We go the whole way with your engineering organization: first a developer self-service that turns days of waiting into an hour, then a DevEx platform your teams like to use, then an Agentic Engineering Platform where agents build and test – and a person approves every change.

Talk to Philipp → See the journey

The journey

Three steps. Each one pays off on its own.

You don’t jump to agents. Each step builds the ground the next one stands on: agents can only work as fast as your platform lets them, and only as safely as your approvals allow.

Step 1 · Developer self-service

Requests that took days now take an hour.

Developers order what they need through a self-service portal in Jira Service Management, with approvals and an asset catalog behind it. At BSH, creating AWS organization accounts and Microsoft Copilot accounts went from several days to one hour.
- Approvals built into the request, not chased by email
- A catalog of cloud resources in Assets as the single source
- A Confluence knowledge base and training, so people actually switch
Case study: change management for developer self-service →Success story: how BSH provisions its cloud infrastructure →
Platform Engineering: How to set up AWS accounts in one hour with a developer self-service Live demo with BSH: account creation, approvals and the Assets catalog in Jira Service Management Cloud. Watch on YouTube
Step 2 · DevEx platform

A platform your developers want to use.

Platform engineering turns the self-service into an internal developer platform: standard paths for building, testing and running software, with security and compliance built in instead of bolted on. Teams spend their time on the product, not on the plumbing.
- Scalability and standardization across teams
- Efficiency and productivity for every developer
- Security and compliance as part of the platform
- Room to experiment without breaking production
What is platform engineering? →Container8 – the developer experience platform →
Container8 — The all-in-one DevOps as a Service platform The platform layer the agentic step builds on. Watch on YouTube
Step 3 · Agentic Engineering Platform

Agents build. People approve.

On top of the platform, AI agents take a requirement to a running change: they write the code and the tests – Playwright end-to-end tests for what the user sees – run them, and record a short video of the result for every requirement. The review becomes a cinema session; an approval deploys it live. Every deployment goes through a risk assessment, and only low-risk changes deploy automatically.
- Tests written with the code: Playwright for the UI, unit and service tests below it
- A video for every requirement, so reviews take minutes
- Approval deploys live; risky changes wait for a person
- A disciplined 10-step workflow with failsafes against hallucinations
- Principles, lessons and architecture decisions kept in the repo for the agents to read
Agentic coding in practice: 10 failsafe steps →AI testing: how every change proves itself →
Automatic Loom video for every requirement – approval deploys live Deployments go through a risk assessment; only low-risk changes deploy automatically. Watch on YouTube

AI testing

Agents write the code. And the tests that prove it.

Agents that ship fast need tests that keep up. We join two things we do every day: the agentic coding workflow, and automated testing with Jira, your CI pipeline and Xray. The result is a change that arrives with its own evidence.

The agent writes the tests
With every change, the agent writes the tests that prove it: Playwright end-to-end tests that click through the user interface like a person would, and unit and service tests below them. A requirement without a passing test is not done.
The pipeline runs them on every build
Your CI pipeline starts the tests automatically on every code change – Bitbucket Pipelines, Jenkins, GitLab CI or another one. When a test fails, the team is notified and the change waits.
Xray for Jira documents them
Results land in Jira, linked to the requirement they test: charts, screenshots for root-cause analysis, and an audit-proof export of the test documentation for your legal requirements.
A person approves what they saw
The video shows the change working; the test results show it holds. With both in front of them, the reviewer decides – and only low-risk changes deploy on their own.

Suitable for Unit testsService testsUI tests (Playwright)Load testsPen testsFailover tests

Automated testing with Jira, Bitbucket and Xray →

For executives · Measured with DX

Every step has to prove itself. In numbers.

Your board does not ask how many licenses you bought. It asks what changed. XALT is an Atlassian Platinum Solution Partner, for DX too, with specializations in Software Development, Service Management (ITSM) and Cloud Migration: we take a baseline before the first step and measure the journey with the DX AI Measurement Framework – per team, never per person, with agents counted as part of the team that directs them.

Utilization
Who uses AI, and for what
Active users, AI-assisted pull requests, tasks handed to agents.
Impact
What gets better – and what must not get worse
Time saved, DX Core 4 throughput and developer experience, next to change failure rate and maintainability.
Cost
Whether the spend is worth it
AI spend per developer against the time it saves, and what an agent hour costs.

Is AI paying off? Measure it like an executive →Talk to Philipp about DX →

Atlassian Platinum Solution Partner

Atlassian Software Development Specialization, EMEA

Atlassian Service Management Specialization, EMEA

Atlassian Cloud Migration Specialization, EMEA

What changes

The work moves. The control stays with you.

	Developer self-service	DevEx platform	Agentic Engineering Platform
Who does the work	The developer, through a portal	The developer, on standard paths	Agents, on the same paths
What people do	Request and approve	Build the product	Decide, review, approve
How it is tested	Manually, or by a test team	Automated in the CI pipeline, results in Xray for Jira	Agents write the tests, the pipeline runs them, Xray documents them, a person approves
Where the rules live	In the approval workflow	In the platform	In the platform and the agent’s workflow

Customer story

BSH x XALT

BSH started with the developer self-service and built the platform with us. Hear it from the team itself.

Read the success story →

BSH x XALT Watch on YouTube

Where is your engineering organization today?

Self-service, platform or agents: Philipp walks you through the step that pays off next for your teams.

Talk to Philipp → Run the AI maturity audit

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