Blog
We build Anvil Coder and work with coding agents ourselves every day. Here we write down what holds up: how to prepare work, enforce rules and review generated code so that you merge it with a clear conscience.
Prefer a real run? The measured Laravel run shows plan, commits and checks step by step, and How it works explains the flow behind it.
2026-09-02
Spec-driven development with Anvil Coder: from a specification through tickets and commits to a draft pull request, with checks and human review.
2026-09-02
How Anvil Coder turns project rules into prompt instructions and executable checks, and why an instruction alone does not prove compliance.
2026-08-26
How Anvil Coder splits epics from YouTrack, Jira, GitHub and GitLab into stories, using configured triggers, separate coding approval and model usage.
2026-08-17
Spec-driven development uses a versioned specification as the working reference. Connect requirements, acceptance criteria, planning and code review.
2026-08-10
Separate approvals during AI coding from final code acceptance. Understand project settings, verification logs and human review before merging.
2026-08-03
Commits make changes traceable but do not prove that tests passed. Connect diffs, requirements and verification logs when reviewing AI-generated code.
2026-07-27
Put architecture rules in an AI agent's working context and support them with checks. Learn how to express constraints, examples and verification limits.
2026-07-20
Small TaskSlices bound the context and simplify review. Learn which tasks can be separated and why integration tests and dependency planning still matter.
2026-07-13
Prepare Anvil Coder with access, a repository, project rules and a small first ticket. Understand usage costs, verification and the final review.