Phase 1: Manual
Human engineers write and review nearly all code. Scale is tied directly to headcount.
Consulting Offering
Agentic Development
Move from AI-assisted coding to an AI-autonomous delivery model where agents handle execution and your engineers operate the system.
From craftsmanship to factory model
In traditional software delivery, output is constrained by human coding capacity. In Agentic Development, AI agents become the primary delivery engine while humans define objectives, guardrails, and final acceptance.
Phase 2: AI-Assisted
Copilots improve throughput, but humans still drive each unit of delivery.
Phase 3: Agentic Factory
Orchestrated agents code, test, and iterate; humans supervise system behavior and business alignment.
Agentic Development vs GenDD
Both approaches use AI, but they operate at different levels of autonomy and scale.
| Dimension | GenDD (AI-Assisted) | Agentic Development (AI-Autonomous) |
|---|---|---|
| Primary actor | Human developer with AI copilots | Orchestrated AI agents with human oversight |
| Scaling model | Still tied to human throughput | Output scales through multi-agent workflows |
| Human role | Hands-on implementation for most tasks | Factory manager: objectives, guardrails, approvals |
| Workflow structure | Tool-augmented individual workflows | Role-based agent loops (architect, coder, reviewer, tester) |
| Best fit | Fast productivity gains in existing team patterns | Systemic transformation of delivery operating model |
Why midmarket teams adopt Agentic Development
Cost decoupling
Increase feature output without linear payroll expansion.
Knowledge persistence
Operational logic is encoded in workflows and agents, reducing key-person fragility.
Speed to market
Agents run continuous iteration loops and can compress cycle time dramatically.
Consistency and quality
Agent roles can enforce repeatable standards for testing, review, and release readiness.
What we build with you
- Agent archetype design: Architect, Feature Dev, QA, and DevOps agent roles
- Workflow orchestration for multi-agent collaboration and handoffs
- Human-in-the-loop approval protocols for high-risk decisions
- Legacy codebase integration and progressive refactoring strategy
Roadmap to agentic maturity
- 1. Audit: Identify high-friction SDLC bottlenecks and automation potential.
- 2. Pilot: Deploy a focused agent use case such as testing or documentation.
- 3. Expansion: Introduce feature-delivery agent loops alongside human teams.
- 4. Transformation: Transition to a governed AI delivery factory model.
Are you building code by hand, or building the factory?
We help leadership teams design and operationalize agentic software delivery with practical guardrails and measurable business outcomes.