Is your AI prototype a sound foundation?
Before the next development step, I assess which parts can support a product, where technical risks lie, and which improvements should come first.
Review your prototype →From Fast Prototype to Dependable Software
From AI-built prototypes to professional software development, I help companies put rapidly developed software on a sound technical foundation and use coding agents reliably in their development work.
Three typical starting points
The right format depends on whether code already exists, a product implementation is planned, or an established codebase needs to be improved for coding agents.
From prototype to production-ready product
Your prototype works, but is not yet a dependable product? I help you get there through technical assessment, architecture, implementation planning, technical guidance, and hands-on implementation as needed.
From prototype to product →Are coding agents unreliable in your codebase?
In the pilot, we use concrete development tasks to identify what holds the tools back. You receive prioritized improvements to architecture, tests, and development workflows.
Book a pilot call →Technical foundations of the work
What matters is not how the software was created, but whether it is fit for its intended use.
01
Architecture and data model: System boundaries, responsibilities, integrity, and critical business logic.
02
Changeability: Coupling, module boundaries, local change context, and documented contracts.
03
Validation: Reproducible builds, tests, type checks, and quality checks.
04
Delivery and operations: Deployment, observability, recovery, and controlled releases.
05
Security baseline: Permissions, secrets, attack surfaces, and identifiable baseline risks.
From question to sound decision
Every engagement starts with an agreed goal and scope. Depending on your needs, it leads to a technical assessment, an implementation plan, or concrete software changes.
01
Scope
Define the use case, critical workflows, repository status, and pending decision.
02
Analysis
Examine code, structure, data, tests, delivery, and operational information.
03
Evidence
Support findings with concrete references, impacts, and uncertainties.
04
Decision
Keep, harden, refactor, or replace incrementally.
05
Implementation as needed
Guide development or implement and validate the agreed features.
06
Handover
Review outcomes, implemented changes, and next steps together.
What you receive
Deliverables depend on the agreed scope, from assessment and planning to implementation.
01
An independent architecture decision instead of an automated maturity score.
02
Technical findings with evidence, impact, priority, and uncertainty.
03
A decision for each relevant system part instead of a blanket rewrite recommendation.
04
A plan your internal team or another agency can implement.
05
Where included in the engagement: technical guidance and implemented, tested software features.
Clear boundaries
01
No pentest: Security is a visible review area, but this is not a formal security test or certification.
02
Agreed scope: Architecture reviews remain focused assessments. Prototype-to-product work can include technical guidance and implementation.
03
Outcome-focused collaboration: We agree on clear goals, responsibilities, and a framework suited to your project.
04
No AI strategy consulting: The focus is software architecture, testability, delivery, operations, and modernization.
Which starting point would you like to assess?
Choose an available time to discuss the application, context, tools used, and the next decision.