2025 sees accelerated convergence in chip design, AI software, and distributed computing. The rise of application-specific semiconductors (for AI inference and training), edge/cloud hybridity, and agentic/automated AI components reshaped architectural decisions. McKinsey and other technology reports emphasize that future computing will not be one size fits all – chip specialization, silicon photonics and energy efficiency were front and center in the 2025 roadmap.
Tech of upcoming 2026
How product and engineering teams should adapt
Design for diversity: Assume that your product will run partly in the cloud, partly at the edge, and it needs to be gracefully scalable.
Prioritize observability and SRE: With more autonomous agents and model-driven components, incident surfaces multiply. Fast shipping without logs/telemetry is incurring expensive costs.
Green computing matters: Customers and regulators are increasingly concerned about the emissions associated with computing. Where possible, track and publish calculation-related carbon metrics.
Quick Architecture Template (Starter)
Use a three-layer approach:
(1) edge estimation for latency-sensitive features;
(2) cloud orchestration and model retraining;
(3) Data lake with controlled access for audit and compliance.