Analytical briefings for engineers, PMs, and CTOs
Analysis of AI model developments, enterprise deployment patterns, and the research advances shaping how organizations build and compete with intelligent systems.
4 min readThe AI chip shortage didn’t end — it transformed. The bottleneck shifted from wafer supply to CoWoS advanced packaging, which TSMC has sold out through 2026. NVIDIA locked up over 70% of available capacity, leaving hyperscalers and startups scrambling for alternatives.
4 min readOpen source AI has closed the performance gap with closed models. The MMLU gap narrowed from 17.5 points in early 2024 to under one point today, while inference costs dropped 60–80%. The real choice now is no longer capability — it is control versus convenience.
4 min readThe AI industry has no consensus definition of ‘production’ for AI agents. Most enterprise deployments labelled ‘production’ are narrow automations with human oversight, not autonomous multi-step systems. The definitional gap creates real risk: procurement decisions, SLA commitments, and compliance claims are built on undefined terms.
4 min read2025 will be remembered not for the volume of AI announcements but for five shifts that had real structural weight. Models got smarter, cheaper, and started taking action — but the more important story was what each shift revealed about where the field was actually heading.