Cambridge, U.K.-based artificial intelligence lab Fetch.ai Ltd. today announced the launch of FetchCoder V2, an AI coding assistant purpose-built for autonomous software development.
Based on the corporate, its latest AI software development assistant addresses challenges that traditional, general-purpose copilots can’t by helping developers construct agents that may act, learn and interact independently across decentralized systems.
The corporate argued the AI agent economy is coming into its own: Autonomous agents have gotten the norm, moving out of research labs and into real production.
Agentic AI, the elemental strategy of constructing and organizing AI agents, represents a unique paradigm from traditional software development. Agents must coordinate not only with human developers, but with each other. Agents also need guardrails when operating autonomously, because mistakes can compound quickly. And so they operate across platforms, blockchains and application programming interfaces concurrently, creating complex interactions.
All that signifies that it’s impossible to examine code runs in single instances. Autonomous behavior should be verified and validated.
“FetchCoder V2 is about turning ideas into intelligent software that works,” said Chief Executive Humayun Sheikh. “It gives developers the tools and confidence to bring autonomous agents to life, without guesswork and with control over every step.”
Following within the footsteps of other tools in the marketplace, corresponding to Amazon Web Services Inc.’s Kiro, Fetch.ai made FetchCoder spec-driven. Developers tell the agent what they’re constructing before it generates a single line of code. It then validates the plan up front, aiming to make sure alignment across your entire team. The goal is to eliminate ambiguous requirements and reduce the danger of rework.
Safety can be inbuilt. For instance, dangerous commands are mechanically blocked. File modification budgets are enforced and changes are tracked and auditable.
During development, tests are baked into every step, making reliability a natural a part of the workflow. If something goes improper, developers can backtrack through progress to see whether the plan is flawed, discover what must be fixed, or reorganize the approach.
Under the hood, FetchCoder uses ASI:One, a proprietary large language model and hooks into Agentverse, Fetch.ai’s platform for locating and deploying hundreds of thousands of AI agents.
For users excited by connecting to the broader landscape of Web3 and blockchain technology, FetchCoder introduces native support for the Cosmos ecosystem. That support is meant to assist developers construct autonomous agents that interact directly with blockchain networks.
Fetch.ai positioned V2 as providing every part general-purpose coding assistants do to assist developers write code, while also helping them ship autonomous agents. The corporate added that the excellence matters: constructing the agent economy today will shape the long run.
Image: SiliconANGLE/Microsoft Designer
Support our mission to maintain content open and free by engaging with theCUBE community. Join theCUBE’s Alumni Trust Network, where technology leaders connect, share intelligence and create opportunities.
- 15M+ viewers of theCUBE videos, powering conversations across AI, cloud, cybersecurity and more
- 11.4k+ theCUBE alumni — Connect with greater than 11,400 tech and business leaders shaping the long run through a singular trusted-based network.
About SiliconANGLE Media
Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digital media brands that reach 15+ million elite tech professionals. Our latest proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to assist technology corporations make data-driven decisions and stay on the forefront of industry conversations.