Generative AI. Observability. Developer platforms. Data management. These are the issues that our industry will face with heightened urgency in 2024. 

SD Times reached out to experts from across the spectrum of software development to find out what they think the new year will bring. Here are some of their thoughts.

Devavrat Shah, co-CEO and founder, Ikigai Labs and an MIT AI professor

LGMs become the next household gen AI tech in the enterprise. Today, nearly every organization is experimenting with LLMs in some way. Next year, another major AI technology will emerge alongside LLMs: Large Graphical Models (LGMs). An LGM is a probabilistic model that uses a graph to represent the conditional dependence structure between a set of random variables. LGMs are probabilistic in nature, aiming to capture the entire joint distribution between all variables of interest. They are particularly suitable for modeling tabular data, such as data found in spreadsheets or tables. LGMs are useful for analyzing time series data. By analyzing time series data through the novel lens of tabular data, LGMs are able to forecast critical business trends, such as sales, inventory levels and supply chain performance. These insights help guide enterprises to make better decisions.

Donald Fischer, CEO and co-founder, and Luis Villa, co-founder and general counsel, Tidelift 

Open source contributors fed up with corporate interests exploiting open source start fighting back. After a period in which the principles underlying the open source movement took a back seat, open source contributors will rediscover open source’s roots in the free software movement and start fighting back against commercially controlled projects bending and breaking open source principles in search of profits. And, already overwhelmed open source maintainers “cry uncle” as well intended, AI-generated pull requests create a snowball of even more noise for them to deal with. Predictably, the end result is even more frustrated maintainers, many of whom will quit their maintenance work altogether, leading to more security risk for organizations

Kaley Boggs, Data Practice Lead, Andela

Influx of GenAI products drive GenAI literacy and upskilling. GenAI product releases will skyrocket in 2024, creating the need for organizations to create a strategy to develop GenAI literacy, training and upskilling, so the tools are leveraged effectively. In order to utilize the AI capabilities, individuals and organizations will need to understand the functionality and operations of GenAI tools. GenAI is only as good as the human intelligence driving it. As organizations adopt tools, individuals who upskill on GenAI will be in high demand to help democratize and scale the use of the tools. GenAI can reduce rote tasks. Highly skilled workers will be drawn to places that use GenAI to free them of such work.

Niamh O’Brien, Senior Manager of Solution Architecture at Fivetran 

Chief Data Officers (or any data leaders for that matter) will need to be change management specialists first and data specialists second to be successful in 2024. Creating a data culture is the exact opposite of the “Build it and they will come” approach from Field of Dreams; CDOs have found themselves too often in a field alone with only their own dreams. You have to bring the “data dream” to all areas of the organization to make a data-driven culture a reality; generative AI is the most tangible and relatable vessel that CDOs have ever had to do just that.” 

Sandhya Sridharan, Head of Engineers’ Platform and Experience, JPMorgan Chase

The rapid evolution of centralized platforms and integration of AI/ML in every stage of the software development life cycle—from ideation and planning to production deployment management—will revolutionize software engineering. These will streamline and accelerate every aspect of an engineer’s workflow – reducing cognitive overload, enabling creation of reusable code, simplifying code searches, faster troubleshooting, and even generating test code—so they can focus on the more creative aspects of software design and bring solutions to market faster. This new relationship between engineer’s platform and AI/ML will pave the way for an era of software development where intelligent automation and human creativity synergize to deliver exceptional products and services at unprecedented scale to customers and users worldwide.

Nima Negahban, CEO and Cofounder, Kinetica

English will replace SQL as the lingua-franca of business analysts. We can anticipate a significant mainstream adoption of language-to-SQL technology, following successful efforts to address its accuracy, performance, and security concerns. Moreover, LLMs for language-to-SQL will move in-database to protect sensitive data when utilizing these LLMs, addressing one of the primary concerns surrounding data privacy and security. The maturation of language-to-SQL technology will open doors to a broader audience, democratizing access to data and database management tools, and furthering the integration of natural language processing into everyday data-related tasks.”

Bruce Fenton, PE partner, Troutman Pepper law firm

Equity investments will have a heightened emphasis on quality. Remember that coming out of the pandemic were two of the busiest years on record for the industry in 2021-22, so while there’s been a pronounced drop-off this year, it hasn’t been so bad from a historical perspective. You’ll notice that it’s mostly A-grade or B+ assets being sold, even though there may be a lot of investment opportunity beneath those grades. Sponsors and corporate players will continue to come in from the sidelines in the new year. There is plenty of dry powder – many billions of dollars of pent-up capital to deploy.  Experienced investors will remember how to do deals in a high-interest environment, including putting more equity into their portfolios, given the heavy cost of borrowed funds. 

Jason Beres, Sr. VP of Developer Tools, Infragistics

Low-Code/No-Code Tools Will Dominate Software Development in 2024. In 2024, low-code/no-code tools will dominate software development as they bring the power of app development to users across the business. The rise of “citizen developers” has proven that as we move toward a no-code future, people without coding experience are changing the working world. As tech companies adopt low-code/no-code tools, they’ll save time and money, rather than falling behind early adopters.

Guillaume Moigneu, VP Product, Growth and Monetization, at

Comprehensive observability at every layer. Companies will continue to integrate Application Performance Management (APM) solutions to achieve full-stack observability, enabling a panoramic view of their systems’ health and performance. APM will provide more granularity in analytics such that technical teams will be able to not only detect but predict system anomalies. This will enable preemptive measures that drastically reduce downtime and empower developers to continuously deliver better quality releases.