Services Approach Why Us About Domains FAQ Contact Book a Consultation
Our Approach

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.

What ADLC Changes

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

Human

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

Agent

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

Human

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

Agent

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

Human

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

Agent + Human

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.

Governance Principles

What Stays True at Every Gate

These are the principles InLoop applies at every stage of the model, regardless of engagement size.

Clear requirements Least-privilege access Human review for consequential output Automated tests and evaluation Traceability of important actions Monitoring and escalation Human ownership of production accountability
Get Started

See ADLC Applied to Your Build

Curious how this model would work for your product or agentic workflow? Start with a conversation.

30-minute call ยท no obligation