Anticipating the Future: AI Engineering in 2026

🚀 Welcome to 2026: The Future of AI Engineering!

As we kick off the new year from New Zealand, I’m excited to share insights on how AI will evolve. 2025 was wild—now it’s time to focus on practical, reliable solutions. Here’s what to watch:

Key Trends:

• Shift from AI Agents to Workflows:

  • Agents offer high variability but struggle with reliability.
  • Workflows provide structured, predictable outcomes—essential for tasks involving money and data.

• Open Source Models on the Rise:

  • Competitive with proprietary models, allowing for greater innovation and cost efficiency.

• Emergence of Smaller Language Models (SLMs):

  • Fast, specialized models often outperform larger counterparts on specific tasks.

• Regulations Matter:

  • Adapting to varying regulations globally is crucial for developing “regulation-aware” AI systems.

What This Means for You:

• Focus on building with reliability over hype.
• Embrace open source and prioritize systematic evaluation.
• Continuous learning in AI engineering fundamentals is essential.

✨ Join the conversation! Let’s discuss your AI strategy or how to navigate agent/workflow design. Share your thoughts below! 🤖💬

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