# The Next AI Platform Isn’t a Model — It’s Your Context

Source: https://www.youtube.com/watch?v=Hkdi-zXMZGo
Recap page: https://rapidrecap.app/video/Hkdi-zXMZGo
Generated: 2025-11-04T13:09:56.134+00:00

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## Quick Overview

The next AI platform is context, not models, shifting focus from large language models (LLMs) to providing rich, specific context—like data, files, and environment—to make AI tasks plausibly solvable, a concept being actively developed by major players like Slack, Google (Gemini Enterprise), and Perplexity (Email Assistant).

**Key Points:**
- The next major AI platform shift is away from model size toward context engineering, which focuses on providing the right background, files, and environment for LLMs to solve tasks.
- Tobi Lutke coined the term "context engineering" over "prompt engineering" to describe the art of providing the necessary context for LLMs to be plausibly solvable (0:05).
- Slack is positioning itself as the "agentic OS" by integrating external AI agents like Claude, ChatGPT, and Perplexity via its new Real-Time Search API, enabling agents to access the full context of Slack chats (2:00, 4:06).
- Google introduced Gemini Enterprise to address the need for context, allowing it to pull context from Gmail, Google Drive, Calendar, and other Workspace apps, positioning it as a major competitor to Microsoft's enterprise AI offerings (10:41).
- Perplexity launched its Email Assistant, which integrates directly with a user's email account to draft replies, organize meetings, and analyze shared documents, emphasizing data privacy and SOC 2/GDPR compliance (9:31, 10:00).
- An industry expert (Mi Kang) suggests the winner in the platform war will be the product with the richest personalized context, prioritizing long session time and broadest information collection (8:55).
- The core engineering problem is optimizing the utility of tokens against LLM constraints to consistently achieve desired outcomes, moving beyond simple prompt crafting (1:48).

![Screenshot at 0:12: The key visual slide explicitly states the thesis: "THE NEXT AI PLATFORM IS YOUR CONTEXT," visually contrasting a circuit board \(representing models\) with interconnected application icons \(representing context and data access\).](https://ss.rapidrecap.app/screens/Hkdi-zXMZGo/00-00-12.png)

**Context:** This video discusses the emerging paradigm shift in Artificial Intelligence development, moving the competitive focus from the raw power or size of Large Language Models (LLMs) to the quality and accessibility of the context provided to these models. The discussion centers on the rise of "context engineering" as a core skill for building effective AI agents, referencing recent announcements from major tech companies like Slack, Google, and Perplexity, all vying to own the enterprise data layer.

## Detailed Analysis

The central argument is that the future of AI platform competition is context, not models. Tobi Lutke introduced the term context engineering, defining it as the art of providing the right background, files, and environment so that an LLM can solve a task—a concept superseding simple prompt engineering. Slack is aggressively pursuing this by integrating various third-party AI agents (Claude, ChatGPT, Perplexity, etc.) via its Real-Time Search API, effectively positioning Slack as the "agentic OS" that owns the conversational data context (2:00). Concurrently, Google introduced Gemini Enterprise, which leverages context from its entire suite (Gmail, Drive, Calendar) to compete in the enterprise AI space against Microsoft's offerings (10:33). Perplexity also entered this arena with its Email Assistant, which provides personalized, secure assistance by deeply integrating with user email context, learning communication styles, and drafting responses (9:31). Industry commentary suggests that the winner will be the platform that collects the most personalized context and achieves the strongest engagement metrics, highlighting the shift from model capability to data accessibility and orchestration.

### Context Engineering Thesis

- The next AI platform is context, not models
- Context engineering is the art of providing the right background, files, and environment to solve tasks
- Prompt engineering is framed as discrete, while context engineering is iterative (1:24, 1:46).

### Slack's Agentic OS Strategy

- Slack integrates external AI agents (Claude, ChatGPT, Perplexity) via new Real-Time Search API (RTS API) and Model Context Protocol (MCP) (4:06, 7:51).
- This allows agents access to the full context of Slack chats, making Slack the central hub for agentic work (5:17).
- Slack is positioning itself as the foundational infrastructure for agentic work (6:40).

### Competitor Moves - Google & Microsoft

- Google introduced Gemini Enterprise to pull context from Workspace (Gmail, Drive, Calendar) (10:33).
- Microsoft is also making moves to lock in its enterprise data context for its AI suite (11:18).

### Competitor Moves - Perplexity

- Perplexity launched its Email Assistant, which is context-aware, learns user style, and ensures SOC 2/GDPR compliance by never training on user data (9:31, 10:00).

### Industry Takeaways

- The platform that wins will be the one with the richest personalized context and strongest engagement metrics (8:55).
- Context is now seen as a moat, exemplified by Salesforce blocking rivals like Glean from accessing Slack data (7:14).

![Screenshot at 0:00: The host introduces the topic, stating the next big AI platform is context, not models.](https://ss.rapidrecap.app/screens/Hkdi-zXMZGo/00-00-00.png)
![Screenshot at 0:12: Title slide explicitly stating the video's thesis: "THE NEXT AI PLATFORM IS YOUR CONTEXT," contrasting hardware/models with data connectivity.](https://ss.rapidrecap.app/screens/Hkdi-zXMZGo/00-00-12.png)
![Screenshot at 0:51: A screenshot of a tweet from Tobi Lutke defining context engineering as superior to prompt engineering \(0:57\).](https://ss.rapidrecap.app/screens/Hkdi-zXMZGo/00-00-51.png)
![Screenshot at 1:40: A screenshot of the Anthropic blog post titled "Effective context engineering for AI agents," reinforcing the central theme \(1:43\).](https://ss.rapidrecap.app/screens/Hkdi-zXMZGo/00-01-40.png)
![Screenshot at 2:52: A diagram illustrating the difference between prompt engineering \(discrete\) and context engineering \(iterative and holistic\) for agents \(2:53\).](https://ss.rapidrecap.app/screens/Hkdi-zXMZGo/00-02-52.png)
![Screenshot at 4:06: A tweet from Slack announcing the ChatGPT app integration into the Slack sidebar, showing how Slack is becoming the agentic OS \(4:17\).](https://ss.rapidrecap.app/screens/Hkdi-zXMZGo/00-04-06.png)
![Screenshot at 7:07: A Google search result showing news that Salesforce is blocking AI rivals from using Slack data, highlighting the growing importance of data control \(7:14\).](https://ss.rapidrecap.app/screens/Hkdi-zXMZGo/00-07-07.png)
![Screenshot at 9:58: A tweet from Mi Kang detailing criteria for winning the platform war, emphasizing the richest personalized context and strongest engagement metrics \(9:00\).](https://ss.rapidrecap.app/screens/Hkdi-zXMZGo/00-09-58.png)
![Screenshot at 10:30: Google Cloud blog post introducing Gemini Enterprise, showing its visual branding and context-aware capabilities \(10:37\).](https://ss.rapidrecap.app/screens/Hkdi-zXMZGo/00-10-30.png)