Glossary

AI that doesn't just answer but plans, uses tools and completes tasks.

Development with an AI agent, while an experienced engineer owns the architecture and review.

Building in short iterations with a working result after each one.

A program built on a language model that gets a goal, not just a question.

The rules for who may build and run AI in the company, and how.

When AI confidently makes things up: wrong facts, code that won't run.

Oversight of the software people in your company build with AI.

Instruction packages that teach AI to work by your company's rules.

The interface programs use to talk to each other and share data.

A monthly fee for a working app, including hosting, operations and oversight of the code.

SEO for the App Store and Google Play so people find your app.

Tests that click through the app like a user on every code change.

The invisible part of an app: servers, databases and business logic.

A program that answers questions in a conversation but doesn't act on its own.

Automation that builds, tests and deploys every code change.

A check of code by a person or AI before it goes into the app.

One codebase that runs on both iOS and Android.

Building software to fit one company instead of an off-the-shelf product.

Development and operations joined: frequent, safe, automated releases.

The EU's AI regulation that applies to companies using AI, not just building it.

The visible part of an app: screens, buttons and everything the user controls.

AI that creates new content: text, images, code, audio.

A version control system: the history of every code change in one place.

Safeguards that let AI and people move fast without causing damage.

Where the app runs and who keeps it running: servers, backups, updates.

The two native app languages: Kotlin for Android, Swift for iOS.

An AI model trained on huge amounts of text that understands and writes language.

Releasing the app and keeping it alive: monitoring, updates and growth.

The open standard that connects AI models to your tools and data.

Software that runs on a phone and installs from the App Store or Google Play.

Knowing the app is down before your users tell you in a review.

The first version of an app with just what real users need.

A mobile app written in the platform's own language: Swift for iOS, Kotlin for Android.

A controlled attempt to break into your app before a real attacker tries.

Designing how an app looks and works, tested before any code is written.

The analysis phase before development that kills bad ideas while they are cheap.

The one person on your side who decides what gets built and when.

A web app that behaves like a mobile one, no app store needed.

Giving AI precise instructions and the right working context.

A clickable model of the app for testing an idea before any code is written.

Everything that keeps the app working: tests, device checks, security.

A way to let AI answer from your own documents instead of from memory.

Rewriting code to do the same thing, only cleaner and easier to extend.

Planning what, when and how ships to the App Store and Google Play.

Requirements quietly piling up until the project runs late and over budget.

AI tools and apps your employees build and run without IT knowing.

Software you rent monthly instead of owning, like Slack or HubSpot.

The hidden cost of quick fixes that makes every future change pricier.

Watching real users work with the app to find where they get stuck.

Building an app by describing it in plain language while AI writes the code.

Lovable, Cursor and friends: tools that turn a description into an app.

An app that runs in the browser: portals, internal systems, B2B tools.