2024

Software Development Trends Report

It’s no secret that we are living in the AI boom. Bloomberg Intelligence estimates that the global market for generative AI alone will grow to “$1.3 trillion over the next 10 years, up from $40 billion in 2022.” But without proper oversight, generative AI can carry risks like security issues and biased or inaccurate outputs.
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To reduce the risks associated with large language models (LLMs), companies like OpenAI and Anthropic are implementing “red teaming.” 

Red teaming, defined in The White House’s Executive Order on Artificial Intelligence, is “a structured testing effort to find flaws and vulnerabilities in an AI system.” Internal red teaming isn’t new. Historically, engineering teams used red teaming to “hack” systems to find security vulnerabilities. Organizations are applying the same principles to AI, but instead of “hacking,” a red team purposefully tests the boundaries of restrictions placed on the LLM models.

Google has had an internal Red Team for over a decade, which recently expanded to include AI testing—and Microsoft established an AI Red Team in 2018. But some organizations, like OpenAI, are taking this idea a step further, recruiting external partners from their own community networks. In 2023, OpenAI created a formal Red Teaming Network, a group of external experts focused on testing their AI models to reveal biases or document when models ignore safety filters.

Amid ongoing conversations around AI ethics and governance, red teaming is evidence that some of the most innovative companies are relying on humans to act as a checkpoint to catch flaws in AI systems.

Automated testing is growing in popularity, as engineering teams forgo manual testing in favor of more scalable tools and processes. Generative AI (GenAI) allows engineering teams to create and even automate tests using natural language, with limited human intervention.

This is creating a mindset shift within engineering teams. Artificial intelligence is making it cheaper and faster to bring quality applications to market and raising the bar for internal teams. Testing, which was often overlooked, is now baked into the entire development process—and working towards 100% test coverage is becoming a key priority for teams to ship faster and with greater confidence.

These changes affect QA engineer and software engineering roles. QA teams will get more nimble and more strategic. To provide the right inputs into GenAI tools, QA engineers will need to have a deeper understanding of the product and the customer. Software engineers, on the other hand, will need to get more familiar with writing tests as they write features. Testing becomes a collaborative process between both teams.

Automation gives engineers more time to focus on adding value to the product and less time on catching bugs—ultimately leading to a more scalable development process.

Good design should be a priority for every product team, but gaps often emerge during the handoff process between UX designers and engineers. Because these teams don’t use the same terms, processes, or tools, design intent is often “lost in translation.”

To bridge this gap, new tools are merging design and engineering workflows, generating variables, code, and documentation from design artifacts. This creates common ground for designers and engineers to align and execute on a shared vision.

For example, Figma’s Dev Mode and Widgetbook act as translators, revealing the code behind every icon and style. This Figma Styles Plugin, launched by the Very Good Ventures team, even takes existing Figma files and exports them as Dart code, creating an error-proof handoff between design and development teams.

Design and engineering are no longer distinct silos and teams. These new tools acknowledge this reality, enabling more code-driven design activities and artifacts that speed up development and launch cycles.

Key players like Apple and Meta continue to invest in spatial experiences, with Apple coining the term “spatial computing” and Meta creating an entire brand around the metaverse. Engineers are building spatial-focused applications for a new augmented world powered by headsets like Apple’s Vision Pro and Meta’s Quest series.

With the launch of their Vision Pro this year, Apple ushered in a new wave of immersive 3D experiences, placing content directly in people’s real-life environments. Creating applications for these experiences requires a shift in design thinking. Web and mobile designers, especially those focused on multi-platform experiences, will need to create and learn a new set of design standards.

Both Apple and Meta are building educational materials to guide designers and engineers into this new era. Meta created a 3D prototyping program containing toolkits and modules to help designers turn “concepts and interactions that are unique to spatial design into tangible virtual objects.”

Meanwhile, Apple launched a series of educational materials around the principles of spatial design, highlighting the importance of ergonomics and comfort when placing elements in people’s field of view. It also recommends designing around “key moments”—what Apple defines as “an experience that isn’t bound by a screen.”

These products aren’t widely adopted (yet), but that doesn’t mean you should ignore them. Designers and engineers that invest time in learning these technologies—and design principles—will have a leg-up when they hit the mainstream.

One of the biggest barriers to building a new application is developer resourcing. That’s why many entrepreneurs are turning to low-code developer tools to validate their ideas before investing in engineering talent.

Tools like FlutterFlow or Bubble offer an entry point for non-technical users to build applications with minimal engineering intervention. In their current state, these tools are a useful way to test a concept or expedite early product launches.

Many engineers are hesitant to use low-code tools to build applications, particularly due to concerns around long-term scalability. Although these tools might not be ready to support high-visibility use cases, they serve as an option for functional prototyping and an alternative to offshore outsourcing.

In the face of developer talent shortages, these tools enable founders and citizen developers—people embedded in the business—to innovate faster and cheaper, bypassing some of the bottlenecks that exist in the traditional development cycle.

There are a lot of reasons that companies are adopting a multi-platform strategy, like the ability to build applications across platforms with one codebase. But one of the biggest, and least discussed outcomes is a better team culture.

Flutter and React Native, the most popular cross-platform frameworks, continue to gain more traction. In fact, Flutter’s ecosystem “grew 26% in 2023 from 38,000 packages in January to 48,000 at the end of December.”

When teams adopt these frameworks, they’re either building something new or re-platforming an existing application. This technology transformation is a catalyst for leaders to take a hard look at their internal processes, including how they organize their teams.

A multi-platform strategy allows leaders to align engineers to critical priorities like new feature sets instead of native applications. Teams can evaluate the entire user experience across devices instead of focusing on individual platforms. “All of a sudden you’re not an Android or iOS developer. You’re a product developer,” says Jorge Coca, Head of Engineering at Very Good Ventures.

The result? Less silos means teams can build new applications faster and cut ongoing maintenance costs—creating business impact in less time. This also increases team morale and innovation.

These programs lead to an additional benefit—retention. In a period where employees prioritize growth and learning opportunities in their career choices, “organizations with a skills-based approach are 98 percent more likely to retain high performers,” according to Deloitte’s Human Capital Trends Report.

Carving out time for employees to learn new skills might feel like a big investment in the beginning, but leaders see long-term benefits from a workforce that deeply understands new technologies and can innovate faster than their competitors.