The progress made in automated software development seems to be stunning!
What will be the role of a future software developer/engineer?
How much will we be able to accelerate software development in coming years? I bet by a lot!
"... Meta and Harvard researchers have released the Confucius Code Agent, an open sourced AI software engineer built on the Confucius SDK that is designed for industrial scale software repositories and long running sessions. The system targets real GitHub projects, complex test toolchains at evaluation time, and reproducible results on benchmarks such as SWE Bench Pro and SWE Bench Verified, while exposing the full scaffold for developers.
Confucius SDK, scaffolding around the model
The Confucius SDK is an agent development platform that treats scaffolding as a primary design problem rather than a thin wrapper around a language model. It is organized around 3 axes, Agent Experience, User Experience, and Developer Experience. ..."
From the abstract:
"Real-world software engineering tasks require coding agents that can operate over massive repositories, sustain long-horizon sessions, and reliably coordinate complex toolchains at test time.
Existing research-grade coding agents offer transparency but struggle when scaled to heavier, production-level workloads, while production-grade systems achieve strong practical performance but provide limited extensibility, interpretability, and controllability.
We introduce the Confucius Code Agent (CCA), a software engineering agent that can operate at large-scale codebases. CCA is built on top of the Confucius SDK, an agent development platform structured around three complementary perspectives: Agent Experience (AX), User Experience (UX), and Developer Experience (DX).
The SDK integrates a unified orchestrator with hierarchical working memory for long-context reasoning, a persistent note-taking system for cross-session continual learning, and a modular extension system for reliable tool use.
In addition, we introduce a meta-agent that automates the synthesis, evaluation, and refinement of agent configurations through a build-test-improve loop, enabling rapid adaptation to new tasks, environments, and tool stacks.
Instantiated with these mechanisms, CCA demonstrates strong performance on real-world software engineering tasks. On SWE-Bench-Pro, CCA reaches a Resolve@1 of 54.3%, exceeding prior research baselines and comparing favorably to commercial results, under identical repositories, model backends, and tool access."
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