In technology, simplicity often outperforms complexity. This principle shapes how Zeidler Group designs legaltech solutions for the investment fund industry—building systems that solve problems effectively without unnecessary complication.
Zeidler recently delved into AI why clarity is vital.
A line from Anthropic on agentic AI captures this idea well: “Start with the simplest solution possible and only increase complexity when needed. Success isn’t about building the most sophisticated system; it’s about building the right one.” In software architecture, this mirrors the debate between microservices and monoliths. While microservices can be flexible, they also introduce latency, costs, and multiple points of failure. Often, a modular monolith is more efficient.
This thinking is particularly important in AI evaluation. Unlike traditional machine learning models, which delivered clear outputs, large language models generate open-ended results that vary each time. Evaluating these outputs requires clarity and robust frameworks, as relying on AI to judge other AI models remains an unsettled practice.
Bigger models are not automatically better. Large systems with billions of parameters hold potential, but their true value depends on the data they are trained on. Scale alone is wasted without clarity on its purpose.
The focus should be on practical design and application. At Zeidler Group, software engineers, lawyers, and regulatory experts collaborate to create solutions that combine technology with legal precision, enabling fund managers to navigate regulation with confidence.
Simplicity also extends to code. Writing clear, self-documenting code helps new team members and stakeholders understand intent quickly. Good code communicates as well as functions.
Across AI, software, and legaltech, the lesson is consistent: start simple, communicate clearly, and scale only when required.
For more, read the full story here.
Read the daily FinTech news
Copyright © 2025 FinTech Global
