The future of humanity on the technological front is collaboration with artificial intelligence. The impact of AI can already be seen today but it takes more than just tools to develop quality software products. What the market needs is top-notch development talent, paired with smartly utilized tools to create an efficient combo. At Code & Pepper, we call this combo “centaur developers”. How AI is impacting software development and why we all should pay attention?

In his second lesson of the book “21 Lessons for the 21st Century,” renowned historian Noah Harari delves into the concept of human-AI centaur teams, a mode of collaboration that heralds unparalleled results. Borrowed from the mythological creature – part human, part horse – this analogy brilliantly encapsulates how humans and AI can symbiotically enhance each other’s capabilities. In the realm of software development, the idea has far-reaching implications.

As we step into an age where AI capabilities increasingly intertwine with daily operations, a centaur team’s inception in software development isn’t just a choice; it’s a necessity. However, the goal should not be to promote competition between humans and AI but to leverage the best of both worlds.

An introduction to modern AI

The first breakthrough was a transistor. The second one was modern computing. The third one was the ability to lower the cost of this computing to approximately zero. It’s when you do that, the ability to process the entire internet and data, representing almost whole human knowledge and experience, arises.

That’s exactly the approach of Jensen Huang (actually, Jen-Hsun), the founder and CEO of NVIDIA, currently the second most valuable company in the world. Artificial intelligence specialists, not only at his company, can figure out the meaning (not pattern) of digitized human knowledge. Basically, we can digitize anything and figure out the meaning of it. And “data” is not understood as only written text or photos, because everything becomes data.

You can digitize your customer data and use it as a base for a large-scale model for your fintech company. But you can also sequence the human genome and use it genes as data to synthesize new chemical compounds for drugs. From simple amino acids to the structure of the protein. 

Now, what AI lets us do, is work on a whole new frontier of computational data. Back in the day, a chip was a chip. A small, gradually shrinking piece of tech, is often described as an SoC, which is a system on a chip. Few independent, yet interconnected systems work together on one piece of hardware. What NVIDIA is doing right now, is working on a chip that, yet again, takes up a huge chunk of space. The H100, as it’s called, replaces systems on a massive scale. The cost of cables alone that it replaces, is bigger than the chip itself.

Why is that important?

Because it promotes two simultaneous approaches to AI – hardware and software-based. It cannot happen without talent. Software developers who put effort into digital products and push the boundaries of what’s possible. And when it’s possible.

Time-to-market is equally important. That’s why at Code & Pepper, we embraced the philosophy behind the term “centaur teams”. We have a precise methodology to identify and recruit only the best 1.6% of software development professionals on the market. 

With more than 70 carefully defined attributes, we can target only those who match our expectations and are able to deliver. There are the ones that work with AI and automation tools that support modern development processes.

With this method, we are capable of working on challenging, practical, and impactful fintech and healthtech projects. 

Examples of fintech apps with integrated AI

There are many forms in which artificial intelligence is either used to make apps or is even integrated with them. Here are examples of why it’s good to include AI in projects.

Bud Financial is an AI-powered data intelligence platform that, in their own words, lets companies have  “the access, make sense of, and enrich messy financial data”. With the help of Bud, banks can connect their apps and data to other fintech companies and financial services. Businesses can verify income, assess affordability, monitor it, and use AI to drive money-related decisions.

Ocrolus is a document processing software that combines machine learning with human verification. The software allows businesses, organizations, and individuals to increase speed and accuracy when analyzing financial documents. Ocrolus’ software analyzes bank statements, pay stubs, tax documents, mortgage forms, invoices, and more to determine loan eligibility, with areas of focus including mortgage lending, business lending, consumer lending, credit scoring, and know-your-customer (KYC) processes.

Noetica is an AI-powered software platform for benchmarking corporate debt transactions. With it, professionals can determine if capital markets deal terms are on or off market. Users can upload any given bond or credit document and compare all deal terms to thousands of both public and private transactions. The AI is used to scan corporate debt terms with the notion that it’s the largest graph in the industry.

The role of AI in modern software development

Sounds easy? It’s not. 

Firstly, leaders need to understand that AI is not a magic bullet that’ll resolve all their development challenges. It’s a tool, a teammate that needs proper guidance to be efficient. The AI system must be trained, updated, and monitored, a task for which humans, particularly those with advanced skills, are indispensable.

Secondly, human talent must be upskilled to effectively ‘steer’ the AI. Not every team member needs to be an AI expert, but a baseline understanding of AI’s capabilities, limitations, and ethical considerations is crucial. Upskilling enables team members to use AI tools effectively, recognize when AI’s output needs human intervention, and create better AI training models.

Lastly, it’s crucial to build a culture that celebrates collaboration and values different skill sets. Human members should feel that AI is an ally, not a threat to their jobs. Conversely, AI should be treated with the respect accorded to any team member, with its input valued and utilized effectively.

As Janel Garvin, the CEO of Evans Data, once said:

The fear of obsolescence due to AI, was also more threatening than becoming old without a pension, being stifled at work by bad management, or by seeing their skills and tools become irrelevant.

As we explained in our internal interview with our developers, it’s skills that matters. They can’t be overshadowed with over-reliance but it can be paired with tools that optimize performance.

Benefits of using AI in software development

There are measurable benefits of using AI on a daily basis. They are:

  • Faster development. People are lazy sometimes. No, it’s actually a good thing. Laziness and the need to constantly improve our lives bring us to automation of time-ingesting responsibilities like debugging and code generation.
  • Improved code quality. AI tools aid developers in writing code by way of automatically spotting and correcting mistakes and bugs.
  • More efficient resource allocation. Software developers can optimize the usage of CPU and network bandwidth. With AI, they can cut expenses and enhance the overall performance of the app. For instance, Kubernetes is an AI-pushed platform that can mechanically allocate sources in keeping with the application’s current demand. 
  • Data–driven decision making. AI techniques like machine learning enable product managers, product owners, and developers themselves to make decisions based on AI-powered recommendation systems. It’s also beneficial for customers. When the product is ready and on the market, recommendation systems used in e-commerce can suggest products based on user preferences and browsing history. 
  • Predictive maintenance. Integrating AI into the product creation process can be a price and time-saving method by figuring out problems earlier than they cause downtime.
  • Improved user experience. AI enhances user experience through personalizing programs in step with consumer behavior and preferences. Fintech companies can leverage it by suggesting highly personalized suggestions, like enhancement of the basic insurance plan, for example. The one that takes into account the current financial situation of the client. Not to mention companies like Revolut, which enhance its portfolio and services, based on market and especially customer data evaluation. Intelligent recommendations and personalization are a must.

The direction for the future

According to IBM’s Global AI Adoption Index, 35% of businesses across industries use AI, and 75% of top executives believe AI will help their organization grow. These numbers have surely gone up since this newest report. Tools like DeepCode or GitHub Copilot show us that there’s room for constant improvement. Even when that improvement is digital, not human-based.

The human-AI centaur team pivots around collaboration rather than substitution. It’s not about AI outsmarting humans or humans wrestling control from AI; instead, it’s about each party recognizing and complementing the other’s strengths and weaknesses.

Humans are unbeatable when it comes to creativity, strategic thinking, and decision-making under uncertainty. Meanwhile, AI shines with its computational capabilities, rapid data processing, and pattern recognition. In software development, this means combining the human talent for understanding high-level abstract concepts and their problem-solving abilities with AI’s strength in executing repetitive tasks, analyzing large data sets, and learning from experience.

A programmer-AI centaur team could, for example, tackle complex development problems. The human partner understands the broader scope of the project and makes strategic decisions, while the AI partner handles monotonous tasks, like code generation and debugging, significantly reducing time and effort.