Technical depth on AI, Azure, Next.js, and the engineering decisions behind them.
Industrial software written in Java, C#, or older languages accumulates over decades. TypeScript is increasingly the modernisation target for the customer-facing and operator-facing layers. This post walks the migration patterns that work in manufacturing, automotive, and energy contexts, and the cases where switching languages is the wrong answer.
The capability spectrum from stateless LLM to multi-agent orchestration is one of the most conflated concepts in the 2026 AI market. The distinctions matter. They change architecture, they change cost by an order of magnitude, and under the EU AI Act they change compliance posture.
A complete working pattern for type-safe Server Actions in Next.js 15 using Zod v4 — auth-aware wrappers, shared client/server schemas, file uploads, discriminated error shapes, useActionState wiring, and tests that exercise the validation boundary.
Industrial documents arrive as scanned paper, multilingual procedures, and proprietary CAD exports. Azure AI Search skillsets turn them into queryable text with structured metadata. This post walks the OCR, entity, language, and custom skill patterns that make the difference between a searchable index and one that actually answers technical queries.
A concrete playbook for reducing Azure OpenAI bills in 2026. Break-even math for Provisioned Throughput Units, prompt-cache economics, the Batch API 50 percent discount, Foundry IQ for retrieval, tiered model routing, and the telemetry that keeps the wins honest.
A practical pattern for rotating Azure secrets with zero downtime using Managed Identity, Key Vault rotation policies, and versioned references — including the common mistakes that cause rotation-induced outages.
A decision matrix for running AI workloads on Azure Container Apps versus AKS — GPU support, scale-to-zero economics, networking, blast radius, operational overhead, and when graduating from Container Apps to AKS actually pays off.
The Digital Omnibus on AI moved the Annex III high-risk deadline from 2 August 2026 to 2 December 2027, and Annex I embedded systems to 2 August 2028. Article 50 transparency, the Article 5 prohibitions and the general-purpose AI duties did not move, so this is the Swedish prep list rewritten around what is already enforceable and how to spend the runway that is left.
Generic LLM copilots are a liability in manufacturing. Technicians need answers that cite the exact procedure, not plausible-sounding text. Retrieval-augmented generation grounded in Azure AI Search solves this when architected correctly. This is the pattern that holds up under service-bay pressure.
A production observability stack for LLM applications on Azure — wiring OpenTelemetry, Langfuse, and Application Insights together so traces, token usage, eval scores, and platform metrics land in the same view.
A practical look at the View Transitions API in Next.js 15 — where native browser transitions replace Framer Motion, where library-based animation still wins, and the patterns that keep bundle size and performance aligned.
A practical comparison of SQL Server 2025 vector search against Azure AI Search and pgvector for hybrid RAG — when collocating vectors with your transactional data is the right call, and when a dedicated search layer still wins.