AI Coding Agents in 2026: Coherence Through Orchestration, Not Autonomy
57% of companies now run AI agents in production, yet quality metrics are sobering. The path to coherent software at scale runs through orchestration and human oversight.
Writing
Thoughts on AI strategy, technology leadership, and the gap between technical possibility and organizational reality. Published here and in outlets like MIT Technology Review, MartinFowler.com, and LinkedIn.
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NVIDIA's Rubin Chip: Cheaper AI Inference for More Viable Use Cases
10x cheaper inference changes the math on AI use cases. Teams can stop rationing tokens and start designing for longer context and multi-step workflows.
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Why AI Governance Needs Engineering, Not Just Policy
Effective AI governance requires more than policy documents. It needs the same engineering rigor we apply to building the systems themselves.
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The POC-to-Production Gap in Enterprise AI
Most AI initiatives fail not because the technology doesn't work, but because organizations aren't ready to operationalize it. Here's how to bridge that gap.
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Three Questions Every CTO Should Ask Before Starting an AI Initiative
Before investing in AI, technology leaders need honest answers to these three questions. The answers might change your approach entirely.
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On Staying Technical as a Technology Leader
The pressure to 'go strategic' and abandon hands-on technical work is strong. Here's why I think that's a mistake.