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Nordic builders shift from models to agentic workflows
Agentic AI is no longer a slide in a pitch deck. It is the default way Nordic teams ship production systems in 2026. Tieto’s latest survey of 600 IT leaders in Finland, Sweden, and Norway shows 68% of respondents now run at least one agentic workflow in production. Only 12% still rely on single-model prompts. The shift is sharpest in embedded systems: Nordic Semiconductor’s nRF Connect SDK now includes AI-assisted development loops that auto-generate, test, and deploy firmware agents on resource-constrained MCUs. TSMC’s European Symposium confirmed the hardware stack is keeping pace, physical AI chips are moving from lab to fab, cutting inference latency by 40% for on-device agents. Why it matters here. The Nordics have always built for real hardware, not cloud-only demos. Agentic workflows let teams replace brittle prompt chains with self-correcting loops that run on the edge. That means lower cloud bills, tighter data sovereignty, and faster iteration. Finnish startup Lovable just expanded its Google Cloud deal 5× to handle the compute load of thousands of customer-service agents that now handle 70% of Tier-1 tickets without human handoff. In Sweden, Klarna’s internal agentic platform has cut fraud detection false positives by 32% since March. One thing to do this week. Pull the evals out of the appendix. Instrument every agent with a lightweight eval harness that logs task completion, latency, and cost per run. Tieto’s data shows teams that do this within the first two sprints ship 2.3× faster. Start with a single metric, say, “did the agent book the meeting”, and expand from there. The evals become the spec, not the other way around.
researched · 5 sources
14 AugAgents & modelsreaches nearby
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