The Coming Shift in Software Architecture
I was reading this piece about AI agents, and it got me thinking about how we use our phones. You know, when you really look at it, most apps are just intermediaries. They sit between you and something you want to do. Order food, check your bank balance, book a trip. The app presents information, you tap buttons, and it executes a simple task.
But what if something could handle all that for you? Not just respond to commands, but actually anticipate needs and act on them. That’s the core idea behind AI agents. They’re not chatbots that wait for questions—they’re autonomous systems that perceive, decide, and act.
Why Apps Might Become Obsolete
There’s this interview on the Lex Fridman Podcast where an AI developer made a striking claim. They suggested that about 80% of today’s apps could become unnecessary once AI agents mature. Not just updated or improved, but completely replaced.
The reasoning is pretty straightforward when you think about it. Most apps exist to present information and execute simple tasks. An AI agent that can reason, browse, transact, and learn doesn’t need a dedicated interface for each function. Your calendar app waits for you to open it. An agent could monitor your schedule, notice you have a meeting across town, check traffic, and book transportation—all without you lifting a finger.
The Numbers Behind the Change
This isn’t just theoretical speculation. McKinsey estimates that generative AI and agents could automate 60-70% of employee work hours globally. That’s a staggering figure when you really consider what it means.
Investment tells a similar story. Cognition Labs, which created an AI software engineer called Devin, raised $175 million at a $2 billion valuation. Microsoft has poured billions into OpenAI and is embedding AI agents throughout its products. Google, Salesforce, Amazon—they’re all restructuring around this agent paradigm.
Customer service is already seeing massive shifts. Klarna replaced 700 human agents with AI that handles over 60% of support tickets. Software development, financial services, administrative work—these areas are all experiencing early automation.
The Job Market Implications
The World Economic Forum’s Future of Jobs Report suggests AI and automation might displace about 92 million jobs globally by 2030. They also predict around 170 million new jobs will be created, but here’s the thing: the new jobs require different skills than the ones being lost.
Jobs involving structured, repeatable tasks with clear inputs and outputs are most vulnerable. Data entry, basic customer service, junior coding roles. Meanwhile, roles requiring creative judgment, complex negotiation, or deep domain expertise might actually become more valuable.
Why This Matters for Crypto
This is where things get particularly interesting for decentralized systems. If AI agents are going to autonomously transact, negotiate, and manage resources, they need programmable money and trustless infrastructure.
They need smart contracts, not traditional banking systems with limited hours. They need permissionless payment rails that don’t require identity verification for software. The convergence of AI agents and crypto seems almost inevitable from an architectural standpoint.
Several projects are already building at this intersection. Fetch.ai is creating an agent-based economy where autonomous agents can discover, negotiate, and transact with each other on-chain. Autonolas is developing a framework for decentralized autonomous agent services. Morpheus is working on a peer-to-peer network for AI agents with built-in crypto payments.
The basic idea is simple: if agents replace apps, then the infrastructure those agents run on becomes critically important. And many believe that infrastructure should be decentralized.
The Regulatory Challenge
Regulators, as usual, seem to be playing catch-up. While authorities debate whether digital images are securities, AI agents are preparing to autonomously execute financial transactions, sign contracts, and manage portfolios.
Current regulatory frameworks have no provisions for autonomous software agents acting on behalf of users. This creates a significant gap that needs addressing.
This regulatory uncertainty actually highlights why decentralized, transparent systems matter. When an AI agent executes a transaction on a public blockchain, there’s an immutable record. When it does the same through a centralized API behind closed doors, you’re trusting opaque systems.
Looking Forward
That 80% figure might sound extreme, but the trajectory is clear. Major tech companies are investing billions in agent development. Use cases are multiplying rapidly.
For the crypto ecosystem, this represents a substantial opportunity. Decentralized networks could serve as the coordination, payment, and trust layer for an agent-driven economy. The builders working at this intersection—combining AI capabilities with crypto infrastructure—might be creating the foundational systems for the next generation of software.
It’s a shift that could reshape not just how we use technology, but how technology serves us. The apps we rely on today might become historical artifacts, replaced by intelligent agents that work quietly in the background. And the infrastructure supporting those agents could determine who controls the next era of digital interaction.
