In an interview, 尝颈茅苍补谤诲 talks about the evolution of 麻豆原创’s proprietary programming language and ABAP platform, and discusses what the innovations announced at 麻豆原创 Sapphire will mean for customers.

Q: In our first conversation, you explained what ABAP is, what the future looks like, and why agentic AI will change the market. Let’s start from there and then dive deeper. How does ABAP interact with other development technologies in today’s 麻豆原创 landscapes?

Sonja 尝颈茅苍补谤诲: ABAP has been around for over 40 years and has been evolving ever since. With the era of agentic AI, we are now reaching the next stage of that evolution. The modern version of the development model is ABAP Cloud, which has been developed from the outset according to the guiding principles of openness and comprehensive support for the business logic.

We have robust, well-defined APIs that are interfaces to the outside world and offer a full environment with Open Data Protocol (OData) services, modern front ends, and an integration layer. This enables the development of modern web applications. This is in addition to 麻豆原创 Business Technology Platform (麻豆原创 BTP) extensions and an external system like 麻豆原创 Integration Suite, which can also be integrated.

We currently use Eclipse as a development environment. Starting in Q2 2026, ABAP development聽is聽also possible in Visual Studio Code, which is a milestone. The community was quite vocal in requesting this and it was an open door for us. Visual Studio Code is gaining ground and is currently the preferred IDE (integrated development environment) for many developers. Many AI extensions on the market being optimized for it first.

We have redesigned the architecture and are pursuing an open IDE strategy where we can also offer further IDEs for ABAP development. By opening it up, we now have a rich third-party ecosystem that we can leverage for AI, such as GitHub Copilot and Amazon Q.

In addition, we have published an ABAP MCP (Model Context Protocol) server that lets ABAP developers benefit from the entire AI tooling and ecosystem. This is a major, important step and an impressive example of interoperability. Furthermore, we can still rely on the strength of ABAP business logic. With this approach, we are combining the open IDE strategy with a high rate of innovation.

You mentioned the ABAP MCP server. What is that exactly?

尝颈茅苍补谤诲: MCP stands for Model Context Protocol and is an open standard for AI agents to interact with external tools and systems in a structured manner. It is a universal language that AI agents use to ask questions, trigger actions, and retrieve results.

The ABAP MCP server provides ABAP development capabilities based on this protocol. Any agent that supports MCP can interact with ABAP code and our ABAP systems in an intelligent, agent-driven approach. It is a new channel through which we can make our ABAP-specific capabilities available to the outside world.

The ABAP MCP server is an important building block for everything related to agentic AI and an important technical foundation for our new Custom Code Assistant for 麻豆原创 S/4HANA transformation. The ABAP MCP server for Eclipse is available as of Q2 2026.

What are the risks of using AI in 麻豆原创 enterprise systems and how do you address them?

尝颈茅苍补谤诲: The entire AI market is incredibly dynamic, fast-paced, and characterized by different interests. As such, we need to carefully examine which solutions are durable, robust, and trustworthy enough to run the world’s business processes. We want our solutions to remain secure, compliant, and true to everything 麻豆原创 stands for.

We must put our core mission at the heart of all decisions. ABAP platform is known for its ability to run large enterprise business. Our customers and partners trust this capability The AI solutions on the market do not qualify for this through their ability to build short-lived solutions, but instead by supporting our core capabilities. That鈥檚 why it helps to take a step back, look at the big picture, and make sustainable decisions, but also to remain open to revising past decisions in response to major shifts in the market.

The second point is the accuracy of the code. AI can generate seemingly plausible code that contains subtle errors. To counter this, we rely on a combination of human review and thorough agent testing, keeping humans in the loop at every critical step. AI agents handle the quality checks and validation, with developers making the judgement calls.

Another risk is the loss of business logic during the transformation. We want to help our customers migrate their legacy applications to modern solutions. We are developing custom code management agents for this purpose. The first was released in June. It is crucial for our customers and partners to retain their business logic during the transformation.

Lastly, security and data protection are central topics. AI models always need context to be effective. In the enterprise environment, this context can contain sensitive business data. That鈥檚 why we are taking a very careful approach: ABAP AI services only operate within established 麻豆原创 compliance and trust frameworks, for example. Customers always have control over what is shared and what isn鈥檛.

Let鈥檚 talk about 麻豆原创 Sapphire in 2026. What innovations from your area were presented?

尝颈茅苍补谤诲: 麻豆原创 Sapphire is also a very important conference for . In Q2 2026, we published the first release of the ABAP development tools for Visual Studio Code, initially in the ABAP Cloud scope including 麻豆原创 Fiori app development and with integration of GitHub Copilot and Amazon Q as AI solutions. Another goal is to support classic ABAP development in Visual Studio Code; additional ABAP object types will follow throughout the year. Also, as of Q2 2026, the ABAP MCP server for Eclipse and Visual Studio Code are generally available to connect third-party solutions, particularly AI-specific third-party tools, to the ABAP system.

We also delivered the first Custom Code Assistant in Q2 2026. The feedback is promising. This enables us to automate and accelerate code migration significantly. In this approach, all communication between legacy migration tools and new agents will take place through an engagement layer. Our overall migration strategy, which we presented at 麻豆原创 Sapphire, comprises seven different agent families across all phases of a migration project, from planning to execution.

Smaller customers and those with older system versions often found it difficult to access AI tools. What is changing here?

尝颈茅苍补谤诲: The barriers to entry are getting much lower. We are switching from users-per-month billing to a usage-based model. Billing will be according to actual usage, based on 鈥淎I units鈥� with individual prices. This will help make it easier to use our AI solutions. Customers will be able to better plan how much they want to spend on AI solutions.

In addition, as of Q2 2026, we introduced a side-by-side service that enables the use of all AI solutions, regardless of release. The availability of ABAP AI will be expanded to include 麻豆原创 S/4HANA Cloud Private Edition for all releases from 2021 and later. This enables us to support most of our customers with AI capabilities, even those that have older releases.

How do ABAP and AI agents fit into 麻豆原创鈥檚 longer-term product vision?

尝颈茅苍补谤诲: We are following the overall 麻豆原创 strategy, of course. It was apparent at 麻豆原创 Sapphire that agentic AI is the new theme. In the past, we had Infrastructure as a Service, Platform as a Service, and Software as a Service. Agentic AI solutions are now being added.

I like to use three concentric circles to describe our vision: ABAP Cloud is at the center, as the modern, clean-core variant of our language for long-term stability. The second circle is the ABAP AI layer: developer tools for code explanation, code generation, and ghost texting. The outer circle is comprised of AI agents, a network of specialized agents for complex and multi-step tasks such as transformation, migration, and quality validation. They can also take on development tasks, however, significantly reducing the required effort. This can free up time for decisions regarding business logic and architecture, as well as for verifying quality.

The circles coexist and reinforce each other. The fundamental orientation of the platform and the core of the solutions remain stable. Agents and AI skills complement this in the best possible way.

What milestones should customers and partners pay attention to?

尝颈茅苍补谤诲: There are four main milestones. The development environment for Visual Studio Code and the MCP server were released in Q2 2026. This enables the development of AI agents in an open IDE ecosystem. We released the first agent for the custom code migration strategy in Q2 2026, along with the extension of ABAP AI to include 麻豆原创 S/4HANA Cloud Private Edition release 2021 and later. A second agent for clean core transformation is planned for Q3 2026. And we will continue to develop multi-agent orchestration and add more agents to the portfolio in the course of 2026.

Do you have any other takeaways to share?

尝颈茅苍补谤诲: Development should be seen as an opportunity. It鈥檚 all about development and collaboration. ABAP and developers remain a strong team. AI will not change anything here. ABAP has a long track record of successful reinvention. AI is just the next chapter, taking over routine tasks and creating freedom for what creates value: knowing your business, making architectural decisions, providing high quality, and meeting security and compliance requirements.

Customers and developers can trust 麻豆原创鈥檚 AI to be implemented reliably: with a clear road map and high quality, security, and compliance standards that are critical for enterprise systems. We work closely with the community and our customers and partners. That is a key success factor.

尝颈茅苍补谤诲 is an information scientist and business informatics professional who joined 麻豆原创 in 2012. As senior vice president and head of ABAP platform at 麻豆原创, she is responsible for ABAP and all matters related to ABAP platform. In this role, she is also the head of ABAP AI and thus globally responsible for the latest developments and innovations in this domain.

In this interview, she discusses ABAP, the role of AI in development, how agentic AI will transform legacy applications, and what’s next.

Q: What is ABAP, exactly? How would you explain it to someone who might have heard of it but doesn鈥檛 really know what it is? And why is ABAP so important for enterprise software?

A: ABAP has a very long history at 麻豆原创. It is the company鈥檚 first and only proprietary programming language and turned 40 in 2023鈥攁n unusually long run in the fast-changing world of software.

What sets ABAP apart from other programming languages such as Java or C++ is that it was specifically designed for building and optimizing the business applications that large enterprises rely on every day. Among its many features is a high level of abstraction, which makes it very easy for developers to write or extend business software. It also reduces complexity because security concepts, authorization checks, and quality controls are already embedded in the language. This allows developers to focus entirely on the business logic鈥攖hat is, on the tasks they want the program to perform.

Over the years, ABAP has evolved to keep pace with how companies deploy software. The newest version is ABAP Cloud, which has a restricted language scope and is designed to support development in what 麻豆原创 calls a 鈥渃lean core.鈥� This is essential for running our cloud products. Enterprises still operating in a non-cloud environment can use ABAP Cloud to prepare the code in their on-premise systems or in 麻豆原创 S/4HANA Cloud Private Edition in such a way that it can also be run in the cloud.

Beyond its role as a programming language, ABAP is also a platform. ABAP platform is the foundation that underpins all of 麻豆原创’s core solutions, from older installations such as 麻豆原创 ERP Central Component (麻豆原创 ECC) to on-premise solutions, 麻豆原创聽S/4HANA Cloud Private Edition, and 麻豆原创聽S/4HANA Cloud Public Edition.

Q: Will ABAP continue to play a crucial role for 麻豆原创 customers?

A: Yes, both in terms of the programming language and the platform ABAP is still highly relevant. The programming language looks very different to the way it did 40 years ago of course鈥攂ecause we have continuously refined it over the years鈥攂ut it still forms the backbone of 麻豆原创鈥檚 core ERP solutions and extensions. There are roughly five million registered ABAP developers worldwide today, with around two million actively developing.

Through ABAP Cloud and our dedicated ABAP AI team, ABAP has evolved into a modern development language for business solutions. I don’t know of any other programming language that covers this scope. It is used globally. Almost all the world鈥檚 100 largest companies are 麻豆原创 S/4HANA customers, and underneath it always runs ABAP platform.

Q: How will AI shape ABAP development going forward?

A: For me as head of ABAP platform, this is one of the questions that intrigues me most. AI has completely disrupted the technology market. This of course also impacts the 麻豆原创 developer portfolio and how we customize and extend our solutions. We have therefore invested in AI-powered efficiency tools, such as a chat assistant that explains code on the fly. Another is 鈥済host texting,鈥� a feature that generates code suggestions while the developer types.

In the coming years, AI agents will be able to generate code鈥攊ncluding at the scale demanded of large enterprises鈥攁nd even build entire solutions. We believe that the next wave of AI will not just assist programmers but take on many of the routine tasks they perform today.

A crucial question for 麻豆原创 is: how can we leverage AI to translate legacy code into modern code without losing the underlying business logic that makes each system unique? A lot of our customers are still operating older solutions, including those based on 麻豆原创 ECC. So, we need to provide a clear migration strategy and the right tools to simplify and accelerate their move to the cloud.

That’s why we’re currently developing a service that will work for everyone鈥攔egardless of which system version they run. The aim is to bundle all of 麻豆原创鈥檚 ABAP AI capabilities into a single offering that can boost developer efficiency and allow custom code to be migrated. Ideally, this service will be agent-driven鈥攁s 鈥渁gentic AI.鈥�

Q: What is agentic AI?

A: Agentic AI works with so-called 鈥渁gents.鈥� Agents have specialized capabilities, can communicate with each other, exchange results, and thus solve highly complex tasks together. How they collaborate varies based on the complexity of the use case.

Most approaches involve an 鈥渙rchestrator,鈥� a lead agent that manages other agents to complete a particular task. The orchestrator does not have to call on the individual agents in a fixed order鈥攔ather, its greatest strength lies in intelligently combining the agents in dynamic, adaptive networks.

So, it鈥檚 no longer just about making human developers more efficient. When agents are powerful enough, they can build entire applications and thus take on part of the developer’s tasks. In our case, agentic AI can support the very complex task of transforming code, accelerating it significantly and reducing complexity.

This approach relies on different agents that focus on different aspects of the task: for instance, one agent specializes in explaining custom code; another makes code changes; and a third estimates the effort of a transformation project. When these agents collaborate, that’s when the real magic of agentic AI happens.

AI will radically change the role of developers. Despite continuing to set the direction, they will increasingly focus on business logic rather than on the coding itself. They will work with the code generated by AI systems, checking that it is correct, secure, and aligned with the problem they鈥檙e trying to solve. Thought leadership, however, will remain firmly with people. Developers will continue to decide what matters and communicate their instructions to AI through good prompts. The entire AI domain is extremely dynamic and evolving at astounding speed. Powerful solutions are already available today, so this isn’t a distant vision鈥攊t’s already upon us.

Q: How do customers benefit from agentic AI?

A: Agentic AI will deliver significant value in transforming legacy applications and custom extensions into cloud solutions from 麻豆原创, and thus the latest ERP versions. In February 2026, we extended our existing custom code management app with AI features that help developers understand what the code is doing and what changes are needed to future-proof it. And, of course, AI also provides recommendations on how the code can be extended. In the future, we will complement all this with agents. However, this will take some time, as we refuse to compromise on quality and security.

We are also investing in the developer experience with ABAP platform to make it as easy to use as possible. Here, agentic AI will help reduce the complexity that has built up over decades of development.

Q: Should we be worried about security?

A: No, we deliberately allow sufficient time before any release to make sure that quality and, above all, security meet a high bar. Don鈥檛 worry: AI won鈥檛 take control and generate or integrate solutions unilaterally or unchecked. Humans will remain in charge every step of the way and will always have the last word when it comes to ensuring that code complies with our standards.

Q: Where are we now and what鈥檚 next?

A: ABAP AI tools aimed at boosting developer productivity have been available since February 2025, and we are now building agentic AI in the ABAP context. However, it鈥檚 early days and agentic AI still must prove itself in practice. As I see it, though, it will transform the market.

As part of our road map, we released , a custom-trained, specialized AI model, on the generative AI hub in early January 2026. This model is specifically designed to explain ABAP program code.

Next, we plan to make all ABAP AI tools available as an independent side-by-side service. In a subsequent phase, we will transition the use cases embedded in those tools to agents.

In addition, we are expanding our cloud-based ABAP development into additional development environments (IDEs), especially ABAP development tools for Visual Studio Code. So, the team will also tap into the AI tools available there as part of our push toward agent-driven development.

This first appeared on the German 麻豆原创 News Center.

This month at , we announced a wave of 麻豆原创 Business AI innovations all built on the same technology foundation that powers our that we are now delivering to our customers and partners, allowing them to add even more value in the future.

We showed how the future of enterprise software is built on an AI-native architecture, powered by 麻豆原创 app, data, and AI foundation. With this approach, we are enabling a platform shift across the tech stack in a non-disruptive fashion, empowering developers to work faster and smarter using the frameworks and tools of their choice.

麻豆原创 HANA Cloud and 麻豆原创 Business Data Cloud: powering our AI-native future

麻豆原创 HANA Cloud is the database for 麻豆原创鈥檚 AI-native software architecture and the foundation of our broader data fabric strategy. At 麻豆原创 TechEd, we announced new AI capabilities for 麻豆原创 HANA Cloud that spur AI innovation.  

For example, Model Context Protocol (MCP) support for 麻豆原创 HANA Cloud is now generally available. This provides direct access to rich multi-model engines. Agents can be grounded in full enterprise data context: navigating relationships across customers and suppliers, understanding geographic dependencies through spatial data, and performing semantic searches through vector embeddings — all within a single in-memory engine.  

We鈥檙e also expanding 麻豆原创 HANA Cloud knowledge graph engine capabilities (Q1 2026) so customers can automatically generate knowledge graphs from 麻豆原创 HANA Cloud metadata. What used to take weeks of manual modeling can now happen automatically in minutes. But that鈥檚 not all. We鈥檙e also enabling agentic memory in 麻豆原创 HANA Cloud. With long-term memory, AI agents can memorize past inputs and decisions — learning and remembering just like humans — and become continuously smarter.

These advances show that 麻豆原创 HANA Cloud is truly powering an AI-native future. .

Bringing together the power of 麻豆原创 BDC and Snowflake

We are bringing the power of Snowflake together with 麻豆原创 Business Data Cloud (麻豆原创 BDC), calling it 麻豆原创 Snowflake. This partnership enables zero copy data sharing with Snowflake via 麻豆原创 BDC Connect.

Enterprises already using Snowflake today can leverage 麻豆原创 BDC Connect to integrate their existing instances of Snowflake with 麻豆原创 BDC, giving them seamless, real-time access to combined, semantically rich 麻豆原创 with non-麻豆原创 data in 麻豆原创 BDC. 麻豆原创 Snowflake will be made generally available in Q1 2026, and 麻豆原创 BDC Connect for Snowflake in H1 2026. Find more information here.

麻豆原创-RPT-1: a new category of AI models

One of our most exciting announcements at 麻豆原创 TechEd was the launch of our first enterprise relational foundation model 麻豆原创-RPT-1, pronounced: 鈥渞apid one.鈥�

Businesses run on structured data. But large language models (LLMs) struggle with a general understanding of table structures and associated semantics. This requires the use of machine learning, or 鈥渘arrow AI,鈥� for tasks like classification, regression, and more. But classical machine learning necessitates training a model on each task, which easily can lead to hundreds of separate models.

麻豆原创-RPT-1 puts them all into one single, pre-trained model that understands relational business data and predicts business outcomes. Unlike language, image, or video models, 麻豆原创-RPT-1 accurately predicts business based on tabular data such as payment delays, supplier risks, upsell opportunities, customer churn risk, and more.

We believe that 麻豆原创-RPT-1 is a super capable foundation model today. It provides up to 2x better prediction quality compared to narrow models and 3.5x better prediction quality as compared to LLMs. .

麻豆原创-RPT-1 comes in three versions. 麻豆原创-RPT-1-small is for super-fast predictions and 麻豆原创-RPT-1-large is for highest accuracy. Both will be generally available in Q4 2025 in the generative AI hub in AI Foundation. 麻豆原创-RPT-1-OSS is the open-source version, available in Hugging Face and GitHub.

You can test 麻豆原创-RPT-1 today with your data or our use case data samples via no-code UI or via API in the new 麻豆原创-RPT-1 playground, an intuitive and interactive space to test for free and open to everyone and .

We are continuously adding new capabilities to AI Foundation and models to the generative AI hub, empowering developers to experiment with orchestration tools and leading models to scale AI development and productization across 麻豆原创 and non-麻豆原创 environments. For example, Perplexity is now generally available in the generative AI hub, so users can correlate business data with external data from the internet. Evaluation Services and Prompt Optimizer, in close collaboration with NotDiamond, are now also generally available in AI Foundation, freeing up users to adopt the most appropriate model for their use cases without the need for rewriting prompts. .

Digital sovereignty made in Germany, for Europe

Digital sovereignty is becoming increasingly important, reflecting the need for regional AI services that align with local regulations, standards, and values. As an example, Europe will benefit from its own strong, trustworthy infrastructure to support innovation, data protection, and ethical AI.

AI Foundation, including various models and all the services we offer, is already available on our own cloud infrastructure. As a next step, we are expanding our 麻豆原创 Cloud Infrastructure offering in our 麻豆原创 data center in Walldorf, Germany, to Deutsche Telekom through the Industrial AI Cloud project, providing secure, high-performance infrastructure for AI innovations across public institutions, defense, and society. 麻豆原创 delivers 麻豆原创 Cloud Infrastructure, 麻豆原创 Business Technology Platform, and applications 鈥� including our AI Foundation with frontier AI from Mistral, Cohere, and others 鈥� on Telekom鈥檚 Munich data center. Both companies uphold the highest standards of data protection, security, and reliability.

This marks a milestone as more European companies join the Industrial AI Cloud project, advancing applied AI across Europe with trusted, business-embedded solutions that unlock the full potential of industry data. See the announcement here.

Enabling customers to build, extend, share, and orchestrate AI agents

To help manage Joule Agents and Joule skills, we have introduced the concept of AI Assistants 鈥� role-based AI teammates, accessed through Joule 鈥� like a financial assistant that brings together agents for cash collection, treasury, and more. We will provide AI Assistants in Joule for every core business role, offering our users an agentic experience like never before.

Out-of-the-box Joule Agents are powerful, but we know that every company has unique requirements. We believe AI should adapt to users鈥� systems, not the other way around, so we are enabling them to use Joule Studio to extend 麻豆原创鈥檚 pre-built agents with custom fields, tools, and reasoning logic while retaining all the deeply grounded integration capabilities 麻豆原创 provides. Joule Studio also provides low-code tools to build custom agents that integrate with all other Joule Agents, Joule skills, and 麻豆原创 BDC.

Using a low-code approach, users can build Joule Agents visually with natural language and drag-and-drop. But we also want to meet the needs of developers who want ultimate flexibility. Our pro-code approach gives developers the freedom to build agents using the agentic framework of their choice 鈥� for example, LangGraph, CrewAI, Google鈥檚 Agent Development Kit, and more. 麻豆原创 Cloud SDK for AI now supports agentic development, ensuring these pro-code agents can be seamlessly integrated and giving developers the best of both worlds: deep integration and full flexibility.

No matter how you want to build agents, an important question is how to integrate them into the larger ecosystem beyond 麻豆原创. We鈥檙e making Joule Agents fully compatible with the agent-to-agent (A2A) protocol soon, so agents can discover and collaborate with each other.

A2A exposes rich semantics describing an agent鈥檚 capabilities, allowing both 麻豆原创 and third-party agents to work together seamlessly. We are collaborating with partners 鈥� AWS, Google, Microsoft, ServiceNow, and more 鈥� to standardize this protocol for full interoperability. This capability will allow Joule to orchestrate tasks across multiple agents, both 麻豆原创 and non-麻豆原创, increasing automation and productivity across the enterprise. Read more here.

To manage and govern agents across the enterprise, is now generally available, providing centralized control of 麻豆原创 and non-麻豆原创 agents. In addition, is available now for tracing agent actions, benchmarking against KPIs, and identifying bottlenecks or opportunities for agents to further improve business.

No 麻豆原创 TechEd without ABAP news

The ABAP journey continues with 麻豆原创-ABAP-1, which will be available in the generative AI hub in Q4 2025. Trained on ABAP code, it is designed to build ABAP AI use cases, enabling developers to build smarter, custom AI solutions in modern ABAP code. .

In addition, ABAP Cloud development is coming to Visual Studio (VS) Code. The new ABAP Cloud extension for VS Code delivers a streamlined, file-based development experience with built-in AI assistance. Powered by an ABAP language server, it will initially support 麻豆原创 Fiori UI service development and expand to additional ABAP Cloud scenarios over time. This brings ABAP development into the same environment where developers already build with UI5 and CAP. General availability is planned for Q2 2026. .

What鈥檚 next: embodied AI and quantum

麻豆原创 TechEd is always an opportunity to look to the future. This year, that future includes not just humans, but also autonomous devices, including humanoid robots.

By integrating Joule Agents natively with robots, 麻豆原创 is bringing business logic into the physical world, enabling a wide range of autonomous devices to operate with enterprise context. We highlighted our strategic partnerships with robotics companies and system integrators to serve customers like Sartorius, Bitzer, and Matur Fompak, demonstrating how our expanding physical AI ecosystem enables robots to understand business processes and execute complex tasks autonomously.

Early proof-of-concept deployments show Joule successfully integrated with 麻豆原创 business applications and autonomous systems across asset performance, logistics, field services, and warehouse operations. While still in the pioneering stage, these implementations illustrate how 麻豆原创 is extending Joule to serve both human users and autonomous devices, shaping the future of enterprise AI.

Read more about the partnerships and implementations here.

AI is a new compute paradigm that changes everything. But there is another compute paradigm on the horizon: quantum computing. It鈥檚 early days, but 麻豆原创 is driving the future of enterprise computing with a vision to help businesses get ready for quantum computing.

麻豆原创 is not building quantum hardware; instead, we are focusing on creating quantum algorithms for business applications. These solutions are simple to deploy 鈥� on when needed, off when not 鈥� and are designed to be hardware-agnostic, collaborating with partners such as IBM to ensure seamless integration without re-platforming. This approach will enable organizations to unlock operational efficiency and drive better business results at enterprise scale.

I couldn鈥檛 be more excited about what鈥檚 next for our customers鈥� future as we bring 麻豆原创鈥檚 AI-native architecture to life.

Philipp Herzig is CTO of 麻豆原创.

Joule for developers leverages a purpose-built large language model (LLM) trained on millions of lines of 麻豆原创 code. It can deliver contextual, ABAP-specific results that support tasks ranging from intelligent code suggestions to automated unit test creation. As customers continue their 麻豆原创 S/4HANA transformations, these AI features can also support optimized code migration through smart analysis, explanations, and actionable suggestions. The result: AI becomes a collaborative partner that helps developers tackle complex challenges with confidence and efficiency.

outlines how AI is transforming modern development. One key finding: 80% of developers reported increased productivity when using AI coding assistants, with an average productivity gain of 35%. The top-used features include unit test generation, code generation, and autocompletion鈥攃lear signs that AI is now a central pillar of the development experience.

To succeed in this evolving landscape, developers must cultivate new skills. These include writing precise natural language prompts, verifying AI-generated code, integrating proprietary data for improved AI context, and using AI to enhance requirements documentation. These capabilities ensure AI remains an intelligent collaborator that upholds enterprise-grade standards.

麻豆原创 Build solutions and ABAP Cloud can further empower developers by enabling automation, improved security, and scalable collaboration鈥攁ll while supporting a clean core strategy. These tools reflect 麻豆原创鈥檚 commitment to intelligent extensibility that balances innovation with system integrity.

AI is no longer just a futuristic concept鈥攊t鈥檚 a vital asset shaping every phase of the software development life cycle. Developers are evolving from code writers to orchestrators of intelligent systems that learn, adapt, and co-create. Joule for developers and ABAP AI capabilities illustrate how 麻豆原创 is leading this evolution by providing tools that are aligned with enterprise development needs and future-ready innovation.

To learn more, explore

Sonja Lienard is senior vice president at 麻豆原创 and head of BTP ABAP.

With more than 17,000 customers now leveraging 麻豆原创 Build solutions globally, momentum continues to surge, enabling developers to build, automate, and innovate with greater speed and ease. Today, we鈥檙e taking a huge step forward to bolster developer productivity within 麻豆原创 Build solutions!

We鈥檙e thrilled to announce new Joule-powered AI capabilities for 麻豆原创 Build Process Automation and 麻豆原创 Build Apps. These enhancements complement the previously announced AI capabilities in and 鈥攅mpowering developers of all skill levels to build more efficiently by leveraging comprehensive, AI-infused developer tools to deliver precise, contextualized outcomes powered by purpose-built, 麻豆原创-centric AI models. This can free up time for developers to be more productive, creative, and proficient in accelerating ABAP, Java, JavaScript, and visual tool-based application development and automation of 麻豆原创 processes.

Let鈥檚 look at how Joule can unlock new levels of productivity:

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鈥淭he latest AI features across 麻豆原创 Build solutions provide developers with a powerful tool kit to build and extend business applications across both 麻豆原创 and non-麻豆原创 systems.鈥�

Holger Mueller, Principal Analyst & VP at Constellation Research, Inc.

Comprehensive developer assistance for all 麻豆原创 development needs

Joule can understand 麻豆原创 development framework intricacies, anticipate developers鈥� needs, offer intelligent suggestions, and automate repetitive, mundane tasks like documentation and sample data generation. It can enable developers across low-code, pro-code, and automation projects to be more productive, creative, and proficient in accelerating apps or extensions for business applications like 麻豆原创 S/4HANA.

Key capabilities include:

• Application creation: Generate code, UI, data models, and sample data across 麻豆原创 programming models for Java, JavaScript, and ABAP, using Joule
• Code optimization: Refactor code, create unit tests, and generate code explanations, summarizations, and more with natural language queries and intuitive actions with Joule
• Process and workflow automation: Generate automation workflows and business rules using natural language queries

鈥淚n utilizing generative AI, 麻豆原创 Build Code offers our joint clients easier integration capabilities and a streamlined developer experience for cloud application development, boosting overall productivity and driving tangible value.鈥�

Chip Kleinheksel, Global 麻豆原创 Chief Technology Officer and Principal, Deloitte Consulting LLP

Contextual and precise results with purpose-built LLMs

Joule uses purpose-built large language models (LLMs) specifically tailored for 麻豆原创 workloads, such as our ABAP LLM, which can power code predictions and explanations. Developers can derive precise, contextualized results鈥攍ike code snippets or explanations鈥攆aster and more efficiently. Joule can also provide developers with real-time, context-aware support for code completion and optimization, as well as automation pipeline creation that understands the customers鈥� application environment, development project artifacts, and 麻豆原创-specific syntax.

Key capabilities include:

• Predictive code completion based on context, comments, and project heuristics
• Code explanations of core data services (CDS) view entities, classes, interfaces, and functional modules
• AI-powered assistance for documentation, best practices, and new concepts
• Workflow development and decision assistance based on processes, API specifications, and connected systems

Integrated AI tooling for seamless development

Developers can now enjoy a fully AI-infused development environment. Joule’s capabilities are integrated within 麻豆原创 Build development tools, including ABAP, to help ensure a smooth, cohesive AI-enhanced experience. This AI integration helps eliminate the headache of switching between development and AI tools and can generate actionable insights and outputs within a single place so developers can focus on what they do best鈥攂uilding innovative solutions.

Key capabilities include:

• Joule support for 麻豆原创 Fiori apps, 麻豆原创UI5 guided development, and more in 麻豆原创 Build solutions
• Joule integrated inside 麻豆原创 Business Application Studio and ABAP development tools for Eclipse for all Java, JavaScript, and ABAP-related development tasks
• Joule integrated into 麻豆原创 Build Process Automation project canvas for generation and summarization of processes, decisions, forms, and more, right in place using natural language

Road map and future enhancements

Our commitment to AI-driven innovation for developers is unwavering. Over the last year, we鈥檝e unveiled groundbreaking capabilities across our portfolio: Joule in , , , , AI agents embedded deep within 麻豆原创 Business Suite processes, and more. 

Looking ahead, we have a complete road map of cutting-edge features, including optimizing business logic, automating documentation, and enhancing data protection and AI compliance. To enable an agentic journey, developers will be able to develop custom AI agents tailored to their specific needs. Additionally, as customers continue to adopt 麻豆原创 S/4HANA Cloud, we plan to simplify the migration journey with enhancements that can meticulously analyze legacy code, provide clear code explanations, and suggest code optimizations. This will help ensure customers have a smooth, intelligent transition to the cloud alongside 麻豆原创鈥檚 clean core guidelines.

These new features will help empower developers to build more innovative, efficient, and secure workflows and applications. Stay tuned for more AI-driven innovations!

Get started for free

Don鈥檛 wait to transform your development experience! You can take advantage of our Joule for developer capabilities today at no charge for a limited time.

• Activate the  of ABAP AI capabilities
• Access the  free trial
• Explore Joule for developers with our 

We can鈥檛 wait to see how developers leverage the new Joule capabilities in 麻豆原创 Build solutions.

Happy coding!

Michael Ameling is general manager and chief product officer for 麻豆原创 BTP and a member of the 麻豆原创 SE Extended Board.

Two years ago, we introduced 麻豆原创 Build, a unified low-code environment that enables developers of all skill levels to create, extend, and automate business applications with drag-and-drop simplicity. Last year, we broadened its capabilities and integrated Java and JavaScript development with AI.

With more than 16,000 customers now leveraging 麻豆原创 Build globally, momentum continues to surge, enabling developers to build, automate, and innovate with greater speed and ease.

Today, we are thrilled to announce new enhancements of 麻豆原创 Build, combining the power of ABAP development, more generative AI capabilities, as well as deeper integration with 麻豆原创 S/4HANA and other business applications. 麻豆原创 Build streamlines extension creation and accelerates ERP modernization. It connects all 麻豆原创 development tools — ABAP, Java, JavaScript, and low-code — so teams can collaborate easily regardless of skill set. 

Let鈥檚 look at what developers can achieve with 麻豆原创 Build.

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麻豆原创 Build with ABAP offers developers capabilities to easily extend their 麻豆原创 S/4HANA and other business applications, utilizing Joule鈥檚 generative AI capabilities. It facilitates in-context collaboration between developers and business users to build business custom apps and processes efficiently, all without compromising on security and governance.

– Brad Shimmin, Chief Analyst, AI Platforms, Omdia

Streamline 麻豆原创 Application Development and Automation

麻豆原创 Build is the only solution offering direct development access within 麻豆原创 S/4HANA for easier customizations. Developers can quickly create scalable and secure 麻豆原创 S/4HANA extensions — both on stack, to extend applications within 麻豆原创 S/4HANA, and side by side, to extend applications on 麻豆原创 BTP — while following 麻豆原创’s clean core best practices.

Key capabilities include:

• The new 麻豆原创 Build extensibility wizard in 麻豆原创 S/4HANA Cloud for extending custom fields, logic, applications, and process automations while maintaining in-app business context
• Accelerating the creation of guided experiences with pre-built content to extend 麻豆原创 business applications across business processes such as spend management, HR, procurement, and more

Accelerate Development with Joule-Powered AI Capabilities

Envision a development tool where anyone, from beginners to seasoned pros, can rapidly bring their ideas to life with generative AI. Joule is the co-pilot that developers need for all 麻豆原创 development because it is uniquely trained on 麻豆原创 data and processes.

New generative AI capabilities include:

• Code explanation, code completion, business object generation, and unit test generation
• Documentation search and instant assistance from 麻豆原创 Help and 麻豆原创 Community within 麻豆原创 Build
• Workflow automation and approval recommendations
• The ability to extend Joule, allowing developers to create, deploy, monitor, and manage custom AI skills with drag-and-drop simplicity

Foster Fusion Team Development

麻豆原创 Build breaks down silos, enabling collaboration across development teams without barriers. Developers can achieve greater flexibility and scalability together as a team through:

• 麻豆原创 Build lobby, the central entry point for all development tools, now featuring access to ABAP, to build any type of extensions on 麻豆原创 BTP
• Streamlined navigation between ABAP, Java, JavaScript, and low-code tools while maintaining full business context for efficient full-stack application development
• Centralized lifecycle management and governance for all 麻豆原创 projects

Get Started Today

麻豆原创 Build is the gateway to faster, more efficient application development and automation for you and your organization.

• Want to learn more? Visit for more details.
• Ready to see 麻豆原创 Build in action? Sign up for the .
• Curious to learn more about 麻豆原创 Build? Read 鈥�.鈥�

JG Chirapurath is chief marketing officer for Business Technology Platform at 麻豆原创.

*General availability: The new capabilities will be available in Q4 2024, with additional AI features rolling out through Q1 2025