AI-driven implementation of your software project

Individual software is worthwhile for companies when standard solutions do not precisely represent business processes or when strategically important competitive advantages are required. A tailor-made solution can be flexibly expanded, does not entail any license dependencies and – implemented correctly – ensures long-term investment security.

generic.de works according to the principle Develop the right thing right and divides every project into four phases: Design (sharpen problem & vision), Discover (plan software concept, effort & costs), Develop (implementation using the Dual Track Agile process) and DevOps (Operations & Support). Typical guidelines: 1-2 weeks of ideation, 2-12 weeks of concept, 3-6 months of implementation; subsequent operation is continuously scalable. This structure provides early cost transparency, rapid MVP results, and continuous improvements.

We use AI-powered support across all four phases: agents assist with research, specification, and implementation. Approvals remain with humans at defined checkpoints – no result moves to the next phase without being verified.

Typical benchmarks: 1–2 weeks for ideation, 4–16 weeks for conceptualization, and 3–6 months for implementation; subsequent operations are continuously scalable. This structure provides early cost transparency, rapid MVP results, and continuous improvement.

In the ideation phase, we identify business problems, prioritize ideas and formulate a reliable product vision – the basis for your software concept.
Together with our innovation partner Novazoon, we conduct methodologically based ideation workshops: In the Novazoon Innovation Lab, trends are analyzed via tech radar, prototypes are built and user feedback is obtained before the most promising use cases move on to concept development.
The added value: Outside-in perspective, TÜV-Süd-certified innovation methods and access to a 45-strong network of experts. The result is valid solutions that are seamlessly integrated into the subsequent software project and the agile development backlog – completely without vendor lock-in and with a clear budget preview.

The software concept is developed during the discovery phase. It translates business goals, user needs, and technical frameworks into a prioritized product backlog, wireframes/UX prototypes, and a realistic roadmap. A solid concept reduces subsequent change costs, enables reliable cost estimates and forms the basis for investment decisions – a central element of successful custom software projects.

In an AI-driven approach, the concept takes on a second function: it is no longer just a basis for your decision-making, but machine-readable context for the AI agents during implementation. The more precisely requirements, architecture, and acceptance criteria are documented, the better the final result will be. AI does not make good conceptual work obsolete – it makes it the decisive lever.

Dual Track Agile combines two work streams: discovery (continuous idea validation with user testing) and delivery (incremental development). As a result, only features that have already been validated flow into programming; the team avoids bad investments and can implement user feedback close to the sprint. We use Dual Track Agile to shorten time-to-value and optimize UX & code at the same time.

With AI support, the balance between both tracks shifts: implementation in the delivery track becomes significantly faster, making discovery the pace-setter. That is precisely why we invest the time gained into validation rather than more code – you get more iterations within the same budget, not just the same result sooner.

In terms of programming, yes: our experience from past projects shows that we can write code up to 3x faster with AI agents. However, this does not translate to the same ratio over the total project duration, because the bottleneck in software projects has rarely been writing code, but rather clarifying requirements, coordination, and approvals. What you actually gain is more iterations, more validation, and more fine-tuning – in other words, a better product – for the same budget.

The biggest cost driver comes later anyway – over five to ten years, the higher costs arise from maintenance and further development, not from the initial creation of your custom software. That is exactly where Clean Code makes an impact. You can see how your project pays off over its entire lifecycle by running your own scenarios with our TCO calculator.

Clean Code has been at the center of every software development at generic.de since 2010. It includes clearly named classes & methods, low coupling, high test coverage and automated quality checks. As a result, your individual software remains permanently maintainable – changes cost less, bugs are identified early and the time-to-market is reduced. In the “Develop” development phase, clean code practices and concept work run in parallel in the Dual Track Agile process; this creates investment security and makes refactorings the exception rather than the rule.

In short: Clean Code reduces technical debt, lowers total operating costs and future-proof your software concept – a central quality anchor for every successful software project.

In the age of AI, there is an additional factor to consider: AI agents work with the same code as humans. Cleanly structured, clearly named code is easier for them to grasp, making it more efficient to modify and develop further. Messy code doesn't just slow down your team; it also hinders every AI tool that works on it later, effectively doubling the cost of any future development.

We combine classic project controlling – such as budget tracking and milestone reports – with Dual Track Agile: Discovery and delivery streams run in parallel, which means that planning and implementation are continuously coordinated. Our internal PMO creates weekly burn-down charts and financial reports so that clients always have full transparency about costs and progress.
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Many competitors rely on so-called “agile fixed price models” to combine sprint flexibility with predictability – but often resort to rigid contract structures that quickly reach their limits when scope changes.
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Our approach remains leaner: Through continuous delivery, automated monitoring and a clearly defined definition of done, individual software can be iteratively optimized – without hidden change requests and with clearly measurable time-to-value.

At generic.de, clients receive unrestricted, perpetual, and global usage and exploitation rights to the complete source code, designs, and the AI development environment, including the harness – no vendor lock-in, full IP security. This sets our approach apart from many agencies that only grant basic usage rights. From a legal perspective, it is generally advisable to explicitly stipulate the transfer of rights in your contracts; otherwise, you may be left with only limited usage rights by default (Section 69 of the German Copyright Act).

This remains unchanged even when code is generated with the help of AI: You receive the complete source code along with all documentation. Furthermore, your code is never used to train AI models – this is guaranteed through privacy mode settings and data processing agreements with all providers involved.