A coding assistant waits for the developer to type. A coding agent does not wait: given a task, it reads the repository, plans, edits many files, runs commands, reads the output, tries again and opens a pull request. This chapter concerns D3 Build and D4 Prove: how a developer directs such an agent within a written mandate, what the sandbox, credentials and budgets around it must be, how a run is recorded, who can stop it from outside the pipeline it uses, and whether agents should write and merge the code. Chapter 7 treated the tools of the craft up to the agentic mode; Chapters 9, 10 and 11 treat review and tests, the toolchain as an attack surface and the release path. Here the question is narrower: what authority does the developer give, to what, and how is it taken back?
The chapter shows the mandate and the run record as artefacts that belong in version control, separates three acts that are often confused (writing, merging and deploying), and stages the debate on whether agents should write and merge the code, with a verdict by class of work.
A coding agent is a program in which a model, given a task, repeatedly chooses a tool call (read a file, edit a file, run a command, search, query a service), receives the result and chooses the next call until a stopping condition is met. The model suggests the next step; the harness around it executes the step. That distinction matters for everything that follows, because the model has no authority of its own. All authority is whatever the harness, the sandbox and the credentials allow, and a mandate is the document that says what that is.
Primary topics explored
- What a coding agent is
- The mandate
- Sandboxes, credentials and permissions
- Stop paths outside the agent
- Run records
- One class that merges: patch-level dependency updates
About AI Developer
AI Developer is Book 12 of The Transformed Architecture. It takes the developer as its subject and asks what happens when AI is used broadly in software development: the five developer functions (frame, design, build, prove, steward), the delegation ladder and the Level 4 prohibitions, the stewardship principle (name, understand, revert), verification as the scarce skill, the junior pipeline, adoption and productivity as claims that need evidence, regulation (the AI Act, the Cyber Resilience Act, the Product Liability Directive, NIS 2, DORA, the GDPR), ethics, intellectual property and sovereignty in the toolchain, and the developer as a person, for European enterprises and public authorities.
It builds on the conclusions of Architecture as Code, AI Governance, AI Platform and Security, AI Red Team, AI Threat, The Transformed Security Architect, AI Boss, AI Blue, AI Purple, AI Operations and AI Leader.
developers at every level, tech leads and engineering managers, architects, platform engineers, site reliability engineers and testers, product owners and designers, leaders who decide on developer tooling, heads of public-sector IT and procurement, works councils and unions, educators, and supervisors and auditors.
Continue with the full chapter
Chapter 8: Build with Agents: Delegated Coding, Mandates and Sandboxes in AI Developer gives the detailed explanations, practical examples and implementation patterns behind this summary.
This whitepaper belongs to “The Craft of Developing” and is one of 37 drawn from the manuscript.