From Tools to Companions
Imagine looking back on your day and realizing you hardly opened any traditional apps at all. Instead, you spent the day accompanied by a single AI assistant that helped you plan, execute, and wrap up each activity from start to finish. This might sound futuristic, but it's a logical evolution of how we naturally live our lives.
We don’t navigate our days by thinking in terms of individual apps or discrete files – we think in terms of activities: attending a meeting, catching up with a friend, going on a trip. Yet historically, our software has been built around things (posts, messages, documents) rather than the activities those things belong to. Now, a new paradigm is emerging where the most useful "app" might not be an app at all, but an AI agent that accompanies you through an entire activity.
From Things to Activities: A Shift in Focus#
For years, Software-as-a-Service (SaaS) products have been designed like specialized containers for specific types of content or tasks. Think about how we use digital tools today: we post pictures on Instagram, send private messages on Telegram, jot down journal entries in Day One, save receipts in a bookkeeping app, scribble notes in a handwriting scanner. Each of these is centered around a unit of work or content – a photo, a message, a note – and each excels at managing that unit. In a sense, traditional apps have a thing-based focus: their value is tied to the pieces of content or data you put into them.
But consider how we perceive our own lives. When you reminisce about a vacation to South Korea, you don’t mentally itemize the tools you used during the trip (translation apps, map services, etc.). You recall the experience – the people you were with, the places you visited, the sequence of events that unfolded. The apps and tools were just incidental, supporting actors. This highlights a disconnect: our digital tools have been thing-centric, while our memories and experiences are inherently activity-centric. The usefulness of software, it seems, might be far greater if it aligned with those activities directly, rather than just collecting artifacts from them.
AI Agents for End-to-End Workflows#
Recent advances in AI are enabling a dramatic shift from that unit-collection mindset toward end-to-end workflows. Instead of hopping between a patchwork of apps, we can envision using an all-in-one AI assistant dedicated to the specific task or activity at hand. This would be a single entity that you engage with for the entire duration of an activity, from the first step to the last. Think of it like having a skilled helper by your side whenever you set out to do something.
The metaphor of a sports equipment captures this well: a basketball is pretty much useless when you’re not playing the game, but during the game it’s essential at every moment. Likewise, an AI agent might be idle until you actually start the activity it’s made for – but once you do, it becomes central to the entire experience, just as integral as the ball is to basketball.
A Personal Example: Catching Up with a Friend#
Consider the simple activity of catching up with a close friend. Today, you might prepare by peeking at your friend’s recent Instagram photos, skimming their Twitter updates, maybe scrolling through your last chat history so you have things to talk about. These are all separate apps and streams of information you manually gather. Now imagine instead having an AI social companion that does this legwork for you. As you get ready to meet your friend (or hop on a call), you could ask this agent, "What's new with Alex lately?"
Within seconds, the agent aggregates highlights from Alex’s digital footprint – perhaps noting that they started a new job, posted vacation pictures from Thailand, and mentioned feeling under the weather last week. It might even pull in context from other sources (like a shared photo album or a recent email exchange) to give you a well-rounded summary.
During the catch-up conversation itself, that same agent could sit in the background (metaphorically like an invisible butler) to help as needed. The agent is multimodal by default – it can understand spoken questions, text prompts, even images you show it – all in service of making your interaction with your friend richer and more seamless.
One Agent to Rule the Meeting#
Now think about the activity of a work meeting. In a typical remote meeting today, you might use Zoom for the video call, Google Docs to share a file or take notes, and Mentimeter (or a similar polling tool) to gather feedback. You constantly switch contexts.
What if instead you had an AI meeting assistant that handled all of this orchestration for you in one place? You, as the human, would just focus on the discussion and decisions, while the agent takes care of the rest.
During the meeting, the agent can transcribe the conversation in real time, highlight decisions and action items, and even gauge the room’s understanding. If a document is mentioned, the agent might chime in, “I have the proposal file here—shall I share it now for everyone to see?”
By the meeting’s end, the same agent could send out a summary to all attendees, complete with key points, decisions, and assigned tasks. This is what an end-to-end workflow assistant can offer – a fluid, activity-based experience instead of a disjointed series of app interactions.
Building Products Like Hiring a Team Member#
This shift toward activity-centric design also changes how we imagine creating new software products. In the past, a successful tech product often addressed a narrow function across many industries – horizontal tools like Google Docs. The new mindset turns that on its head.
Now, designing a product starts to feel more like writing a job description and hiring a digital employee to fill that role.
Want to build a product that helps with travel planning? Instead of a flight booking widget, you build a travel agent AI that handles it all – from researching destinations to generating packing lists. One agent, many tools, one goal.
The previous tools were horizontal across verticals, but the new agents are verticals using the necessary horizontals to reach the desired outcome. They're more like full-stack teammates, not just building blocks.
Software That Follows Our Life’s Flow#
The most profound part of this shift is how it syncs with how we naturally experience time. Our memories are episodic, not data-driven. We remember trips, milestones, birthdays – not the tools we used to document them.
When software becomes activity-centric, it fades into the background. You’re no longer switching between apps; you’re simply living, with agents handling the invisible threads that hold your activities together.
You’ll look back not on the apps you used, but on the experiences you had – and the helpful agents that were there with you along the way.
Conclusion: From Tools to Companions#
Tech leaders already suggest that agents are the new apps. And if that’s true, then we’re entering a world where we don’t juggle tools – we partner with AI companions.
You might have a workout agent in the morning, a project agent at work, and a cooking agent in the evening. These aren’t dashboards or databases. They’re context-aware partners that align with how we think, move, and remember.
By focusing on activities rather than things, our digital world can finally revolve around our lives – not the other way around.
In the end, you may not remember the apps you clicked.
But you’ll remember the agent who helped you through it all.