Platform Engineering: Enhancing Cloud-Native and AI Capabilities

Michael Mueller

September 17, 2024

Platform engineering Ai Gen ai

The technological landscape is ever-evolving, presenting organisations with both unprecedented opportunities and complex challenges. From the rise of the internet to the shifts toward cloud computing, mobile technologies, and DevOps practices, each leap has demanded swift and strategic adaptation. Now, Generative AI (GenAI) emerges as the next transformative force, poised to revolutionise data handling, automation, and user experiences. However, integrating GenAI isn’t merely about adopting a new tool—it’s about reshaping workflows, infrastructure, and organisational culture. This is where the establishment of a dedicated platform team becomes not just valuable but essential.

The Familiar Pattern of Technological Adoption

When new technologies gets adopted at organisations they often follow this or a similar sequence:

Initial Exploration: A pioneering team experiments with a manageable use case to evaluate the technology’s potential.
Pilot and MVP Development: Acting as change agents, they tailor the technology to fit the existing architecture, often requiring custom integrations.
Abstraction and Scaling: Abstraction layers are created to simplify adoption, leading to the development of internal platforms or frameworks.
Championing and Education: Enthusiastic team members become advocates, sharing knowledge and best practices organisation-wide.
Standardization and Reuse: Patterns emerge, resulting in standardised processes that streamline further adoption.
Governance and Guardrails: As usage scales, governance mechanisms are implemented to ensure compliance, security, and optimal performance.

The Critical Role of Platform Teams

Platform teams are specialised units that build and maintain the foundational services and tools upon which other teams rely. In the context of GenAI, platform teams are instrumental in:

Providing Reusable Components: They develop and manage shared infrastructures, such as model hosting environments, vector databases, and API gateways.
Enabling Self-Service: By creating user-friendly platforms, they empower development teams to integrate GenAI capabilities without the underlying complexities.
Ensuring Compliance and Governance: They implement guardrails that ensure all GenAI applications align with organisational policies and regulatory mandates.
Facilitating Knowledge Sharing: Acting as centres of excellence, they promote best practices, offer training, and cultivate a culture of continuous learning.

Why GenAI Integration Demands a Platform Team

Integrating GenAI is a multifaceted endeavour that extends beyond simple implementation. Here’s why a platform team is indispensable:

Navigating Complex Infrastructure Requirements

GenAI applications are built from different components:

Large Language Models (LLMs): Hosting and managing advanced models like GPT-4, Claude or any other require substantial computational resources and specialised expertise.
Vector Databases: Efficient data retrieval in GenAI involves vector databases that index unstructured data.
Frameworks and APIs: Standardising and maintaining new frameworks and APIs is crucial for seamless integration into existing applications.

A platform team centralises these elements, ensuring a scalable and reliable infrastructure that serves the entire organisation.

Keeping Pace with a Rapidly Evolving Landscape

The GenAI field advances at an extraordinary pace, like we have seen with the Cloud Native space in the past:

Emerging Models and Tools: New developments can quickly overwhelm individual teams attempting to stay updated.
Evolving Best Practices: Yesterday’s solutions may not meet today’s standards.

Platform teams¹ stay at the forefront, updating tools and practices accordingly. By centralising expertise, platform teams remove the burden on individual teams, allowing them to focus on innovation rather than maintenance.

3. Addressing Governance and Compliance Challenges

GenAI introduces unique considerations:

Data Privacy: Stringent controls are necessary to prevent the inadvertent exposure or misuse of sensitive data.
Ethical Considerations: Mitigating biases, preventing inappropriate content generation, and adhering to regulations like the EU’s AI Act require vigilant oversight.
Licensing and Intellectual Property: Navigating the complexities of model licences and ensuring compliance is essential.

Platform teams implement comprehensive policies and monitoring systems, effectively managing risks across the organisation.

Enhancing Developer Enablement and Support

Adopting GenAI shifts the developer paradigm:

Overcoming Resistance: Developers may feel threatened by AI or daunted by its complexity.
Providing Training and Resources: Educational materials, workshops, and sandbox environments help developers build confidence.
Standardising Tools: Offering consistent frameworks and development environments reduces the learning curve and fosters productivity.

Platform teams are pivotal in empowering developers to embrace GenAI, facilitating a smoother transition and fostering innovation.

Strategic Steps for Successful GenAI Integration

To get the full potential of GenAI, organisations should consider the following steps:

Establish the Platform Team Early As soon as initial use cases demonstrate promise, forming a platform team ensures that the necessary infrastructure and policies are developed proactively.
Develop Scalable Infrastructure Focus on creating reusable components that can serve multiple teams. This includes model hosting services, standardised APIs, and robust monitoring tools.
Implement Robust Governance Frameworks Define clear policies for data usage, model selection, and ethical considerations. Integrate tools for continuous compliance monitoring and enforcement.
Enable and Educate Development Teams Provide comprehensive training sessions, detailed documentation, and ongoing support. Foster an internal community dedicated to GenAI best practices.
Foster Cross-Functional Collaboration Integrate the GenAI platform team with existing cloud, security, data, and developer experience teams. This synergy leverages shared knowledge and accelerates innovation.
Monitor Progress and Iterate Regularly assess adoption rates, performance metrics, and compliance adherence. Be prepared to refine strategies in response to feedback and technological advancements.

Conclusion

Integrating GenAI into your organisation is not just a technological upgrade—it’s a strategic transformation that reshapes infrastructure, processes, and people. Platform teams are the core of this transformation, providing the structural support, tools, and guidance necessary for successful adoption.

By centralising expertise and resources, platform teams eliminate redundant efforts, ensure compliance, and facilitate the rapid scaling of GenAI capabilities. They help overcome initial adoption roadblocks, mitigate risks, and lay the groundwork for sustained innovation.

In a world where technological advancement happens daily, establishing a platform team isn’t just a strategic advantage—it’s a necessity for organisations committed to staying at the forefront of their industries. Embracing GenAI with a dedicated platform team positions your organisation to harness its full potential, driving efficiency, fostering innovation, and securing a competitive edge in the market.

Ready to take the next step in your GenAI journey? Our team of experts is here to help you navigate the complexities of integration and set up a platform team tailored to your organisation’s needs. Contact us today to unlock the full potential of Generative AI.