From LLMs to Agents: Why Context Engineering Needs Decentralized Infrastructure

DeGPT News 2025/7/3 11:00:00

Visual representation of decentralized context infrastructure connecting AI agents and models in a Web3 environment

AI is evolving beyond prompts

Today’s leading tech firms—like Meta, Apple, and Microsoft—are shifting from LLM chatbots to agent-based systems powered by real-time reasoning, memory, and multimodal capabilities.

But this evolution brings a new challenge: context.

From Prompts to Context Engineering

As highlighted in recent research, the future of intelligent systems depends not just on bigger models—but on better context.

Context engineering involves delivering LLMs:

Dynamic user history

Long-term memory

Real-time tools and signals

Model-agnostic system prompts

Secure, verifiable execution

This shift makes the infrastructure behind AI more important than the models themselves.

Why Centralized Context Is a Risk

Major players are struggling:

Meta is poaching top AI minds but rethinking whether to keep Llama at the core

Apple may abandon its own models, leaning on Anthropic or OpenAI

Closed ecosystems limit context portability, transparency, and long-term AI utility

In contrast, context in decentralized systems is:

Persistent

Permissionless

Interoperable across agents and models

Owned and controlled by users

How DecentralGPT Fits In

DecentralGPT is not just a place to run LLMs—it’s a foundation for agent infrastructure:

On-chain memory and interaction history

Open-source models like DeepSeek, Qwen3, GPT-4o mini

A DePIN-powered compute layer

Multi-agent, multi-model, multi-modal readiness

Free access—no sign-up or wallet needed

Why It Matters for Web3 and Web2 Developers

Whether you're:

Building agents with Claude or GPT-4

Testing context chains

Managing compute access

DeGPT helps you scale your AI logic without platform lock-in, while rewarding contributors through the $DGC token economy.

CTA – Build on Context that Lasts

Decentralized agents need decentralized context.

Try DeGPT today to explore how multi-model AI can be open, fast, and context-aware.

Launch the platform:https://www.degpt.ai

Run a node & earn $DGC

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