Spectro Cloud completed a $75 million Series C funding round led by Growth Equity at Goldman Sachs Alternatives with participation from existing Spectro Cloud investors.
Through 2027, generative AI (GenAI) will spawn new roles in software engineering and operations, requiring 80% of the engineering workforce to upskill, according to Gartner, Inc.
"Bold claims on the ability of AI have led to speculation that AI could reduce demand for human engineers or even supplant them entirely," said Philip Walsh, Sr Principal Analyst at Gartner. "While AI will transform the future role of software engineers, human expertise and creativity will always be essential to delivering complex, innovative software."
Gartner analysts expect AI will impact the software engineering role in three ways:
Short term: AI will operate within boundaries
AI tools will generate modest productivity increases by augmenting existing developer work patterns and tasks. The productivity benefits of AI will be most significant for senior developers in organizations with mature engineering practices.
Medium term: Emergence of AI agents will push boundaries
AI agents will transform developer work patterns by enabling developers to fully automate and offload more tasks. This will mark the emergence of AI-native software engineering when most code will be AI-generated rather than human-authored.
"In the AI-native era, software engineers will adopt an 'AI-first' mindset, where they primarily focus on steering AI agents toward the most relevant context and constraints for a given task," said Walsh.
This will make natural-language prompt engineering and retrieval-augmented generation (RAG) skills essential for software engineers.
Long term: Advances in AI will break boundaries and mark the rise of AI engineering
While AI will make engineering more efficient, organizations will need even more skilled software engineers to meet the rapidly increasing demand for AI-empowered software.
"Building AI-empowered software will demand a new breed of software professional, the AI engineer," said Walsh. "The AI engineer possesses a unique combination of skills in software engineering, data science and AI/machine learning (ML), skills that are sought after."
According to a Gartner survey conducted in the fourth quarter of 2023 among 300 US and UK organizations, 56% of software engineering leaders rated AI/machine learning (ML) engineer as the most in-demand role for 2024, and they rated applying AI/ML to applications as the biggest skills gap.
To support AI engineers, organizations will need to invest in AI developer platforms. AI developer platforms will help organizations build AI capabilities more efficiently and integrate AI into enterprise solutions at scale. "This investment will require organizations to upskill data engineering and platform engineering teams to adopt tools and processes that drive continuous integration and development for AI artifacts," Walsh concluded.
Industry News
The Cloud Native Computing Foundation® (CNCF®), which builds sustainable ecosystems for cloud native software, has announced significant momentum around cloud native training and certifications with the addition of three new project-centric certifications and a series of new Platform Engineering-specific certifications:
Red Hat announced the latest version of Red Hat OpenShift AI, its artificial intelligence (AI) and machine learning (ML) platform built on Red Hat OpenShift that enables enterprises to create and deliver AI-enabled applications at scale across the hybrid cloud.
Salesforce announced agentic lifecycle management tools to automate Agentforce testing, prototype agents in secure Sandbox environments, and transparently manage usage at scale.
OpenText™ unveiled Cloud Editions (CE) 24.4, presenting a suite of transformative advancements in Business Cloud, AI, and Technology to empower the future of AI-driven knowledge work.
Red Hat announced new capabilities and enhancements for Red Hat Developer Hub, Red Hat’s enterprise-grade developer portal based on the Backstage project.
Pegasystems announced the availability of new AI-driven legacy discovery capabilities in Pega GenAI Blueprint™ to accelerate the daunting task of modernizing legacy systems that hold organizations back.
Tricentis launched enhanced cloud capabilities for its flagship solution, Tricentis Tosca, bringing enterprise-ready end-to-end test automation to the cloud.
Rafay Systems announced new platform advancements that help enterprises and GPU cloud providers deliver developer-friendly consumption workflows for GPU infrastructure.
Apiiro introduced Code-to-Runtime, a new capability using Apiiro’s deep code analysis (DCA) technology to map software architecture and trace all types of software components including APIs, open source software (OSS), and containers to code owners while enriching it with business impact.
Zesty announced the launch of Kompass, its automated Kubernetes optimization platform.
MacStadium announced the launch of Orka Engine, the latest addition to its Orka product line.
Elastic announced its AI ecosystem to help enterprise developers accelerate building and deploying their Retrieval Augmented Generation (RAG) applications.
Red Hat introduced new capabilities and enhancements for Red Hat OpenShift, a hybrid cloud application platform powered by Kubernetes, as well as the technology preview of Red Hat OpenShift Lightspeed.
Traefik Labs announced API Sandbox as a Service to streamline and accelerate mock API development, and Traefik Proxy v3.2.