Implementation Patterns

Pattern 01 — Waterfall Turbo

Keep your phase gates. Compress the calendar dramatically.

Best for

Regulated industries, fixed-scope initiatives, heavy documentation requirements.

AI usage

Generate full requirements packs, test plans, and audit trails at each gate.

Timeline

• Phase 0-2. Context, prototypes, architecture completed sequentially with executive sign-off.
• Phase 3-4. Task breakdown plus build/test handled in tightly managed execution waves.
• Phase 5. Compliance dashboards and KPI reviews prove value post-launch.

Benefits

• Full audit trail preserved
• AI documentation equals regulator-ready packets
• Predictable gate approvals with drastic time compression

Pattern 02 — Agile Acceleration

Blend phases into sprint cadence for continuous outcomes.

Best for

Product teams, SaaS companies, platform squads pushing weekly releases.

AI usage

Copilot prompts baked into planning poker, story refinement, and QA automation.

Timeline

• Sprint 0. Phase 0-2 run as a dedicated track to lock KPIs, prototypes, and architecture.
• Build sprints. Phase 3-4 align with normal sprint ceremonies. Daily AI pair programming drives build/test.
• Continuous. Phase 5 instrumentation feeds sprint reviews so every demo shows KPI movement.

Benefits

• Sprint compatible and familiar to teams
• Context package survives across iterations
• Materially faster throughput without burning trust

Pattern 03 — Structure-First Adoption

Prove the governance model, then layer AI when the org is ready.

Best for

Organizations without AI clearance, or teams proving BVDLC before tooling spend.

AI usage

None initially. Templates filled manually while compliance, security, or legal teams review. Once greenlit, swap the generators in without changing the process.

Timeline

• Phase 0-2. Use the book's worksheets to capture context, prototypes, and architecture manually — building the exact artifacts AI will consume later.
• Phase 3-4. Disciplined task planning plus QA scripts ensure quality while operating without copilots, proving the governance path.
• Phase 5. Outcome tracking proves ROI and builds the case for AI adoption.

Benefits

• Zero dependency on AI tools
• Meaningfully faster than traditional SDLC from structure alone
• Creates the compliance artifacts security teams need before approving AI
• Switch to AI with no process changes later

Related on this site

• Execution Patterns — per-task delivery modes (Human-Only, AI-Assisted, Agent-Delegated, Hybrid)
• 30-Day Pilot Blueprint — day-by-day playbook to prove BVDLC on a real initiative
• Launch Checklist — the gate criteria for moving between phases
• Case Studies — worked examples of each pattern in production