The next frontier in AI is not just developing individual agents, but orchestrating teams of them. Users will move from dialoguing with a single chatbot to managing multiple agents working in parallel on complex, long-running workflows. This becomes a new core skill for knowledge workers.
By the end of 2026, recording every meeting and applying AI agents to transcribe, summarize, assign action items, and align with strategy will be table stakes. Hoffman argues that companies not doing this will be making excuses, akin to sticking with horse-drawn carriages in the age of the car.
Instead of static documents, companies can embed their strategy into an AI agent. This agent assists in planning, identifies cross-departmental conflicts, and can be queried in real-time during decision-making to ensure constant alignment, making strategy a dynamic part of daily operations.
The most effective strategy for AI companies to manage public backlash is to make their products pragmatically helpful to as many people as possible. Instead of just warning about disruption ('yelling fire'), companies should focus their communication on providing tools ('paddles') that help people navigate the changes.
To achieve radical improvements in speed and coordination, we may need to allow AI agent swarms to communicate in ways humans cannot understand. This contradicts a core tenet of AI safety but could be a necessary tradeoff for performance, provided safe operational boundaries can be established.
The next wave of addiction won't come from passive consumption like social media, but from active creation. AI tools give people the powerful dopamine hit of successfully making things, a feeling most have never experienced. This is framed as a positive, potential-unlocking phenomenon.
Reid Hoffman predicts public discourse around AI will turn intensely negative. AI will be blamed for everything from rising electricity prices to unemployment, regardless of its actual impact. This scapegoating will intensify as AI's real, though initially small, disruptive effects begin to be felt.
The next major AI breakthrough will come from applying generative models to complex systems beyond human language, such as biology. By treating biological processes as a unique "language," AI could discover novel therapeutics or research paths, leading to a "Move 37" moment in science.
The traditional 9-to-5 is becoming obsolete not because we'll work less, but because work will resemble an entrepreneur's life: intense, project-based sprints followed by lulls. AI agents running in the background will amplify this asynchronous, high-variance work style.