AI-assisted delivery
Vibe Coding to Production: How to Manage an AI-Assisted Build
Vibe coding can produce a prototype quickly. The real work is turning it into a usable, reviewable, and maintainable system.
A prototype is not production
AI-assisted development can move an idea from a blank screen to a working prototype quickly. That speed is useful, but a prototype is not yet a system a team can trust with real users, real data, or daily operations.
The project work begins when the first version exists: clarify the user outcome, make the architecture understandable, test the edges, control access, and document what another person needs to maintain.
Start with the outcome
A technical project should begin with the result the organisation needs, not with a list of tools. Ask what should be different for the business or the user when the project is finished. This keeps the plan connected to value instead of activity.
For example, “build a dashboard” is an activity. “Give the marketing team reliable access to current product and pricing data so it can make faster decisions” is an outcome.
Define the boundaries
Good scope makes it easier to say what the project will and will not deliver. Write down the primary users, core capabilities, integrations, data sources, and acceptance conditions. Record assumptions as explicitly as constraints.
A useful scope conversation also identifies what can move to a later release. Protecting the first usable version is often more valuable than promising every possible feature.
Build a plan people can use
A work breakdown structure turns the goal into phases and activities. Each activity should describe an action and the result it produces. That makes the plan useful for coordination, not just for creating a list of tasks.
- Discovery: understand the current process and the people affected.
- Design: define the target workflow, data model, requirements, and decisions.
- Build: create the product, integration, automation, or migration steps.
- Validate: test real scenarios, risks, data, usability, and acceptance.
- Roll out: support adoption, documentation, ownership, and handoff.
Plan for decisions and uncertainty
A schedule is not a risk strategy. Add a risk register, an issue log, and a decision log to the project controls. For each meaningful risk, document probability, impact, owner, response, and trigger. For each decision, capture the options considered and why one was selected.
This is especially important when technical work includes vendors, data quality, access permissions, changing requirements, or dependencies outside the team’s control.
Keep the plan connected to reporting
A plan becomes useful when its milestones can feed status reporting. Leaders should be able to see what is complete, what is at risk, what needs help, and which decisions are pending. The reporting format should make the next action obvious.
The AHI App project in my portfolio is an example of this connection: the charter defines the goal, the WBS structures the work, the risk register surfaces uncertainty, and the status report turns progress into decisions.