Alexey Glukhov from Payrov on the future of software development and the use of new technologies

We had the pleasure of speaking with Alexey Glukhov, Co-Founder and Product Owner of UK FinTech company Payrow. In this insightful interview, Alexey delves into the drivers of the transformation in software development, the sustainability of these changes, and the significant impact on market dynamics and product development.

The excitement around LLM, no-code and low-code technologies is palpable, especially in the context of their potential to transform software development for startups and Minimum Viable Products (MVP). What do you think about this trend?

We are on the cusp of a huge growth in software development. Traditionally, the high costs associated with software development have been largely driven by the high salaries that skilled software engineers command. With the advent of LLMs, no-code and low-code technologies, these barriers are being removed, making software development more accessible and affordable for startups and MVPs.

How do large language models (LLMs) affect software development today? What potential effects could this change have on software pricing and market dynamics?

LLMs have attracted considerable attention for their ability to generate code with surprising proficiency. They are extremely good at writing code, although not as polished or efficient as that produced by experienced programmers. You wouldn’t rely on LLMs to create a custom, enterprise-class software solution just yet. However, LLMs do allow people with limited technical backgrounds to autonomously create basic, functional pieces of code. This represents a departure from the traditional belief that software development is the preserve of highly skilled programmers. This capability could significantly change the dynamics of software costs itself.

Consumers will only pay for something they can’t build themselves. This democratization of coding has the potential to transform software development by allowing a broader audience to innovate and solve problems with code. This shift could lead to a deflationary effect on software prices, especially for general-purpose applications that face competition from user-generated alternatives. However, sectors that require technical expertise or act as critical infrastructure (such as databases or systems of record) may remain relatively insulated from these market forces.

Could you explain what implications this has for MVP and market dynamics?

The impact of LLMs on software development is particularly evident in the creation of MVPs. In terms of the broader implications, I think that while LLMs may not spell the end of software itself, they are changing the expectations for Minimal Viable Products (MVPs). As non-technical users gain the ability to develop basic software solutions themselves, there may be a corresponding decline in demand for off-the-shelf applications. Consumers are increasingly willing to invest in specialized software that offers unique functionality beyond what they can create themselves.

In addition, there may be opportunities to build platforms on which this new LLM-based code will be written, perhaps integrating with systems of record or appearing as AI agent platforms that help users coordinate tasks in existing systems. In the case of an MVP, I think this is acceptable for quick assembly, provided you proceed with caution and have a solid grasp of the real data.

How do no-code and low-code platforms contribute to this transformation?

In parallel with the growth of LLM, the rise of no-code and low-code platforms is further accelerating the democratization of software development. They enable business users and citizen developers to create functional applications without deep coding knowledge, accelerating time to market and supporting innovation in organizations.

However, no-code platforms can be risky, as there are potential loopholes and code review issues. For example, there is a concern that tools like ChatGPT may produce worse results.

A more promising approach is to use AI to analyze large data sets, construct models based on that analysis, and generate potential alerts. Additionally, using AI to develop predictive models and combat fraud holds great promise.

What are your thoughts on the future integration of LLM with no-code and low-code solutions? Can AI completely replace low-code development in the future?

Looking to the future, I envision a convergence where LLM-generated code integrates seamlessly with no-code and low-code platforms. There is huge potential in developing AI agent platforms that orchestrate LLM-generated code across multiple operational frameworks. Such platforms could increase organizational agility, enabling companies to leverage advanced capabilities without extensive technical investment.

While low-code has been a catalyst for accelerating software development, AI will further accelerate that acceleration. While some applications may eventually be developed entirely by AI without human involvement or low-code tools, that does not mean that all software development will render low-code platforms obsolete. Instead, we may see the emergence of a new generation of AI-assisted low-code platforms that will dominate the creation, debugging, and maintenance of complex, customized, and demanding applications.

Do new technologies have application in the financial sector?

They can play a significant role in transforming the world of finance and payments. Low-code tools and applications often provide a visual, sometimes drag-and-drop interface, enabling software development without extensive hand-coding. The potential for finance professionals to quickly implement new systems to capture new revenue opportunities and quickly adapt to changing regulations is enormous.

The Icon Solutions report, which surveyed senior executives from tier-one banks in Europe and North America, highlights the urgent need for change in the payment processing sector. A significant potential loss of revenue is attributed to the inability to quickly meet product demand. The main culprits for this problem are the shortage of developer capacity and other resource constraints that continue to hinder progress for ambitious organizations.

The report also indicates that 55% of first-tier banks favor developing their own payment processing software. This preference stems from a desire to maintain project control and a belief that reliable off-the-shelf solutions are rare.

What are the risks and challenges associated with new technologies?

Custom coded apps often have security holes like session management issues and input validation errors, making them difficult to secure. Effective security management requires careful planning, but many startups fail due to poor strategies. I think many users of low-code/no-code (LCNC) platforms rely on these platforms for security features due to a lack of in-house security experts.

I believe that compliance-driven industries, such as financial services and healthcare, require the highest level of security for their applications.

As applications become more integrated with other systems, IT involvement becomes necessary for modification, integration, and performance testing. This can lead to a loss of user control over applications and increased IT workloads. Establishing guidelines for the use of low-code and no-code applications can help manage these issues by establishing clear boundaries and requirements for IT involvement in more complex integrations.

How should businesses cope with these technological changes?

In summary, the synergy between LLM, no-code, and low-code platforms undoubtedly represents a paradigm shift in software development. Whether this shift will be beneficial or not remains to be seen. As these technologies evolve, companies must navigate a landscape of uncertainty, balancing agility and innovation with caution. Historically, disruptive technologies have lowered cost barriers and catalyzed transformational change across industries, but not without their own set of challenges. The future of software development will likely be shaped by how effectively companies can integrate and leverage these innovations to drive growth and competitiveness while mitigating potential risks.

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