Engineering workflow assessment
Review how work moves from issue to release. Observe representative tasks and identify where agents help with exploration, implementation, tests or documentation.
AI for engineering teams
Claude Code & Codex Adoption for Engineering Teams
Help your whole engineering team deliver well with AI.
Discuss your workflowThe operation, connected
Help your whole engineering team deliver well with AI.
Aiwah helps engineering teams make coding agents part of a repeatable delivery practice. We work with the repositories, tasks and review process your team already uses, then establish the context, tooling and habits needed to produce changes that engineers can understand and maintain.
A coding-agent licence does not establish a shared engineering practice. Individual developers may get useful results while others spend more time correcting generated work. The missing pieces often include clear project context, reliable local setup, focused tasks, useful tests and a consistent review process.
- A few developers use AI effectively, but the practice has not spread across the team.
- Agent-generated changes create excessive review work or miss repository conventions.
- The team cannot tell whether AI is improving delivery after accounting for rework.
What we can build
Purpose-built capabilities.
One connected system.
Scope the combination that solves your operating problem, with clear responsibilities for software and people.
Repository context and instructions
Create maintainable project guidance describing architecture, conventions, commands and boundaries. Keep instructions discoverable and close to the code they describe.
Development environment and tool access
Make setup, dependency installation and local checks reliable. Connect approved development tools with access appropriate to the task and a clear owner for credentials.
Testing and review practice
Define the evidence a generated change needs before review. Use existing quality standards, focused tests and human code review to evaluate behaviour and maintainability.
Practical team enablement
Work with engineers on real tasks in their repositories. Teach scoping, delegation, debugging and review through completed changes the team can discuss.
Adoption and delivery measurement
Track cycle time, review effort, defects and rework alongside tool cost. Use the findings to improve the practice instead of treating generated code volume as success.
Agent-assisted deliveryAgents work inside a reviewable engineering loop.
Repository context, tests and human review determine what reaches production.
An example workflow
From the first signal
to the next accountable action.
This is a starting point for design. The actual workflow, permissions and integrations are scoped around your operation.
- 01
Select a repository and task
Choose representative work with an engineer who owns the result. Observe the current effort and establish a starting point.
- 02
Prepare the working environment
Improve instructions, setup and test commands. Configure the agent and approved tool access for the selected workflow.
- 03
Deliver with the team
Complete actual changes, review the output and capture what made the process reliable. Refine the guidance from those lessons.
- 04
Extend the practice
Document the approach, train more team members and review delivery results. Give the practice an internal owner who can keep it current.
Works with your existing tools
Connect the systems that already matter.
We work with your source repositories, issue tracker, CI pipeline and local development tools. Claude Code and Codex are configured around your stack and provider terms; the practice can accommodate other approved coding tools.
Measures we can define together
- Task-to-review cycle time
- Review effort per change
- Defect and rework rate
- Cost of accepted changes
We establish a baseline and agree a measurement method. Results depend on your process, data and adoption; these are measures to track, not promised outcomes.
Related work and thinking
Go deeper through work
we have already published.
Explore existing case studies and essays connected to this service.
From discovery to live operation
A team responsible for the system, not just the handoff.
We begin with a working session around a real example. We map the workflow, identify the costly handoffs and agree the decisions, permissions and integrations the system needs.
We then shape a focused first release, build the operating interfaces and test routine work alongside exceptions and failure recovery. Rollout includes the people using the system and a way to observe whether the change is helping.
You keep practical control of the code, workflows, business logic, data and operating context we create, subject to third-party services and licences. Support and continued improvement are scoped with the engagement.
Read about security and controls →Before we begin
Your questions,
answered clearly.
Is this a training workshop?
Working sessions are part of it, but the engagement also improves repository context, environment setup and the review workflow. The goal is a practice the team can use after the sessions end.
Do you replace our engineers?
Your engineers keep ownership of architecture, correctness, reviews and releases. We help them delegate suitable tasks to coding agents and evaluate the resulting changes effectively.
How do we know whether adoption is working?
Agree a representative set of tasks and compare completion time, review effort, defects and tool costs. A useful evaluation includes the work required to accept and maintain the change.
Explore connected services
Bring one important workflow
What should work better
in your business?
Tell us where the operation slows down, what your team is doing manually and what a better result would look like.
Book a meeting