Amazon Web Services (AWS) announced the general availability of Amazon Q, a generative artificial intelligence (AI)-powered assistant for accelerating software development and leveraging companies’ internal data.
By 2025, more than half of all software engineering leader role descriptions will explicitly require oversight of generative artificial intelligence (AI), according to Gartner, Inc.
"Outside of generative AI's impact on technology implementation, it also changes the managerial responsibilities of software engineering leaders," said Haritha Khandabattu, Senior Director Analyst at Gartner. "This includes those related to team management, talent management and code of ethics. Software engineering leaders will find themselves at a significant disadvantage if they do not recognize and adapt to these changes — facing the risk of being replaced by those who embrace this disruptive technology."
Generative AI Requires Software Engineering Leaders to Focus on Their Team's Value
When piloting generative AI, software engineering leaders must demonstrate the business value of using generative AI to augment their teams. This will help software engineering leaders build a compelling business case for ongoing investment in their teams.
Software engineering leaders must also be transparent with their teams and focus conversations on how AI technology will enhance developer productivity, rather than focusing on how it will replace staff.
"Generative AI will not replace developers in the near future," said Khandabattu. "While it has the ability to automate certain aspects of software engineering, it cannot replicate the creativity, critical thinking and problem-solving abilities that humans possess. Leaders should reinforce the value of their teams by demonstrating how generative AI is a force multiplier that can enhance efficiency."
Generative AI Transforms How Software Engineering Leaders Recruit and Manage Talent
Generative AI applications can speed up recruitment and hiring tasks, such as performing a job analysis and transcribing interview summaries. For example, software engineering leaders can enter a prompt requesting keywords or key phrases related to skills or experience for platform engineering.
Software engineering leaders can also invest in generative AI to allocate more time to focus on the people-centric aspects of their role. Investing in generative AI technologies will allow software engineering leaders to continuously upskill engineers and cultivate an adaptable workforce.
"In addition to recruitment, skill management and development lie at the core of leaders' responsibilities," said Khandabattu. "AI-enabled skills management, a dynamic skills approach that helps in supporting talent and work processes, will help software engineering leaders rethink roles by identifying skills that can be combined to create new positions and eliminate redundances."
Generative AI Introduces Ethical Concerns That Require New Policies
"The use of foundational AI models can introduce risks such as hallucinations, the generation of false yet plausible-seeming content, and bias," said Khandabattu. "Software engineering leaders need to be cautious when using this technology."
Software engineering leaders must work with, or form, an AI ethics committee to create policy guidelines that help teams responsibly use generative AI tools for design and development. Software engineering leaders play a key role in identifying and helping to mitigate the ethical risks of any generative AI products that are developed in-house or purchased from third-party vendors.
"Refrain from using generative AI to replace tasks that require human judgement and critical thinking," said Khandabattu. "Constantly evaluate use cases where generative AI can add maximum value in day-to-day activities."
Industry News
Red Hat announced the general availability of Red Hat Enterprise Linux 9.4, the latest version of the enterprise Linux platform.
ActiveState unveiled Get Current, Stay Current (GCSC) – a continuous code refactoring service that deals with breaking changes so enterprises can stay current with the pace of open source.
Lineaje released Open-Source Manager (OSM), a solution to bring transparency to open-source software components in applications and proactively manage and mitigate associated risks.
Synopsys announced the availability of Polaris Assist, an AI-powered application security assistant on the Synopsys Polaris Software Integrity Platform®.
Backslash Security announced the findings of its GPT-4 developer simulation exercise, designed and conducted by the Backslash Research Team, to identify security issues associated with LLM-generated code. The Backslash platform offers several core capabilities that address growing security concerns around AI-generated code, including open source code reachability analysis and phantom package visibility capabilities.
Azul announced that Azul Intelligence Cloud, Azul’s cloud analytics solution -- which provides actionable intelligence from production Java runtime data to dramatically boost developer productivity -- now supports Oracle JDK and any OpenJDK-based JVM (Java Virtual Machine) from any vendor or distribution.
F5 announced new security offerings: F5 Distributed Cloud Services Web Application Scanning, BIG-IP Next Web Application Firewall (WAF), and NGINX App Protect for open source deployments.
Code Intelligence announced a new feature to CI Sense, a scalable fuzzing platform for continuous testing.
WSO2 is adding new capabilities for WSO2 API Manager, WSO2 API Platform for Kubernetes (WSO2 APK), and WSO2 Micro Integrator.
OpenText™ announced a solution to long-standing open source intake challenges, OpenText Debricked Open Source Select.
ThreatX has extended its Runtime API and Application Protection (RAAP) offering to provide always-active API security from development to runtime, spanning vulnerability detection at Dev phase to protection at SecOps phase of the software lifecycle.
Canonical announced the release of Ubuntu 24.04 LTS, codenamed “Noble Numbat.”
JFrog announced a new machine learning (ML) lifecycle integration between JFrog Artifactory and MLflow, an open source software platform originally developed by Databricks.
Copado announced the general availability of Test Copilot, the AI-powered test creation assistant.