Your engineers are faster with AI. Your roadmap has not moved the same way. Stride installs the engineering discipline behind AI-assisted engineering, then ships production code alongside your team. It starts with a workshop run live on a real codebase, not a slide deck.
Reserve the WorkshopStride engineers have been trusted by teams at CLEAR, Betterment, Jane Street, National Grid, and One Health Link.
90% of organizations have adopted AI in their software development (DORA 2025). Adoption stopped being the question. Value creation is the question now.
Individual engineers feel faster. Delivery does not follow. As AI adoption rises, instability often rises with it, and duplicated code blocks have grown tenfold since 2020 (GitClear). Duplicate code with small variations multiplies the same bug across copies, which makes defects harder to find and slower to fix.
This is the J-curve DORA describes: a dip in productivity and stability before the returns arrive. Leaders who misread the dip as failure pull funding before the curve turns. The teams that navigate it with discipline reach the other side. Most do not.
The cause is not the models or the tools. It is the engineering discipline around them. AI writes code quickly. It does not decide what to build or hold a standard for what ships.
Stride applies its Plan-Do-Check-Act cycle to AI-assisted engineering. This is the difference between vibe coding and disciplined development with agents, and it runs on your real codebase, not a demo. The method holds engineers accountable for every line, including the code they did not write themselves.
Analyze the codebase and design the change. A human reviews and approves the plan before any code is written.
Implement test-first, in small atomic increments, with red-green discipline and a preserved git history.
Evaluate the output against the original plan. The definition of done goes past running code.
Close each cycle with a retrospective that sharpens the next one.
The discipline is measured, not assumed. The PDCA framework ships as an installable Claude skill: each phase is a structured prompt that holds the agent to codebase analysis and an approved plan before any code, test-first implementation, a completeness check against the plan, and a retrospective. A behavioral eval harness verifies the prompts hold across scenarios. A DORA metrics toolkit runs in your pipeline on every pull request and again each week, scoring commit quality, flagging large and sprawling commits, tracking test coverage and code drift, and classifying your codebase against the DORA team profiles. Adoption is easy to see. This is how your team sees delivery.
A structured PDCA cycle reduced software defects by 61% in a controlled study (Ning et al., 2010). Discipline is what converts AI speed into fewer bugs downstream.
Duplicated code blocks have grown tenfold since 2020 with undisciplined AI use (GitClear). The Do phase guards against copy-and-vary anti-patterns before they multiply.
Stride engineers ship in production, not in slide decks. A model-switching agent built for 73V automates 85 to 87% of SMS patient inquiries with human-in-the-loop clinical oversight, delivering $360K in documented annual savings.
Stride engineers work inside your team. The discipline transfers as the code ships.
The Striders on your engagement drive the agents writing the code using PDCA.
Striders and your team ship against the business outcome you own, applying PDCA on your real codebase.
Your engineers learn the method on the job, not in a classroom.
A 90-minute working session with senior Stride engineers who ship agentic systems in production.
The full PDCA workflow run live on a real codebase, so your leaders see disciplined AI-assisted engineering in motion.
A read on where your teams stand today, scored against the DORA team profiles.
A follow-up summary with recommended next steps. Yours to keep regardless of whether you engage Stride.
Built for engineering leaders. No slideware. A technical working session with engineers who build with agents for a living.
Stride forms a co-sourced team. Our engineers and yours pick a real piece of work, a feature, an agent, or a legacy system to modernize, and build it together on your production codebase. We run the full PDCA cycle in the open, every day. We ship working software, not a slide of recommendations or a prototype that stalls at the demo.
Your engineers learn by doing the work, with real feedback on quality and cost. When the engagement ends, your team owns the software and the practice that produced it, and runs the next build without us.
The workshop shows your leaders the method running live and reads where your teams stand today. The co-sourced engagement ships production software while the discipline transfers to your team.
Anthropic Claude Partner. 95+ clients. 350 engagements. 40+ agentic AI deployments.
"Stride engineers embedded with our team and built a working AI agent in weeks, not months. The system is in production handling thousands of patient interactions, and it paid for itself within 90 days."
VP of Operations, 73V Healthcare
AI-assisted engineering is the practice of using AI coding agents under explicit engineering discipline so that speed turns into delivered value rather than faster typing. Stride runs it on a Plan-Do-Check-Act cycle: a human approves the plan before any code, implementation is test-first in small increments, output is checked against the plan, and each cycle ends with a retrospective.
AI generates code quickly but does not decide what to build or hold a standard for what ships. Without discipline, teams see more duplicated code and lower delivery stability even as individuals feel faster. The discipline around the tools, not the tools themselves, is what moves the roadmap.
Engineering leaders, CTOs, VPs of Engineering, and heads of engineering whose teams have already adopted AI coding tools and are not yet seeing the delivery gains they expected.
Your real code. The 90-minute session runs the full PDCA workflow live on a real codebase and scores where your teams stand against the DORA team profiles.
If you proceed, Stride forms a co-sourced team. Our engineers and yours build a real piece of work together on your production codebase, running the full PDCA cycle daily. Your team owns the software and the practice when the engagement ends.
No. The discipline is a means to ship better software faster, taught on the job while real code ships. Disciplined engineers using AI outperform undisciplined engineers using AI.
Tell us about your team and codebase. A Stride engineer follows up within one business day to scope the session.