The Agentic Development Life Cycle
AI agents are changing the economics and mechanics of software development. The opportunity is not to remove engineers from the process. It's to let AI handle more execution while experienced humans remain responsible for judgment, quality, risk, and accountability.
From Human Execution to Human Governance
Traditional SDLC assumes human execution throughout most activities. ADLC introduces capable AI agents into execution while adding explicit human validation and governance gates.
Plan
A senior engineer scopes the work: what's in, what's out, what dependencies exist, and what "done" looks like. This step doesn't get delegated to an agent, because the quality of everything downstream depends on how well it's framed here.
Agent-Build
Agents write the implementation, tests, and docs directly against the plan, cycling through iterations faster than a human-only team could turn around pull requests. Speed here is the point, but speed without the next gate is just risk moving faster.
Human Review
A senior engineer reads the actual diff, not just the agent's summary of it: checking correctness, security implications, and whether it fits the codebase's existing architecture. This is where most of the judgment calls in the cycle happen.
Agent-Refine
Review feedback goes straight back to the agent, which revises immediately rather than queuing into next sprint. Turnaround that used to take days often takes minutes, but it still returns to a human before anything ships.
Human Approval
Final sign-off rests with the person accountable for the outcome, not the agent that produced it. That's a deliberate governance choice: speed from AI, accountability from people.
Ship & Monitor
Deployment and monitoring are AI-assisted, watching for anomalies and flagging issues early. Escalation, incident response, and the conversation with the client if something goes wrong stay with a person.
What Stays True at Every Gate
These are the principles InLoop applies at every stage of the model, regardless of engagement size.
See ADLC Applied to Your Build
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