Boldare at LeadDev Berlin 2025 - AI-enhanced leadership and the next chapter of engineering culture

AI as an amplifier, not a revolution

One of the strongest messages that resonated throughout the event was that AI doesn’t replace people, it amplifies systems. As shared in the State of AI-Assisted Software Development 2025 report:

AI amplifies what already exists. In well-organized teams, it accelerates flow and quality. In struggling teams, it magnifies dysfunction.

This perspective mirrors our own experience at Boldare. AI adoption alone doesn’t transform organizations – AI-enhanced systems do. When supported by solid communication, feedback loops, and a healthy engineering culture, AI becomes a catalyst for smarter, faster, and more consistent delivery.

“20–30% of our code is written by AI”

During one keynote, a quote from Satya Nadella (Microsoft CEO) captured everyone’s attention:

I’d say maybe 20% to 30% of the code that is inside of our repos today are probably all written by software [AI].

This isn’t a prediction – it’s reality. AI now contributes meaningfully to production-level codebases. At Boldare, we’re also seeing how AI-assisted coding changes the developer experience: reducing cognitive load, supporting review processes, and freeing space for creative problem-solving.

The H.O.L.D. framework – a mindset for AI-enhanced decision-making

One of the most insightful sessions introduced the H.O.L.D. framework – a model for responsible collaboration with AI systems:

• Halt – Pause with intention
• Observe – Verify before you trust
• Loop back – Synthesize and calibrate
• Deliberate – Reflect and transfer learning

We loved how this model blends perfectly with our own product mindset:\ experiment, reflect, adapt. AI tools can accelerate delivery, but only when combined with human judgment and deliberate learning cycles.

From “taming hallucinations” to building trust through feedback

Another memorable talk explored the challenge of AI hallucinations – and how to ensure consistent value through feedback-driven learning loops.\ By connecting user feedback and system observations directly into LLM pipelines, teams can move from “occasional brilliance” to continuous reliability.

At Boldare, we’re exploring similar ideas in our AI-enhanced engineering workflows – treating models not as code generators, but as context partners that help us think better, design clearer, and learn faster.

5 ideas that stuck with us

1. Fail cheaply. Learn fast. Build smarter. Small, inexpensive experiments > big, risky bets.
2. Clarity scales better than control. Clear goals and shared understanding scale, micromanagement doesn’t.
3. Architects don’t leave chaos – they leave clarity. Architecture is not documentation; it’s decision visibility.
4. Prompts are the new design docs. The way we ask shapes what we build.
5. Broadcast decisions. Build alignment. Deliver impact. Sharing unfinished thinking helps build momentum and shared clarity.

LeadDev Berlin reminded us that technology evolves, but principles stay the same. Great engineering still comes down to clarity, curiosity, and collaboration — now amplified by AI.

For us at Boldare, this was more than a conference. It was a confirmation that AI-enhanced leadership isn’t about tools — it’s about people who know how to combine insight, experimentation, and empathy at scale.