AI, development and cloud

Tomáš Kubica

Practical writing about AI, development, cloud and what works when building modern systems.

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Agents change what one unit of work is

A reflection on how agents change the unit of work, move interaction from specification toward intent, and create a new economy of human and token capital.

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2026

  1. Agents change what one unit of work is
  2. Cheaper and faster agents with progressive disclosure MCP through Foundry Toolbox Search
  3. Saving tokens in GitHub Copilot
  4. How to centrally manage and govern skills for agents
  5. Is subscription a suitable business model for an AI product? Is AI getting more expensive? Are tokens getting more expensive? Or are we just moving toward a fair model?
  6. AI coding - context vs. measurement, software as memory, I will not learn your software, OpenClaw and the smart home
  7. Spiral reading: AI podcast from PDFs without losing context
  8. Three paths to GenUI and their pros and cons
  9. New Agent Skills Standard for Your Coding Workers in GitHub Copilot
  10. Coding agents — parallel agent work on your tasks

2025

  1. Deep dive into AI agent observability with Microsoft Agent Framework - tracing with open-source tools Aspire Dashboard and Langfuse
  2. Deep dive into observability for AI agents - metrics, logs and dashboards with Azure Monitor, Grafana and Application Insights
  3. Deep dive into AI agent observability with Microsoft Agent Framework - OpenTelemetry semantic conventions and using the OTEL collector
  4. How to do simple AI text analysis? LLM, fine-tuning, BERT, or embeddings?
  5. Your own data (RAG) for your AI agent, part three - AI chooses the strategy for getting to data itself
  6. Your own data (RAG) for your AI agent, part two - knowledge graph and advanced methods
  7. Your own data (RAG) for your AI agent, part one - step by step with Python and PostgreSQL