Ask a developer how long it takes to build a working AI agent today, and the answer is often hours, not weeks. Ask how long it takes to get that agent approved, connected to production data, and trusted by the business, and the answer gets a lot less certain.
SAP CTO Philipp Herzig made that point bluntly during a virtual media Q&A at SAP TechEd 2026 in Berlin on Tuesday. "Building is, quite frankly, the most unimportant part these days, because you can do it so quickly," he said. The harder questions come before and after: what to build, whether to deploy it, which agents get access to core systems, and whether the agent delivers the value it promised.
That framing explains most of what SAP announced this week. The new developer tools are less about writing agents and more about everything around them.
Start with Joule Studio, SAP's AI-first environment for building and extending agents. The Joule Studio CLI can now configure Model Context Protocol (MCP) connections, development skills, and authorizations in one step. When a developer opens the project in their own IDE, business and product requirements are already there as structured project files. SAP says the goal is to let developers spend their time on agent logic instead of setup. General availability is rolling out in phases.
Testing got attention, too. Joule Studio adds a built-in sandbox where teams can run test queries, inspect traces, and use auto-generated unit tests before an agent reaches production. Offline evaluations, planned for late Q4 2026, will check accuracy, agent-to-agent (A2A) call correctness, and resistance to prompt injection against auto-generated scenarios. Changes to prompts, models, or data sources can be tracked, approved, and rolled back. That gives teams an audit trail when something breaks.
Then there's governance at the traffic level. SAP Enterprise AI Gateway, planned for Q1 2027, will put MCP, API, A2A, and LLM traffic under one control plane. It handles authentication, policy enforcement, routing, monitoring, usage tracking, and auditing. For developers, it includes an MCP developer hub for discovering and subscribing to MCP servers from any provider and reusing existing APIs and integration flows as agent-ready tools.
Herzig explained why that control point matters. "You don't want every agent out there to just arbitrarily talk to the SAP system and get the data out, or write something back into the system," he said. In SAP's model, an agent is registered in the SAP AI Agent Hub, reviewed against rules such as the EU AI Act, and verified. Only verified agents can run against the gateway. After deployment, SAP Signavio's agent mining compares what the agent actually delivers with what it was expected to deliver.
The other theme was cost. Herzig said customers worry about "the huge token bill," and he blamed much of it on naive use of LLMs. SAP's pitch is that business context from SAP Knowledge Graph cuts the number of tokens an agent needs. "The question is always how can we avoid tokens in the first place," he said.
He pointed to a comparison from the keynote. According to Herzig, the first iteration of the same agent took roughly 30 hours to build with Claude Code and two hours in Joule Studio, at about half the cost. He also acknowledged that developers can reach the same outcome with Claude Code. This is SAP's own benchmark on one example, so treat it as a claim to test, not a settled result.
Data access is part of the same story. SAP Business Data Cloud is adding a lakehouse built on Dremio, with native Apache Iceberg support, an Apache Polaris-based catalog, and a distributed SQL engine that queries data without copying it. General availability is planned for Q1 2027. A new Ontology Manager, planned for beta in November, will let developers curate domain-specific business context and reuse it across agents.
SAP also expanded its tabular AI models for structured data. SAP-RPT-TS handles time-series forecasting and is available now through SAP HANA Cloud or SAP AI Core. SAP-RPT-Decisions, aimed at approvals and routing decisions, is planned for Q4 2026. SAP-RPT-2, planned for Q1 2027, adds anomaly detection, embeddings, and multi-table processing. SAP and HPE also plan to run SAP-RPT aboard the International Space Station to triage anomalies and reconstruct missing sensor data without sending it back to Earth.
Some of this is usable today. SAP Integration Suite now supports native Git operations on integration flows, including comparing flows and resolving conflicts. The Joule Studio developer certification is free through Dec. 31. And for select customers, deploying and running custom agents on the SAP-managed Joule Studio runtime is free through December, with design-time tooling free under fair-use limits.
Herzig was clear that SAP doesn't expect to own every agent experience. "We are not saying that we are the center of the universe," he said. Through A2A and SAP's agent gateway, third-party agents running in tools like Copilot or Claude can call Joule Agents.
On autonomy, he compared agents to coding assistants. At first, developers approve every command. "And after a while, it's like, why is it bothering me all the time?" he said. Trust builds on simple, repeatable tasks. Regulated, high-risk decisions, such as those in HR, will keep a human in the loop for a while.
The open questions are practical ones. Much of the lineup won't be generally available until Q4 2026 or Q1 2027. SAP hasn't said what runtime pricing looks like after the free period ends. And the 30-hours-versus-two-hours claim needs testing outside SAP's demo.
But Herzig's core argument holds up. If an agent can be built in an afternoon, the bottleneck moves to deciding which agents deserve access, proving they work, and keeping the token bill in check. That's where SAP is putting its developer investment.