02 Mar 2025
No-code and low-code platforms have moved far beyond experimentation.
What started as tools for prototypes and internal tools is increasingly used in corporate environments — for dashboards, workflows, integrations, and even customer-facing applications.
Industry forecasts suggest that a significant share of new business applications will be built on no-code or low-code platforms in the coming years. This reflects a real shift in how organizations approach software delivery — but also raises important questions about limits, risks, and long-term sustainability.
This article examines:
Several structural factors drive adoption.
Organizations are expected to test ideas, launch internal tools, and adapt processes faster than before.
No-code platforms:
This is particularly attractive for early validation and internal use cases.
Qualified developers remain scarce, especially in specialized domains.
Low-code tools:
This does not remove the need for developers — it changes how their time is used.
Many business problems are not algorithmically complex, but process-heavy.
Workflow automation, approvals, data synchronization, and reporting often benefit more from:
than from custom code.
Used appropriately, these platforms are effective in several areas:
Their strengths lie in speed, accessibility, and standardization.
For organizations, this can reduce friction between business and IT — when governance is clear.
Despite their strengths, no-code and low-code platforms have constraints.
As soon as applications require:
configuration-based systems reach their limits.
Workarounds often introduce hidden complexity.
Many platforms are optimized for moderate usage.
At higher scale:
This can become a concern for customer-facing or mission-critical systems.
No-code platforms abstract away infrastructure — but also control it.
This creates:
In regulated or long-lived systems, this requires careful evaluation.
A common misconception is that no-code removes the need for architectural thinking.
In practice:
Without architectural discipline, no-code projects can accumulate technical and organizational debt just as quickly as custom systems.
Many successful organizations adopt a hybrid approach.
For example:
This allows:
The question is not no-code or code, but where each fits best.
In European contexts, additional factors matter.
Organizations must consider:
Not all no-code platforms offer sufficient transparency or control for regulated environments.
This does not disqualify them — but it requires informed selection and clear governance.
The decision should be guided by:
No-code accelerates delivery — but acceleration without boundaries can create downstream costs.
No-code and low-code platforms are neither a universal replacement for software development nor a temporary trend.
They are tools — effective when applied to the right problems.
Organizations that benefit most:
In that context, no-code becomes an accelerator — not a constraint.
Enter your email to receive our latest newsletter.
Don't worry, we don't spam
Anna Hartung
Anna Hartung
Anna Hartung
As digital systems scale, software itself increasingly contributes to energy consumption. This article explores what green coding means in practice, where software efficiency directly affects energy consumption, and how technical decisions influence both sustainability and performance — with a focus on realistic, measurable improvements.
While practical quantum computers are still years away, the direction of the industry is already influencing strategic decisions — particularly in security, cryptography, and long-term infrastructure planning. This article focuses on what quantum computing actually is, what quantum advantage means in practice, and why quantum security matters long before quantum computers become mainstream.
As connected devices, sensors, and real-time systems proliferate, edge computing — processing data closer to where it is generated — is gaining importance. This article explains what edge computing means, why it is closely linked to IoT and 5G, and when edge architectures make sense for real systems — with a focus on practical constraints and architectural decisions.
Today, multicloud setups are no longer the exception. They are a strategic response to vendor dependency, regulatory requirements, and specialized workloads. At the same time, cloud spending has become a board-level topic. This article explains why multicloud strategies are becoming standard, how FinOps changes cloud cost management, and what organizations should consider to stay flexible and financially predictable.
With the adoption of the EU Artificial Intelligence Act, Europe introduced the world's first comprehensive legal framework specifically governing AI systems. This article explains what the AI Act regulates, how the risk-based approach works, and what companies should consider when building or deploying AI-enabled products. This is an informational overview — not legal advice.
Artificial intelligence is changing cybersecurity on both sides of the equation. Attackers use AI to automate and personalize attacks, while defenders rely on machine learning to detect anomalies and respond faster. This article explores how AI changes modern cyber threats, where AI genuinely improves defense, and how organizations can approach AI-driven security responsibly.