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Autonomous AI Agents on Blockchain: Discover Fetch.ai (FET)
Why is Fetch.ai Revolutionary?
In a landscape where artificial intelligence is concentrated in a few giant corporations, Fetch.ai emerges as a solution that democratizes access to AI technology. It is a layer 1 blockchain network that combines two transformative forces: AI-powered autonomous agents and decentralization.
The vision is clear: enable anyone, without needing to be an engineer or have millions in resources, to create, deploy, and monetize artificial intelligence applications. This represents a fundamental shift in how we understand AI within the decentralized ecosystem.
The Technology Behind FET
Fetch.ai operates as a protocol built with the Cosmos SDK and WASM language. Its architecture rests on three fundamental pillars:
Agents: Autonomous entities that perform specific tasks. A developer can create an agent to carry out a particular job, or configure it to interact with other agents and expand its capabilities. They can be public or private depending on needs.
Agentverse: A cloud platform where these agents are deployed and registered. Its importance lies in eliminating the need for expensive hardware to run AI applications, democratizing operational costs.
The AI Engine: A large language model (LLM) that interprets user instructions and executes the corresponding actions. This engine is intelligent: it can route a task to a single agent or coordinate multiple agents if complexity requires.
Origins and Significant Milestone
Fetch.ai was founded in 2017 by Humayun Sheikh, Toby Simpson, and Thomas Hain from Cambridge, United Kingdom. The platform was officially launched in 2019, but a crucial moment arrived in February 2022: the Fetch.ai mainnet went live with FET as its native token.
Before this, after a successful funding round in 2019, FET was born as an ERC-20 token on Ethereum. Over time, the network gained significant traction: in March 2023, it raised $40 millions led by DWF Labs, reaching a valuation of $250 millions.
Practical Applications Transforming Industries
Fetch.ai’s capabilities go beyond theory. Real implementations already exist:
Strategic Partnerships
Fetch.ai’s partnerships demonstrate its relevance:
Bosch: The Fetch.ai Foundation collaborated with Bosch to explore AI and Web3 solutions that optimize industrial processes, generating significant savings.
Deutsche Telekom: As Europe’s largest telecommunications provider, its subsidiary MMS actively participates as a network validator.
IOTA: Partnered with this decentralized IoT platform to enable granular data control, reduce dependencies on centralized systems, and monetize anonymous data.
FET Tokenomics: Distribution Details
FET is the utility token that grants access to the entire network. Initially, $7.05 million was raised in September 2018 (private sale) and another $6 millions in March 2019 (IEO).
The maximum supply of FET was set at 1,150 million tokens. According to updated data as of January 2026:
The original distribution allocated 40% to the Fetch.ai Foundation and founders, 17.6% through token sales, 22.4% reserved for future launches and mining, and 10% for advisors.
FET has multiple utilities: paying network fees, deploying AI models, and accessing advanced services. As a Proof of Stake (PoS) blockchain, holders can stake their FET to secure the network and earn rewards, as well as participate in governance.
Platform Strengths
Current Challenges
Despite its strengths, Fetch.ai faces limitations:
How to Acquire FET
FET is available on most major exchanges. To buy:
Final Reflection
Decentralized artificial intelligence is not just a trend; it is a necessity. With FET and Fetch.ai, tools emerge that allow developers, small businesses, and individual creators to participate in the AI revolution without relying on corporate giants.
As AI integrates into more industries and sectors, the central question is: who controls this technology? Fetch.ai offers a different answer, putting power into the hands of the community through autonomous agents that work together, learn collectively, and transform complex real-world tasks into accessible and transparent solutions.