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Transforming Software Development at NML

BY PAUL CARTMEL
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Any sufficiently advanced technology is indistinguishable from magic.

The best-known and most widely cited of Arthur C Clarke’s three laws.

Another axiom relevant to the world of software development and AI is this:

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Bullshit in, bullshit out.

Those two truisms should be given in an AI-first world. So, what will help a software development company like NML differentiate itself from its peers in the coming years?

Let me give you some of my thoughts and thus introduce an AI-first series of posts I’d like to publish.

Sixteen years ago, I launched the software development house NML. In 2016, NML birthed Atura, an AI-first client service chatbot. Doing so thrust me into the thick of the rapidly evolving world of AI, particularly robotic process automation and natural language processing, well before AI was a hot topic in public discourse.

The advent of AI-driven code generation is creating a major shift in software development. It is forcing my team at NML and me to rethink the skillset we need. Over the next three years, we will disrupt ourselves from the inside out, leveraging the accelerated learnings gained through Atura.

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Do more with less.

The CTOs and CIOs in our client base are already asking for this: essentially higher sprint velocities using AI-driven code. What we cannot bypass if we want to avoid producing bullshit and instead create magic is the human interaction required to refine and implement AI-generated code.

Interacting with LLMs and using retrieval-augmented generation (RAG) off domain-specific documents will become a basic, commoditised task. NML and Atura’s differentiators, I believe, will be the ability to build client-specific machine-learning models, refine autogenerated code, and trigger complex and dynamic language flows that interact with operational systems—that is, don’t just retrieve basic textual answers.

For these reasons, my last two hires have been actuaries with little understanding of designing and writing commercial code. They’re learning fast with a little help from their AI friends.

These are interesting times, and adapting to a changing landscape is becoming more critical than growth under rapidly ageing business models and structures. I’m enjoying the change.

Follow me as I go deeper into how we are rethinking our software business at NML in my upcoming posts.

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