The road from prompt engineering through context, agents and spec-driven development to closed loops - and why an executable definition of a good result is a company's most valuable asset.
Practical techniques for reducing token consumption in agentic coding without losing result quality.
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.
A practical demo of how Foundry Toolbox Tool Search reduces input tokens through progressive disclosure, cold search, and warm auto-pin.
A workflow proposal for team-managed agent skills through a catalog, local PoC, GitHub issue, and agentic triage.
A reflection on why agents change the economics of AI products and why a pure flat subscription model runs into limits.
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Copilot, skills, context, feedback, and practical work with agents in software development.
How user interfaces, pricing, consumption, and business models change in AI-first products.
Practical personal workflows for using AI to accelerate learning, reading, and work with information.
Retrieval, vector search, knowledge graphs, and strategies for getting the right data into AI answers.
Concrete patterns for using AI over text, data, agents, and operational telemetry.
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