Inside Google’s ‘Agentic Gemini Era’ Announced at I/O 2026

Below is what Pichai meant—and how Google’s latest tools illustrate the shift.

Why Pichai thinks today’s AI may soon look “primitive”

Pichai pointed to the speed of capability growth and adoption across Google’s AI systems. One striking metric: Google says it is now processing 3.2 quadrillion tokens per month, a roughly seven‑fold increase from the 480 trillion tokens reported at the previous year’s I/O event.

That surge reflects both rapidly improving models and the fact that AI is being integrated into more everyday products—Search, Workspace, Android, YouTube, and developer tools.

In interviews, Pichai suggested that when people look back a few years from now, they may see today’s systems the way we now see early mobile phones: impressive for their time but extremely limited compared with what followed.

The meaning of the “agentic Gemini era”

The centerpiece of Google I/O 2026 was Pichai’s description of a new stage in AI computing: agentic systems.

Instead of waiting for prompts, these systems can:

• reason through problems
• plan multiple steps
• execute actions across apps or services

Pichai said the company’s latest launches mark the beginning of this “agentic Gemini era,” where AI systems increasingly function as proactive assistants rather than passive chatbots.

This shift also reflects Google’s long‑term strategy of embedding AI across its ecosystem so that it can coordinate tasks across different tools and services.

Gemini Spark: a 24/7 personal AI agent

One of the most visible examples of this shift is Gemini Spark.

Google describes Spark as a 24/7 personal AI agent designed to help manage a user’s digital life. Under the user’s direction, it can proactively coordinate tasks across Google products and take actions on their behalf.

Key characteristics include:

• Continuous operation rather than single prompts
• Integration across Google apps and services
• Ability to complete multi‑step tasks automatically

This type of agent represents a move toward persistent AI assistants that function more like digital collaborators than simple tools.

Gemini 3.5 Flash: built for agents and coding

Google also introduced Gemini 3.5 Flash, the first model in its new 3.5 model family.

The company positions Flash as a model optimized for agentic workflows and complex coding tasks, particularly those involving long sequences of actions or problem‑solving steps.

According to Google, the model:

• combines frontier‑level intelligence with fast response speeds
• rivals larger flagship models on many tasks
• excels at long‑horizon problems such as multi‑step development workflows or complex research tasks.

These capabilities are important for AI agents that must plan and execute tasks autonomously rather than produce a single answer.

Gemini Omni: multimodal creation from any input

Another major launch was Gemini Omni, a model designed for multimodal generation.

Google says Omni can combine text, images, audio, and video inputs to generate high‑quality video outputs, starting with cinematic video creation and editing through conversational prompts.

The model merges Gemini’s reasoning abilities with generative media systems, representing a broader push toward AI that can understand and generate across many formats at once.

How the role of engineers may change

The agentic shift also has implications for software development.

As AI systems become better at planning and executing multi‑step tasks, engineers may spend less time writing every line of code and more time guiding AI systems that handle large portions of the implementation.

Google’s positioning of Gemini 3.5 Flash as a model designed specifically for coding agents and long‑running workflows illustrates this direction.

However, publicly available statements around I/O 2026 stop short of claiming that engineers will fully transition into “managing teams of agents.” The stronger, source‑supported takeaway is that Google expects AI agents to take on more complex programming tasks over time.

Addressing public anxiety and competition

Pichai also acknowledged that the rapid pace of AI development is creating both excitement and concern. Public reactions to AI technologies increasingly include debates about job disruption, safety, and the broader societal impact of automation.

At the same time, the competitive environment is intensifying. Google’s announcements at I/O highlighted both its pace of product releases and the scale of its infrastructure investments, signaling that the company intends to compete aggressively as AI becomes the next major computing platform.

The bigger picture: AI as a new computing platform

Taken together, the announcements at Google I/O 2026 illustrate a broader shift underway in the tech industry.

AI is moving from a tool that answers questions to a platform that completes tasks. Systems like Gemini Spark, Gemini 3.5 Flash, and Gemini Omni show how Google is trying to build an ecosystem where AI agents can coordinate information, generate content, and execute complex workflows across applications.

If the pace Pichai described continues, the current generation of AI may indeed look primitive surprisingly quickly—much like the early phones that preceded the modern smartphone era.