Don't view AI as just a feature set. Instead, treat "intelligence" as a fundamental new building block for software, on par with established primitives like databases or APIs. When conceptualizing any new product, assume this intelligence layer is a non-negotiable part of the technology stack to solve user problems effectively.

Businesses currently present disconnected personalities to customers across sales, service, and marketing. AI agents can bridge these silos to create a seamless, long-running dialogue that remembers context throughout the entire customer journey, fundamentally transforming the customer relationship.

The primary bottleneck for many users isn't a model's raw intelligence but the user's ability to provide sufficient context. The next paradigm shift will be AIs that can autonomously enter a new environment (like a Slack channel), gather context, and figure out how to be useful, dramatically lowering the barrier to value.

Current communication tools like Slack are ill-suited for managing AI agents. The future lies in integrated "super apps" that combine chat interfaces with built-in credential management, file systems, and API key provisioning, creating a unified environment for human-agent collaboration.

Existing APIs for services like email are often stateless and designed for transactional marketing. The next generation of tools for agents must be stateful, mimicking human services like Gmail. They need to support complex workflows like searching, threading, and filtering, all accessible programmatically.

OpenAI's new platform, Frontier, is designed for building 'AI co-workers' that can access a company's various data sources and systems. This represents a strategic move beyond single-user chatbots toward an enterprise-grade orchestration layer for managing teams of interconnected AI agents.

As foundational AI models become commoditized, the key differentiator for apps will be their communication prowess. The ability of an AI to explain itself, understand urgency, and know when to interrupt or escalate to a human will define user trust and value more than its raw intelligence or task-completion ability.

As users increasingly rely on AI agents, traditional graphical user interfaces will become obsolete. SaaS products must evolve to offer conversational interfaces that other agents can interact with directly. The primary user will shift from a human clicking buttons to another AI sending messages.

The primary barrier for useful AI agents is not the underlying model but the complex task of 'data wiring'—connecting to a user's real-world context like emails, local files, and support tickets. Products that solve this difficult integration challenge, where most agents currently fail, will gain a significant competitive advantage.