Notion's AI agents transform product team workspaces.

Your daily PM briefing | May 14, 2026 | PM Interview Prep Club

Remember when AI felt like a future tech memo, all strategy decks and conceptual frameworks? Well, that memo just got a pull request. Today, we're not just observing; we're diving into the PMs and legendary builders who are actually shipping AI, embedding it into products, and getting their hands dirty. This isn't about understanding AI; it's about building with it, and if you're not getting practical, you're missing the boat.

When Anders Hejlsberg talks, you listen. The mind behind Turbo Pascal, C#, and TypeScript isn't just reflecting on tech history; he's looking straight into how AI will reshape the very act of software engineering. Hejlsberg sees AI fundamentally changing how developers write, debug, and even conceive of code. This isn't about AI replacing engineers, but augmenting them in profound ways, automating boilerplate, and surfacing insights that accelerate development cycles. For a PM, this means your dev team's capacity and velocity are about to get a serious upgrade – if you're smart about integrating AI into your engineering workflows. This isn't just theory; it's a veteran's roadmap for how AI reshapes the fundamental act of creation. How does your dev roadmap stack up?

Intercom, a company deeply entrenched in customer communication and AI agents, just dropped an ultimate guide to building and maintaining a knowledge base specifically for Sales Agents. This isn't theoretical; it's a practical blueprint for feeding your AI the right information using robust knowledge management strategies and Retrieval-Augmented Generation (RAG). They're laying out the exact steps, from content curation to structured data, you need to ensure your AI agents are not just fluent but also accurate and effective. If you're building any kind of AI agent for customer-facing roles, this is your how-to manual for giving it the "brain" it needs to perform. For any PM building an agentic product, the KM isn't just content; it's the core competency. Is your data ready to be an agent's memory?

Forget the mega LLMs for a second. Microsoft Research is showcasing how specialised, "small" foundation models are integrating into critical infrastructure. Their new GridSFM can predict AC optimal power flow in milliseconds, significantly boosting efficiency and unlocking massive cost savings for electric grid operators. This isn't about generalised intelligence; it's about pinpoint AI built for a specific, high-stakes domain. It gives grid operators direct, real-time visibility into congestion and system health. As a PM, this is a powerful signal: AI's integration isn't just in consumer apps or enterprise SaaS; it's fundamentally enhancing the invisible, foundational systems of our world. This isn't consumer-facing, but it screams: AI isn't just for chat; it's for optimising fundamental systems with tangible, massive cost savings. Where's the opportunity in your industry's small foundation model?

Notion is making a clear strategic move, transforming its workspace into a true hub for AI agents. As reported by TechCrunch, their new developer platform lets teams connect various AI agents, external data sources, and custom code directly into Notion. This isn't just about adding AI features *to* Notion; it's about making Notion *the place* where AI agents live and operate within your workflow. It signals a shift from discrete AI tools to integrated, agentic productivity software that orchestrates multiple AI functions. For PMs, this is a masterclass in platform strategy: instead of building every AI feature yourself, you enable an ecosystem in which others can integrate with and extend AI capabilities within your product. Notion isn't just integrating AI; it's building an *ecosystem* for agents. Is your product a standalone AI tool or an AI orchestrator?

The collective signal here is deafening: AI has crossed the chasm from theoretical discussion to hands-on building and deep integration. As a PM, you need to be thinking beyond just "AI features" to how AI fundamentally re-architects your product's capabilities, your engineering team's output, and even your own role in crafting these solutions. This isn't about hiring an "AI PM"; it's about *every* PM understanding the practicalities of integrating, empowering, and even coding with AI to ship truly transformative products today.

If today's stories sparked an interview-shaped thought, here's where to take it next:

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Written by the team at PM Interview Prep Club — Coaching, community, and content to help you ace your PM interviews.

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