4 min read
|
Saved February 14, 2026
|
Copied!
Do you care about this?
The article discusses how advancements in agentic intelligence are reshaping the role of developers and the coding process. It introduces Entire, a new platform designed to enhance collaboration between humans and AI agents, focusing on a new software development lifecycle that captures context and reasoning through versioned checkpoints.
If you do, here's more
The software development landscape is undergoing a significant shift, driven by advancements in agentic intelligence. Tools like Anthropic's Claude Code and OpenAI's GPT-5.3-Codex are changing how developers work. Instead of traditional coding, developers now interact with multiple agents simultaneously through terminal windows. This has accelerated code generation but highlights a troubling bottleneck: the existing software development lifecycle was designed for human collaboration, not for the machine-driven processes of today.
Entire aims to address this disconnect by creating a developer platform where humans and agents can work seamlessly together. Their solution includes a git-compatible database that consolidates code and reasoning, a semantic reasoning layer for coordinating agents, and a reimagined software development lifecycle tailored for AI collaboration. They recently secured $60 million in seed funding to support this vision, underscoring the growing recognition that the industry needs a new framework for development.
The first product from Entire is the Entire CLI, which introduces Checkpoints. This feature captures the context of agent sessions as versioned data in Git, preserving the reasoning behind code changes. Each commit now includes metadata detailing the prompts and decisions made during the coding session, allowing for better traceability and collaboration. The tool aims to reduce redundancy and improve the efficiency of agent interactions.
Entire is also committed to transparency and community involvement. By releasing the Entire CLI as an open-source project, they invite feedback from developers to inform future updates. This approach emphasizes collaboration and aims to create a versatile platform that supports a variety of agents and models, reflecting a shift toward a more interconnected and collaborative development environment.
Questions about this article
No questions yet.