Each package starts from a concrete challenge in your software development and ends with a result your team can use right away. It starts with a free initial assessment. If the package fits, we clarify the assignment in a second meeting. The offer fixes scope, duration and price before work begins.
Slow releases, heavy manual testing, new regulatory requirements, or the question of whether AI actually improves productivity: often the technology is not the real problem. What is missing is clarity about where an investment truly pays off.
That is why every project starts with a clearly defined goal, a fixed scope, and a measurable result. You only invest further once the benefit is visible.
When defects are only found by customers, manual testing delays releases and nobody knows exactly what the tests actually cover.
When your software product may fall under the Cyber Resilience Act and you need clarity on what concretely has to be done technically.
When AI should not stop at individual developers but work across your whole team's development process, including a large or long-grown codebase.
For other clearly scoped software, test automation, CI/CD, or AI/ML projects you also receive an individual fixed-price offer.
Together we clarify goal, scope, and desired outcome. You then receive a transparent offer with defined deliverables, timeline, and fixed price.
All prices are net, plus VAT.
Answers to general questions about pricing, the initial assessment and the way of working are in the FAQ on the home page. View FAQ
LLM stands for large language model. It has been trained on very large amounts of text and source code and generates answers, text or code that fit a given input. On its own, an LLM does not act, it only responds. It runs as a cloud service or, for open models, on your own infrastructure.
An agent is a system in which an LLM does not just respond but plans and carries out steps on its own: it reads information, calls tools, checks the result and decides on the next step until a task is done. People decide which tools and permissions an agent gets.
A coding agent is an agent for software development. It works directly in the codebase: it reads existing code, changes files, runs builds and tests and corrects itself based on the results. Unlike plain code completion, it handles whole tasks across several files. Examples are Claude Code, OpenAI Codex, OpenCode and GitHub Copilot.
Agentic engineering is software development in which coding agents have a defined place in the development process. People write requirements and specifications and make the architecture decisions, agents implement subtasks, and tests, reviews and CI/CD safeguard quality. The goal is not as much generated code as possible, but maintainable software finished sooner.
An agentic harness is the environment in which coding agents work reliably in a specific project: context on architecture and conventions, rules and guardrails, approved tools, tests as feedback and clear hand-over points to people. The harness is what turns a general-purpose agent into one that fits your codebase. It is the central result of the AI Developer Productivity Sprint.
A regression is a defect in a feature that used to work, caused by a change elsewhere. Regression tests check after changes that existing behaviour is preserved. Their scope grows with the software, and when run manually they delay releases. The Test Automation Sprint uncovers gaps in testing, prioritises by risk and effort and clarifies which tests are worth automating.
CI/CD stands for continuous integration and continuous delivery or continuous deployment. With continuous integration, every code change is built and tested automatically as soon as it is merged into the shared codebase. Continuous delivery keeps tested versions ready to ship at any time; continuous deployment ships them automatically. Common tools are GitLab CI/CD and GitHub Actions.
DevOps brings development and operations together into a shared responsibility. Instead of handing software over to a separate operations team, teams automate build, test, delivery and monitoring and get fast feedback from production. CI/CD is its technical backbone.
The Cyber Resilience Act is Regulation (EU) 2024/2847 on cybersecurity requirements for products with digital elements, meaning hardware and software placed on the EU market. Among other things, it requires security from the design stage, vulnerability handling across the whole lifecycle, security updates and technical documentation. Reporting obligations have applied since 11 September 2026, the remaining obligations apply from 11 December 2027.
SBOM stands for software bill of materials, the parts list of a piece of software. It lists a product's components and their versions, including open-source libraries. This makes it quick to check whether a product is affected by a newly disclosed vulnerability. The CRA requires manufacturers to draw up an SBOM in a commonly used, machine-readable format covering at least the top-level dependencies of the product. It is part of the technical documentation and does not have to be made public. Widespread formats are SPDX and CycloneDX.
Slow releases, open CRA questions, or AI without measurable impact: 30 minutes are enough for an initial technical assessment and a clear next step. Free of charge and non-binding, and you talk directly to me, Christopher Weber.
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