Dominique Ronde

Dominique Ronde is a Staff Solution Engineer, PhD candidate in Applied Artificial Intelligence, and author focused on AI, data streaming, Apache Kafka, Apache Flink, and real-time system architecture. With more than 20 years of experience in IT, data platforms, and digital transformation, he helps organizations design reliable, scalable, and practical data systems. On Big Data Pilot, he writes about AI, machine learning, event streaming, software engineering, and the realities of building technology that actually works in production.

AI in Quantitative Investing: Limits of Autonomous Stock Picking Systems

AI-driven stock picking agents are often presented as the next step in quantitative investing. The narrative is compelling: autonomous systems ingest market data, reason over it, and continuously improve decisions through feedback loops. In theory, this aligns well with modern machine learning paradigms and agent-based architectures. In practice, the situation is more constrained. These systems

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Hallucinations Are Not a Bug. They Are an Engineering Constraint.

If you believe hallucinations in AI will disappear with the next model release, this blog post might be uncomfortable to read. Because they won’t. And this is not because the technology is broken or because engineers haven’t tried hard enough. It’s because this is not a product problem in the first place. And for everyone

Hallucinations Are Not a Bug. They Are an Engineering Constraint. Weiterlesen »

Cloud Is Not a Disaster Strategy

What recent regional disruptions remind us about resilience, locality, and architecture Recent geopolitical tensions in the Middle East coincided with service disruptions across parts of a major hyperscale cloud platform. Public reporting indicated that more than one region and several availability zones experienced degradation during the same period. Situations like this are complicated and affect

Cloud Is Not a Disaster Strategy Weiterlesen »

Everyone Talks About Agents. Nobody Talks About State.

Over the past year, the discussion in AI has gradually shifted away from models as isolated reasoning engines and toward agents as autonomous operational systems. Large language models are no longer framed merely as tools for generating text or answering questions. They are presented as components capable of planning, acting, coordinating across APIs, and making

Everyone Talks About Agents. Nobody Talks About State. Weiterlesen »

OpenClaw Is Not the Autonomy Revolution You Think It Is

When you scroll through social media today, you might come away believing that OpenClaw has ushered in a new era of autonomous AI assistants that you can drop straight into production and have them “just work.” That impression is misleading. OpenClaw, formerly known as Clawdbot and Moltbot, is a clever and technically interesting side project

OpenClaw Is Not the Autonomy Revolution You Think It Is Weiterlesen »

Running Code AI Locally: An Engineering Reality Check

Over the last couple of days, my LinkedIn feed has been flooded with euphoric posts about “Code AI” and “local coding assistants”. Screenshots of terminals, bold claims about productivity exploding, and the familiar undertone that if you are not running an LLM locally via Ollama, OpenCode, or Copilot, you are already falling behind. I know

Running Code AI Locally: An Engineering Reality Check Weiterlesen »