Starting RACE Programming from day one
No legacy constraints. No existing rituals. Build the RACE Programming system right, adding headcount only when each configuration is provably saturated.
Why greenfield is the best starting point
Greenfield is where RACE Programming's economics are strongest (~3× the output for the same budget): no legacy constraints, no team rituals to unlearn, no brownfield coordination overhead. From day one the bottleneck is specification quality and Team Principal availability, not code volume.
The failure mode in greenfield AI projects is scaling prematurely, adding engineers before the Pit Wall is proven, before the Executable User Story cadence is stable, before Team Principal availability is locked. The six-stage model below prevents it.
The six scaling stages
Add headcount only when the current configuration is provably saturated. Each stage is a complete, functional delivery system, not a partial team waiting to be filled.
Start as one pair
Pit Wall pair (Forward Deployed Engineer + AI Product) acts as both Pit Wall and Pit Crew. They author EUS, build prototypes, execute.
When to move on: Team Principal's required pace exceeds two-person capacity → add the first Pit Crew Software Engineer. Pit Wall keeps executing alongside the new engineer.
Split roles, add crew
Still insufficient → add a second engineer, forming a Pit Crew. Pit Wall covers quality gating until throughput justifies a dedicated Pit Crew Quality Engineer. The Forward Deployed Engineer shifts to Pit Wall only (50% allocation).
When to move on: Still not enough throughput → move to the scaled form: one Pit Wall serving 2–5 Pit Crews simultaneously.
Grow to 5 Pit Crews
The scaled form: one Pit Wall serving up to 5 Pit Crews. Add Pit Crews as demand grows.
Five Pit Crews = throughput of 10 Scrum teams with a synchronized backlog. Unreachable with a classic delivery approach.
Split streams
If demand still exceeds one Pit Wall's capacity at 5 Pit Crews → split with Team Principal into 2 independent streams, each with its own Pit Wall.
The pattern repeats from Stage 1 within each stream.
Each stage adds headcount only when the previous configuration is provably saturated.
Who you need, and when
Pit Wall (Stage 1 minimum)
- Forward Deployed Engineer (Pit Wall lead). Architecture decisions (ADR), prototype build, Pit Wall execution oversight.
- AI Product. Gherkin acceptance scenarios, EPB management, EARS NFR, client communication.
- Silicon Software Engineer (the AI agent). Prototyping and spec authorship alongside the human pair. Not headcount: the AI teammate.
- Both human roles required. One person may cover both in early-stage engagements.
- Qualification threshold: AI Fluency at senior level. Prototype build time ≤ 2 days. EUS acceptance rate > 80% first pass within 2 months.
Pit Crew (add when Pit Wall saturated)
- Pit Crew Quality Engineer + 2 Pit Crew Software Engineers + the Silicon Software Engineer (the AI agent, not headcount).
- No ceremonies. No standups. Inner cycle 2×/day.
- Rule: do not add people inside a Pit Crew; add Pit Crews.
- Qualification: AI-native execution. All 4 DoD gates green before every Pit Stop Demo, non-negotiable.
The first Stint
Team Principal: what you must lock in before Stint 1
- Availability SLA in writing. Team Principal responds to prototype review and Pit Stop Demo within 1 day. An engagement-level SLA, not a courtesy ask. Missing feedback blocks Pit Wall and compounds.
- Feedback calibration. "I don't like it" is not feedback. Train Team Principal to answer: Is this what I meant? What business rule is missing? What would my user say? Calibrate in Stints 1–2.
- No direct Pit Crew contact. If Team Principal bypasses Pit Wall and tasks Pit Crew directly, intervene immediately. First occurrence: address. Second: escalate as engagement risk.
Metrics from week one
See the Framework overview for full role and artifact specifications. If your team is migrating from Scrum, the From Scrum guide covers the transition mechanics in detail.