AI IN THE DEVELOPMENT WORKFLOW
Software development with AI support
The team uses AI to support engineering tasks. People remain responsible for architecture, review, testing, and project decisions.
Tools used in the process
Each tool is selected according to the task, project constraints, and confidentiality requirements.
OpenAI Codex
Support for writing, understanding, and changing code within the development workflow.
Claude Code CLI
A coding assistant used in the terminal to analyze and modify codebases.
Claude and GPT-4
Support for technical analysis, planning, review, and documentation.
AI testing tools
Support for proposing scenarios, writing tests, and reviewing coverage gaps.
Where AI helps
Less repetitive work
AI can support mechanical coding tasks and leave more time for analysis and technical decisions.
Review with context
The tools help locate inconsistencies and suggest options. The team reviews the output before using it.
Documentation in the workflow
AI supports documentation drafts, which are checked and adjusted by people who know the project.
Support for writing tests
The tools help propose test cases. The team decides what needs validation and interprets the results.
Frequently asked questions
How do you handle code suggested by AI?
Tool output is treated as a draft. The team reviews, tests, and adjusts the code before adding it to the project.
Which AI tools do you use?
We use tools such as OpenAI Codex, Claude Code CLI, Claude, and GPT-4 according to the task and project constraints.
How do you handle client code and data?
Tools, access, and usage rules are defined according to project sensitivity. Confidentiality duties are part of the agreement with the client.
Does using AI change the team setup?
Team composition depends on scope and responsibilities. AI supports some tasks, but people retain technical responsibility and make the decisions.
Want to assess where AI fits the project?
Tell us what you need to build and which technical or confidentiality constraints we should consider.
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