Agentic SDLC Transformation
Your engineers have Claude Code or Codex, but no engineering practice behind them. We rebuilt how we deliver software around AI agents, and the framework is open. We start with one pilot team: a Forward Deployed Engineer runs real tickets with it for 8–12 weeks and hands back before/after numbers on your own delivery data.
HOW TO START
Three Ways to Work With Us
Read it – the framework, the guides and the case studies are public at raceprogramming.com. Take what fits and tell us what doesn’t work: the framework changes because of that feedback.
Talk to us – a 30-minute call with the FLS CTO team. Bring your admin console numbers from Claude Code or Codex. We tell you whether a program is worth it, and after the call we send a free written Adoption Baseline: seats, spend, practice, gaps.
Adopt it – one pilot team moves to RACE Programming for 8–12 weeks, on your codebase, under a fixed fee. Your other teams stay on Scrum until the pilot proves the cadence.
THE PROBLEM
Why Agentic Coding Stalls Without an Agentic SDLC
AI-assisted software development is already everywhere; an AI SDLC is not. When only the coding step speeds up, planning, review and testing stay manual, and team delivery barely moves.
OUR APPROACH
RACE Programming: The AI SDLC Framework Behind the Program
RACE Programming (Reliable Agentic Coding Excellence) is First Line Software’s AI SDLC framework for agentic engineering. Agile coordinates people. RACE runs a team that has a new member: the Silicon Software Engineer. We built and proved it on our own production work before offering it to anyone. It is a structural change, not a marginal one, which is why we start with one pilot team.
Prescriptive, not permissive. Every role, artifact and ceremony is specified, not suggested.
Executable User Stories. Our form of spec-driven development: one source of truth that engineers and agents read the same way.
Defined roles. The Team Principal on your side owns the outcome. The Pit Wall, a Forward Deployed Engineer and AI Product, directs the work with the Silicon Software Engineer. The Pit Crew, a Quality Engineer and two Software Engineers, ships it.
Stints. Delivery cycles of 2 to 3 days, each ending in a Pit Stop: a deploy to production.
Quality held fixed, RACE moves one side of the triangle: about 3× the finished software for the same budget, the same scope for about a third of the cost, or 2 to 5× faster time to business result. Conservative figures, measured on our delivered projects. Read the full framework and its guides at raceprogramming.com.
Explore RACE ProgrammingPROOFWhat RACE Programming Delivers on Our Own Projects
01
~3× the speed, ~⅓ the cost.
A two-person AI team shipped a production, document-grounded knowledge assistant for a 50+ office professional-services network.
02
A working demo in three days.
A three-person team rebuilt two native mobile apps as one React Native codebase from the old source archives.
03
Fixed price, end to end.
A supply-chain product delivered by a three-person team in the shape of RACE Programming.
04
Measured honestly.
On your program we start from your week-one baseline and report where you actually land, next to spend and code quality, including if the gain is low.
BUILT BYBuilt in the
FLS CTO AI Lab
RACE Programming was created by Pavel Khodalev, CTO of First Line Software, and the CTO AI Lab team, and refined on our own delivery work from 2024 to 2026. The same team stands behind every Agentic SDLC program.
Pavel Khodalev
CTO & Head of AI Lab
San Francisco, CA
Pavel Khodalev is a race car driver at Hendrick Motorsports with five years’ experience making speedy turns for several hours, helping his thousands of fans to fulfill their entertainment needs. Specializing in left turns and safely overtaking his opponents in the pursuit of a checkered flag, Pavel uses that expertise to never come in last.
By focusing on making sure Hendrick Motorsports ends up in the winner’s circle at every race, Pavel has been able to put the racing certifications he earned at driver’s school to good use. Over the years, his strengths at Hendrick Motorsports have garnered some recognition for winning several races each year. Pavel may spend his days at the racetrack, but it’s the thrill of the race and the glory of coming in first that gets him up in the morning.
When he’s not behind the wheel, Pavel is an avid fisherman and loves spending time in the great outdoors.
WHAT YOU GET
What an Agentic SDLC Transformation Installs
We don’t sell licenses and we don’t teach buttons. We install SDLC automation using agentic AI as one managed engineering practice, measured against your own delivery data.
Goes into your teams:
Executable User Stories, not prompts
An embedded Forward Deployed Engineer
Claude Code or Codex as the agent workforce
Review discipline
Stays with you:
Adoption and cost dashboard
Encoded playbook
ROI report
THE PROGRAM
The Program: Four Phases, 8–12 Weeks
Baseline & Map
Week 1-2.
Pick the pilot team, audit its usage, spend and practice, agree target metrics. We start from the Adoption Baseline you got after the first call. Deliverable: adoption baseline.
Embed & practice
Week 3-6.
Your FDE runs real tickets with the pilot team in Stints of 2–3 days, each ending in a production deploy. Your other teams keep working on Scrum. Deliverable: merged work + practice notes.
Encode & standardize
Week 7-8.
What worked for the pilot team becomes your standard, in your repos. From Standard up, a RACE Engineer rolls it out to the next teams. Deliverable: encoded playbook.
Visibility & handover
Week 9–10.
Before/after numbers your board can read without us. Deliverable: dashboard + ROI report.
Engagement Options
Fixed fee, agreed before we start. Three packages, same method; what changes is scope.
Standard
1 pilot team · 8 weeks · 1 embedded FDE.
Prove the cadence on one high-visibility team; the rest stay on Scrum.
Standard
4–6 teams · 10 weeks · FDE + RACE Engineer.
Pilot first, then rollout. Cross-team model policy + adoption and cost dashboard.
Enterprise
org-wide · 12 weeks+ · RACE Engineer, dedicated team and program manager.
Governance policy, full skills library, board reporting cadence.
HOW WE SOLVE IT
One Agentic Engineering Standard for Claude Code and OpenAI Codex
MODEL-AGNOSTIC
| — | Claude Code (Anthropic) | Codex (OpenAI) |
|---|---|---|
Repo context | CLAUDE.md standard | AGENTS.md standard |
Reusable team know-how | Skills, subagents, hooks | Skills, AGENTS.md conventions |
Integrations | MCP servers: Git, CI/CD, issue tracker, docs | MCP servers: Git, CI/CD, issue tracker, docs |
Where it runs | Terminal, IDE, CI | CLI, IDE, cloud tasks |
Model policy | Which model per task type, written into the playbook | Which model per task type, written into the playbook |
Why one standard, two agents:
FIT CHECKWho Agentic SDLC Transformation Is For
Not for
You haven’t licensed a coding agent yet — start with an evaluation
You want a product built from zero — that’s Rapid AI Delivery (Race Mode) →
You want AI workflows for Legal, Finance or Sales — that’s AI Enablement Services
You want a training course with certificates
Best for
You hold Claude Code or OpenAI Codex licenses
and the spend is material
Leadership asks for an ROI answer
and you don’t have one
Practice varies team to team
and you want one standard
You have production code
and real review load
Your teams run on Scrum and you want a safe first step:
one pilot team, the rest stays on Scrum
Where we apply itClaude Code Adoption works across different industries
Why First Line Software
Our own framework, proven in production
RACE Programming was built and validated on FLS delivery work before we sold it.
Claude Code and Codex, one standard
Select Anthropic Partner depth, without locking you into one vendor.
Measured honestly
Public benchmarks put the median gain near 7–8% and the measured ceiling near 24%. We report where you actually land, including if it’s low.
Fixed-price. Not T&M
Scope, timeline and price agreed before we start.
Agentic SDLC FAQ
What is agentic SDLC?
An agentic SDLC (agentic software development lifecycle) is a way of delivering software where AI coding agents such as Claude Code or Codex do much of the coding, testing and documentation, while engineers write specs, review output and own decisions. It needs defined roles, executable specs, review discipline and metrics, not just agent licenses.
How is this different from training engineers on Claude Code or Codex?
Tool training improves how engineers prompt. An agentic SDLC transformation changes the delivery process itself: spec-driven, role-based, agent-executed, measured. Same licenses, different operating model. An embedded engineer works on your real tickets under RACE Programming, and the result is reported against your own delivery data.
Do you work with OpenAI Codex or only Claude Code?
Both. The engineering standard sits above the agent: the same specs, review checklist, model policy and metrics apply to Claude Code and Codex. First Line Software is a Select Anthropic Partner, but we don’t resell licenses, so we recommend the agent that fits each team and task.
Will agentic coding reduce our AI spend or increase it?
Either is possible, and both are fine as long as you can see which and why. Model policy and context discipline lower cost per outcome; higher throughput can raise total spend. At the end you can state cost per merged PR and per delivered user story instead of cost per seat.
How do you measure whether it worked?
Against your own week-one baseline: PR throughput, cycle time, review load and code-turnover ratio, next to spend. RACE adds its own delivery metrics: user stories delivered per Stint, delivery cost in dollars, story acceptance rate, Pit Stop pass rate and rework rate. We report where you actually land, including if it is low.
What about code quality, and what do we own at the end?
Agentic output needs a stricter review standard than human code, so the quality number is reported next to the velocity number. Every CLAUDE.md, AGENTS.md, skill and playbook lives in your version control, and the dashboard runs on your data. No dependency on FLS.
The framework is public. Why pay you?
You can adopt it on your own; the guides are written for that. We shorten the path: an engineer who has run RACE on production work sits in your team and leaves the standard behind.
What changes for my team?
One pilot team moves to RACE Programming: Pit Wall and Pit Crew roles, Stints that end in a production deploy. Your other teams stay on Scrum until the pilot proves the cadence.
What happens after I send the form?
The FLS CTO team replies and books a 30-minute call. After the call you get a free written Adoption Baseline: seats, spend, practice, gaps.
The agent licenses are already paid for. An agentic SDLC is what makes them pay back.
Book a Discovery Call
- Thirty minutes with the FLS CTO team, the engineers who built RACE Programming and would run your program. Not a sales call. Bring your admin console numbers from Claude Code or Codex: we tell you whether a program is worth it, and after the call we send a free written Adoption Baseline: seats, spend, practice, gaps.