01 · DISCOVERY
Signal in. Spec out.
AI-augmented customer research and synthesis. Evaluatable specs replace narrative product docs.
- Ticket-pattern mining
- Spec-as-prompt
- Evaluation criteria
AI Software Development Lifecycle · Fixed-bid · Compliance-grade
AI SDLC Practice.
We rebuild your software development lifecycle for the AI era — discovery, design, build, ship, and operate — wired for AI-first workflows that compound. Delivered as fixed-bid AI Readiness Blocks.
Built around AI Readiness Blocks · Fixed-bid · Measurable per block · HIPAA · HITRUST · SOC 2
01 — Why SDLC needs rebuilding
Your SDLC was designed before AI. It shows.
AI editors collapsed the cost of producing code. They did not collapse the cost of reviewing it, validating it, integrating it, or supporting it once it ships. So the bottleneck moved — from code creation to everything around code creation — and most engineering organizations are running a workflow built for a problem that no longer exists. Our AI SDLC Practice rebuilds each stage of the lifecycle for the new constraint: production is cheap, validation is the work.
02 — The five-stage rework
Discovery. Design. Build. Ship. Operate.
We rework each stage so AI tools and agents are first-class participants — and so the quality system catches up with the speed of code production.
02 · DESIGN
Design for simulation.
Design docs are written so a simulator can check them. Architecture decisions are tied to measurable surfaces.
- Sim-checkable specs
- Decision logs
- Eval-aware patterns
03 · BUILD
Agentic delivery.
Claude Code, Cursor, and custom agents handle obvious code. Engineers handle judgment.
- Claude Code rollout
- Custom integrations
- Agent toolchains
04 · SHIP
Pre-merge simulation.
CodeSim runs on every PR and gates the top regression-prone surfaces. AI-generated PRs are safe to merge.
- CodeSim in CI
- Block-on-regression policies
- Gated rollouts
05 · OPERATE
Tickets to code.
Customer reports route to the failing path. Cowork handles non-engineering grind. Feedback loops back into discovery.
- PlayerZero routing
- Agentic ops (Cowork)
- Closed-loop feedback
03 — How we deliver
Fixed-bid AI Readiness Blocks.
Every engagement decomposes into 2–6-week blocks. Each block has a defined deliverable, a fixed price, and a measurable outcome. Blocks compound: each one permanently reduces the cost of the previous surface area. No time-and-materials drift, no pilots that go nowhere.
Block type · Build
Claude Code rollout for a team.
Stand up Claude Code across one engineering team with a tailored skill pack and operating rituals so the tool ships value in week one.
Block type · Ship
Pre-merge regression gates.
Wire CodeSim into CI for the five surfaces that produce the most regressions. Each becomes a hard pre-merge gate, so AI-generated PRs can't reach production without passing simulation.
Block type · Operate
PlayerZero + ticket routing.
Deploy PlayerZero, wire CodeSim into CI, route Zendesk/Intercom/Linear tickets to the exact failing line of code.
Block type · Operate
Agentic ops for a team.
Cowork plus a custom agent toolchain absorbs reporting, file ops, vendor follow-ups, and the rest of the non-engineering grind that eats a team's week.
Block type · Design
Spec-as-prompt rework.
Rewrite a product surface's specs so they're simulation-checkable. Tie design decisions to measurable outcomes.
Block type · Discovery
Ticket-pattern mining.
Mine the support backlog with PlayerZero traces to surface the top 10 ticket shapes — and which design choices keep producing them.
Beyond fixed-bid blocks, we also run extended engagements where our practicing offshore team is fully embedded with the customer as a long-term partner — same operating model, scoped over quarters and years rather than weeks.
04 — A sample 90-day roadmap
What an engagement looks like.
Roughly typical. Every roadmap is scoped to the actual surface area we're working with.
Day 0–14
Assess the system.
Full access to your engineering system — codebase, workflows, incident history. We map exactly where maintenance spend is trapped, where AI will move the needle fastest, and where the compliance perimeter is. Output: a prioritized block roadmap with fixed pricing.
Day 14–30
Block one ships.
Typically a foundational block — Claude Code rollout for one team, or pre-merge CodeSim gates on the top three surfaces. End of block 1, the team has a tool they actually use and a metric that visibly moved.
Day 30–60
Block two compounds on block one.
Usually PlayerZero + ticket routing. The block-one investment becomes more valuable as the operate stage closes the loop. Incidents resolve faster. AI-generated PRs become safer to merge.
Day 60–90
Block three. Then we step back.
Agentic ops or a build block, depending on where leverage is biggest now. By the end of 90 days, three blocks are in operation and the team owns the workflows — we stay on for office hours, not for ongoing dependency.
05 — FAQ
Common questions.
What is an AI SDLC Practice?
An AI SDLC Practice is the discipline of redesigning each stage of your software development lifecycle — discovery, design, build, ship, and operate — so that AI tools, agents, and evaluation systems are first-class participants rather than bolted-on assistants. Done right, it shifts the bottleneck off code production and onto validation, where AI quality systems like PlayerZero do the heavy lifting.
How is this different from generic AI consulting?
Generic AI consulting tends to focus on point tools or proofs of concept. An AI SDLC Practice works at the lifecycle level — the workflows, gates, evaluation systems, and operating habits that determine whether AI compounds or stalls. We deliver durable practice change, not pilots — because we're a practicing engineering company, not a consultancy.
How are AI Readiness Blocks priced?
Each block is fixed-bid with a defined deliverable, a measurable outcome, and a 2-to-6-week timeline. We share the full block roadmap and pricing before any work begins — no time-and-materials drift, no surprise invoices.
Do you require specific tools?
We're opinionated about three tools that earn their place almost every time — PlayerZero, Claude Code, and Cowork. Beyond that we're tool-agnostic and compose the rest of the stack to fit the job (Cursor, Linear, custom integrations, and so on).
Will this replace our engineers?
No. We build the system that makes your engineers more leveraged. AI handles the production of obvious code and the simulation of changes; engineers focus on judgment, architecture, and the work AI is bad at. Onboarding and seniority both compound faster.
Do you work in regulated industries?
Yes. HIPAA, HITRUST, and SOC 2 environments are our baseline. Data residency and access boundaries are scoped before any work begins, and we operate inside your existing compliance perimeter rather than around it.
What outcomes should we expect?
Typical engagements have shown ~50% reductions in maintenance overhead, 60%+ faster incident resolution, and 4× faster engineer onboarding to first ship. Specifics depend on the codebase and the block roadmap.
How long does an engagement run?
Engagements start at 4 weeks (single block) and run up to roughly six months (full SDLC rework). Most clients run three to five blocks across 90–180 days.