A product discussed on AI Engineer.

From Writing Code to Designing Systems: How the Developer Role is Changing — Chris Noring, Microsoft
Jul 11, 2026 · 23:05
Chris Noring from Microsoft argues that the developer role is shifting from writing code to designing systems and orchestrating AI agents, using tools like GitHub Copilot and Claude. He proposes a workflow starting with the CLI rather than the editor, employing agents.md for high-level guidance, skills for repeatable tasks, and custom agents for orchestration. Noring demonstrates scaling by delegating tasks via /delegate in the CLI or assigning issues to agents in the GitHub UI, allowing developers to become 20x more productive. He stresses that guardrails are essential to prevent agents from producing 'slop', and that human-in-the-loop oversight remains critical. The episode emphasizes that developers must encode standards and constraints into their workflows to maintain consistency and quality at scale.

Why your product needs an AI product manager, and why it should be you — James Lowe, i.AI
Jul 28, 2025 · 18:37
James Lowe, Head of AI Engineering at the UK Government's Incubator for AI, argues that technical expertise makes AI engineers ideal candidates for the critical role of AI Product Manager, which balances business viability, technological feasibility, user desirability, and the core question of possibility. He shares three hard-won lessons from building products like CONSULT, Minute, and Redbox: resolve AI uncertainties early with evaluations and real-user tests (achieving 1,000x faster and 400x cheaper consultation analysis), experiment widely with features then cut back (streamlining a transcription tool from overwhelming options to a focused Justice Transcribe used for Prime Ministerial meetings), and pivot harder than ever as the landscape shifts (Redbox evolved from digitizing ministerial red boxes to a secure LLM chat client, then to an MCP-based tool provider when Microsoft Copilot Chat went free). The episode emphasizes that AI product management is a mindset, not just a title, and that engineers should step into this leadership gap to build impactful AI products.

Running AI Application in Minutes w/ AI Templates: Gabriela de Queiroz, Pamela Fox, Harald Kirschner
Aug 14, 2024 · 1:29:02
In this workshop, Microsoft's Gabriela de Queiroz, Pamela Fox, and Harald Kirschner show how to deploy AI applications in minutes using AI templates, Azure OpenAI proxy, and GitHub Codespaces. They walk through deploying a simple chat app, then two RAG applications: one that queries a Postgres database with SQL filtering, and another that performs RAG on unstructured documents using Azure AI Search. Key decisions include using async frameworks like Quart and FastAPI, token-based chunking, and hybrid retrieval with semantic reranking for best results. They stress the importance of running evaluations with hundreds of samples and share production insights from Copilot Chat, where TFIDF sparse indexing and LLM reranking are used. The session includes free Azure credits and a proxy to bypass Azure OpenAI approval, allowing attendees to deploy everything without spending their own money.
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