Agentic Software Factory

An agentic software factory is a pipeline in which AI agents carry work from specification through design, coding, testing, review and deployment, with automated gates and human oversight at defined points. It extends the older software factory idea of repeatable, standardised production by adding agents that plan and act.

An assistant helps one developer inside an editor. A factory coordinates several agents and tools through a defined workflow, runs them in isolated sandboxes, checks their output with automated tests and security scans, and records what each agent did.

Typical stages are intake and specification, planning, implementation by coding agents, automated verification, review, supply chain checks such as signing and SBOMs, deployment and monitoring. Spec-driven tools such as GitHub Spec Kit and Kiro structure the early stages.

Use layered gates: tests including property-based and mutation testing, static analysis such as Semgrep and CodeQL, dependency and provenance checks with SLSA and Sigstore, human review of risky changes, and benchmarks such as SWE-bench to track agent quality over time.

Agents execute generated code and shell commands. Sandboxes such as Firecracker microVMs, gVisor, devcontainers and Kubernetes agent sandboxes limit what a mistaken or manipulated agent can reach.

Results vary. DORA research reports both benefits and delivery risks from AI adoption, while METR's randomised trial found experienced developers on familiar repositories were slower with early-2025 tools. Measure your own outcomes rather than assuming gains.

Links were checked in November 2026. Some sites block automated checks and may need a manual click. This page is a resource list, not engineering advice, and vendor documentation reflects the vendors' own views.