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Vibe coding is a structured practice, not a fad. At Access, it multiplies productivity by 2 to 3 on legacy modernization projects, without sacrificing the quality of delivered code. We build with AI what we deploy for our clients.
Vibe coding is not "asking ChatGPT to write code in place of the developer". Nor is it an experimental project confined to a few prototypes.
It is a development discipline in which the engineer dialogues with an AI (Claude Code, Cursor, Copilot) in natural language, iterates on proposals, arbitrates, tests, and merges. AI accelerates production; the human keeps judgment, validation, and responsibility.
We practice it every day, on the most critical legacy modernization projects: COBOL to Java, Delphi to .NET Core, BizTalk to Azure Logic Apps.
At Access, vibe coding is governed by five non-negotiable rules.
One — Systematic human review: no AI-generated code merges without human pull request, with tech lead. Two — Strategic prompt traceability: pattern migration, audit, and architecture prompts are versioned in a dedicated repository. Three — Confidentiality: client personal data never sent to public models without filtering or pseudonymization. Four — Model choice case by case: Claude for complex reasoning, local models for maximum confidentiality, Copilot for autocomplete. Five — Monthly quality audit: test bench on AI-generated code vs manual code.
Each new consultant follows a 2-day internal training then framed pair-programming for 4 to 6 weeks with an Access mentor. There is no "self-taught vibe coding" in our teams.
On a recent COBOL to Java migration program, we measured productivity per pattern: 500 to 1,500 lines of code migrated per person-day depending on complexity. Classic manual methods plateau around 200 to 500 lines per day.
This productivity does not translate into lower quality. The migrated code is more consistent (AI applies a uniform style), better documented (auto-generated then validated comments), and better tested (unit tests suggested at each function).
The gain is reinvested by the client: more tests, more documentation, more exploratory POCs, or simply a project that finishes faster and costs less.
Vibe coding is not a black box delivered packaged. During the program, client teams are trained on Access's practices, tools, and patterns. Strategic prompts are shared. Monthly workshops transfer the know-how.
At delivery, the client team does not just have modernized code. They have an autonomous team, capable of continuing evolutions with the same AI tools, the same level of rigor, and the same quality guarantees as us.
This is our principle: do not create dependency. Capacity building is planned from the Discovery phase, not improvised at delivery.
Yes, when reviewed and tested like any code. At Access, no AI code merges without human review. Unit tests are mandatory. Vibe coding accelerates production, it does not remove rigor.
Depends on context. Generic code: Claude Code or Copilot in cloud. Sensitive data: privately hosted models (Mistral self-hosted, Azure OpenAI with tenant isolation). No personal data in public cloud without explicit agreement.
No. It frees them from repetitive tasks and lets them handle more value (architecture, review, arbitration, mentoring). An AI-augmented senior produces what two or three non-augmented seniors used to deliver.
Yes. This is the principle of capacity building. We train the client team during the program, transfer the patterns, prompts, and evaluation tools. The client becomes autonomous on the practice.
We frame every program at Intake, with transparent budgeting. A short POC of a few weeks can be delivered before committing to the full program.
See a vibe-coding demo →