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January 27, 2026

Four Essays from the CEO - #4

AI Market Dynamics in 2025: Agents Became Real and Talk of an AI Bubble

From the outside, 2025 might look obvious: “AI agents.” From the inside, it felt like a steep climb. The industry language changed fast: guardrails, evaluations, QA agents, reliability, orchestration. The tech improved quickly, and attention followed.

We felt that shift directly. One highlight: sharing the stage with OpenAI at the Handelsblatt AI Summit. It was exciting, and it signaled something bigger: agentic AI in engineering was no longer a niche topic. It has entered the mainstream.

Is there an AI bubble?

At the same time, we watched the AI market with a clear-eyed view. Parts of the AI ecosystem, especially infrastructure, show signs of overheating. When major players move huge sums around data centers and partnerships, it’s worth reflecting on. For now, my view remains: even if parts of the AI space look bubble-like, the application layer is solid. Real use cases, in production today, that deliver measurable value are not a mirage. That is where Synera lives. Real time saved, real cost reduction, real quality increases.

The companies that last will be the ones that:

  • Offer AI agents that do real, precise work, not just talk about it. This requires horizontal integration into existing toolchains to cover more tasks and offer greater agentic orchestration across complete value chains
  • Are flexible to integrate with older and newer tools. The tech space is changing rapidly, LLM models are updated quickly, agent-to-agent protocols are now available to facilitate enterprise-wide process orchestration. Still organizations use technology from the 90s. These worlds need to be combined if agents are going to deliver tangible value and scale.
  • Deliver repeatable value in operational environments, not just pilots
  • Have a clear roadmap to help customers lead change management
  • Meet enterprise IT, security, and compliance standards  

A CEO’s Perspective  

From the CEO seat, 2025 demanded two things at once: urgency and responsibility. We had to move fast without losing trust.
Leadership changes, performance expectations, global expansion: these were strategic shifts for Synera, not just operational ones.
The longterm vision remains: a JARVISlike companion for engineers. Not a chatbot, but a system that can:

  • Assemble toolchains
  • Execute engineering workflows
  • Iterate autonomously
  • Work operationally beyond a pilot

In 2025, although speed became a defining factor for our company, what mattered was proof.

  • Proof that agentic AI can engineer.
  • Proof that teams can scale without losing trust.
  • Proof that the future of engineering can change by freeing human creativity, not replacing it.

And after 2025, this is no longer just a vision. It is a trajectory we are already on.

This article is the fourth in a series by Synera CEO Dr. Moritz Maier about how Synera built agentic automation for engineering, helped usher in a new era of vehicle technology development and moved closer to a “JARVIS for Engineers”. A 360° year-end reflection from the CEO’s perspective. Read the other articles:

  1. From Breakthrough to Reality: Why Multi Agent Engineering Finally Works.
  2. From Engineering Workflow Automation to Agentic Digital Engineers
  3. AI Market Dynamics in 2025: Agents Became Real and Talk of an AI Bubble

About the author:

Dr. Moritz Maier is CEO & Co-founder of Synera. He was fascinated by the connection between technology and entrepreneurship from an early age – founding his first company at 16. His path later led him through scientific research and consulting to the central question that drives him to this day: How can engineers work more intelligently through automation – rather than just faster?
With a PhD in product development processes and experience in generative design, additive manufacturing, and process automation, he now works on the vision of digital engineers: AI agents that support technical development teams and give them more space for innovation.

His approach: Technology should adapt, not the other way around – only then can it truly help people in everyday engineering.

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