Blog
Practical insights on agentic software delivery
Featured
SWE-in-a-team: a coding benchmark for software factories
Our SWE-in-a-team benchmark graded thirteen coding agents and models in an SDLC loop. An Open-Weight builder resolved every ticket at half the price.
Agentic SDLC, defined: a gated loop from issue to verified pull request
An agentic SDLC takes each change through plan, build, CI, review, preview and test, and sends rejected work back. In 260 missions, the loop fixed 40 of 46.
Claude Code on Linear: assign an issue, get a tested pull request
Assign a Linear issue to SHIP and Claude Code plans it, builds it, clears your CI, reviews it and tests it on a preview before the pull request reaches you.
Latest
Connect GitHub's and Linear's MCP servers to your coding agents
Bind GitHub's MCP server with a scoped token and Linear's with an OAuth sign-in. Keep review and QA read-only, and see each call on the run.
MCP servers for coding agents: bind them once, keep the keys out of the sandbox
Give your planner, builder, reviewer and QA agents the MCP servers your repository already declares, with credentials that never enter the agent's sandbox.
Run the pi coding agent headless on real tickets, in a sandbox
Run the pi coding agent as SHIP's builder in an isolated sandbox, on an open-weight model through your own OpenRouter key, with review and QA around it.
Codex code review for Claude Code: set up a second-provider reviewer
Keep Claude Code on the builder and put Codex on the reviewer, in ship.yml or for one mission, so a second provider reads every diff before you do.
What is an AI software factory, and how to build one with Claude Code
An AI software factory takes each issue through agent stages and verification gates to a pull request a person accepts, and records what every change cost.
Introducing SHIP - the agentic engineering platform you need
SHIP is here to help engineering teams deliver more with AI, control costs, and keep the quality practices that make software reliable.