Building software where agents execute and humans steer a gate-driven framework from intent to production.
What's inside
The framework is organized around four interlocking concepts that together define how agentic software is structured, governed, and delivered.
Pillar 01
From Intent to Release every stage earns the next through proof of value, not assumption.
Intent → ReleasePillar 02
Quality checkpoints between every stage. Nothing passes until it proves it builds no exceptions.
Prove it buildsPillar 03
Autonomy spectrum from fully hands-on to fully hands-off calibrated per stage and context.
Hands-on → Hands-offPillar 04
The complete end-to-end ADLC guide combining all pillars into a unified operating model.
Full playbookPillar 01 · 6 Stages
The ADLC decomposes software delivery into six discrete stages, each with clear entry criteria, agent/human role assignments, and exit conditions. Every stage is a gate-protected handoff not an assumption.
Unlike traditional SDLC, each stage can run at different autonomy levels. Stage A may be fully human-directed while Stage D operates hands-off, depending on the team's verified trust in the agent's capability at that task type.
Pillar 02 · 5 Gates
Gates are not bureaucracy they are the mechanism that makes high autonomy safe. Each gate is a structured validation moment where the output of the preceding stage must demonstrably satisfy defined criteria before work proceeds.
Gates enforce the principle that agent confidence is earned, not declared. A gate-failed stage returns to the agent with structured feedback rather than escalating broken assumptions downstream.
Gate flow
Pillar 03 · 5 Autonomy Levels
The five autonomy levels define how much of a stage's execution is delegated to agents versus retained by human engineers. Level assignment is not fixed per team it is earned per task type based on demonstrated agent reliability at that task.
The RICE-A test (Reversibility, Impact, Confidence, Effort, Autonomy Fit) guides level selection at each stage gate, ensuring delegation scales with verified trust rather than optimism.
Autonomy spectrum
Context
Traditional SDLC wasn't designed for a world where non-deterministic agents perform substantial portions of the work. ADLC fills that gap.
LLM-based agents produce variable outputs. Without stage-gate governance, errors compound silently across a pipeline rather than surfacing at defined checkpoints.
Delegating too much too early is as harmful as delegating too little. ADLC's autonomy levels provide a structured ramp that matches delegation to demonstrated capability.
Even at Level 5 autonomy, humans define intent, approve gates, and own outcomes. ADLC makes human-agent role boundaries explicit so accountability is never ambiguous.
Stage F (Operate & Improve) isn't an afterthought it feeds signal back to earlier stages, enabling agents to improve their performance on future iterations.
ADLC is not a replacement for your current process. It layers atop any SDLC waterfall, agile, or continuous adding the agentic governance dimension without discarding what works.
The five-level autonomy spectrum means teams can adopt ADLC at Level 1 today and progress toward higher autonomy as agent reliability in their context is established and verified.