ChatGPT, Claude, Cursor... What did every major AI product of 2025 have in common? They were all built for "me, faster." Writing code, drafting docs, generating images — all solo missions. But here's the thing — a16z's 2026 outlook keeps hammering the same point: AI's next killer app isn't productivity. It's connection.
What Is It?
Every year, a16z publishes its "Big Ideas" series forecasting the tech landscape. In the 2026 edition, seven partners from the Apps team each tackled a different topic — but one thesis ran through all of them.
"We're moving from an era where AI does work for you, to an era where AI connects you to other people."
The shift is happening across three axes:
a16z's Three AI Shifts
1. Single-player → Multiplayer. Most AI tools today are "me + model" setups. You chat alone, you get results alone. Fareed Mosavat at a16z speedrun put it bluntly: "Multi-player AI will eat single-player AI." The tools that win will be the ones where AI outputs are shared across teams, with context flowing between people.
2. Making → Thinking. Anish Acharya pointed out that "every tool we use is built for execution." IDEs make code. Figma makes designs. Spreadsheets make models. But tools for exploration — tools that help you figure out what to build — barely exist.
3. Apps → Platforms (distribution channels). ChatGPT's Apps SDK, Apple's mini-app support, group messaging rollout. Consumer AI products finally have a native distribution channel. Acharya called it "a once-in-a-decade gold rush in consumer tech."
Add Olivia Moore's vision of voice agents managing entire customer relationships, Marc Andrusko's prompt-free proactive AI, and Seema Amble's multi-agent teams coordinating enterprise workflows — and the picture becomes clear.
Act 1 of AI was the "personal productivity revolution." Act 2 is the "redesign of connection and collaboration."
What Changes?
Here's how current AI products differ from what's coming, broken down by key dimensions.
| Dimension | Productivity AI (Act 1) | Connection AI (Act 2) |
|---|---|---|
| Usage model | Me + AI (1:1) | Team + AI (N:1 or N:N) |
| Core value | Speed, efficiency, cost savings | Shared context, coordination, discovery |
| AI's role | Executor (does what you ask) | Orchestrator (connects the dots) |
| Tool type | Making tools | Thinking tools |
| Output flow | Individual → Individual | Individual → Team → Customer |
| Distribution | Standalone apps, websites | ChatGPT app store, mini-apps |
| Competitive moat | Model performance | Network effects, shared data |
This isn't just speculation — there's data backing it up.
Morning Consult's consumer AI survey revealed a telling paradox: 55% of power users who actively use AI also said "too much technology can be a bad thing." That's up from 40% just 15 months earlier.
TD's 2026 AI Insights Report points in the same direction. While 78% of Americans use AI, their usage patterns are becoming increasingly "relational" — shifting from solo productivity to using AI for connecting with others.
People don't want AI to be more powerful. They want AI to make their relationships richer. Forbes analyzed this as "the loneliness crisis driving explosive demand for AI-powered emotional connection."
Getting Started
If you're building consumer AI products, here's a practical framework for applying a16z's thesis.
- The "solo or social?" test
Pick one AI feature you're building right now. Does its output become more valuable when shared with others? If yes, there's room to design it as multiplayer. ChatGPT's group messaging is heading exactly this direction. - Expand from making tools to thinking tools
Build AI that helps users figure out what to create, not just how. Acharya noted that "as coding agents get more accurate, the hard problem shifts to deciding what to build next." Support the exploration and discovery process with AI. - Consider the ChatGPT app store as a distribution channel
The OpenAI Apps SDK and mini-app ecosystem are opening up. That's a native distribution channel reaching 900M users. If you're building consumer AI, this is an opportunity you can't ignore. - Put AI "in between" people
Shift from AI that helps individual users to AI that orchestrates between them. Like Seema Amble's multi-agent vision — AI that connects team members' context and coordinates workflows across the organization. - Design for the "tech paradox"
Even power users worry about tech overload. Morning Consult data shows that pushing utility without building trust backfires. "Invisible AI" — what Marc Andrusko calls prompt-free, proactive AI — could be the answer.
Heads Up: Related Content
"a16z: Notes on AI Apps in 2026" focuses on coding agents and software-first teams. This piece dives deeper into the "connection" angle from a consumer AI product planning perspective.
