Agents Can't Verify Their Work
No tests, no CI feedback loops. Your AI agent writes code it can never validate. Every change is a coin flip.
84% of developers use AI coding tools. Only 11% of organizations have agents in production. The problem isn't the AI — it's the codebase. Get your Nerva Score™ and find out exactly what to fix.
You bought Copilot licenses. You tried coding agents. But nothing sticks — because the infrastructure your agents need doesn't exist yet.
No tests, no CI feedback loops. Your AI agent writes code it can never validate. Every change is a coin flip.
No AGENTS.md, no API docs, no architecture diagrams. The agent guesses at your codebase conventions — and guesses wrong.
Only 29% of developers trust AI code accuracy — down from 40%. Without infrastructure-backed trust, adoption dies.
AI coding agents are only as effective as the infrastructure surrounding the repository. A codebase without tests, CI/CD, documentation, and observability makes AI agents useless.
We don't fix your AI. We get into your repos and build the infrastructure so agents can actually work.
81 criteria. 9 pillars. 5 maturity levels. A rigorous assessment that tells you exactly where your repos stand — and what to fix to make AI agents actually work.
Basic version control. Some formatters and linters. Agent can read code but cannot verify its own changes.
Basic CI/CD and testing in place. Agent can fix straightforward bugs with rapid CI feedback.
Production-ready for agents. Agent can fix bugs, add tests, update docs, implement clearly-specified features. This is where ROI starts.
Comprehensive automation and metrics. Agent can execute multi-file refactors, optimize performance, harden security.
Full autonomous capability. Agent can develop complete features, respond to incidents, triage work autonomously.
Every pillar represents a critical feedback loop your AI agents need to function. Miss one, and the whole system breaks down.
Formatters, linters, type checkers, pre-commit hooks, complexity analysis
CI/CD pipelines, release automation, deployment frequency, build caching
Unit tests, integration/E2E, coverage thresholds, flaky test detection
README, AGENTS.md, API schemas, architecture diagrams, freshness checks
Env templates, devcontainers, database migrations, local service setup
Structured logging, error tracking, distributed tracing, alerting, runbooks
Secrets management, branch protection, dependency scanning, DAST
Issue templates, labeling systems, PR templates, backlog health
Error-to-insight pipelines, product analytics instrumentation
We don't hand you a report and walk away. We embed in your team and do the work.
We scan your repositories against 81 criteria across all 9 pillars. You get your L1–L5 Nerva Score with every gap identified — for free.
We build a prioritized transformation roadmap: which pillars to fix first, what agents to deploy, what L3 looks like for your stack and team.
We embed in your team and do the work. Set up CI/CD, write test infrastructure, configure agents, create docs, harden security — hands-on, in your repos.
AI agents are live and working. We train your team, measure the score delta, and expand to more repos. You see the ROI in weeks, not quarters.
This isn't a slide deck engagement. Our consultants are in your codebase, day-to-day, making AI agents work.
Configure Claude Code, Copilot, Cursor, or OpenHands to work with your specific repos, conventions, and workflows.
Build fast feedback loops so agents can verify their own work. Agents that can't test are agents that can't ship.
Write the test suites, coverage gates, and flaky-test detection that let agents make changes with confidence.
Create AGENTS.md, architecture docs, and contributing guides so agents understand your codebase — not guess at it.
Secrets management, branch protection, structured logging, error tracking — the infrastructure agents need to operate safely.
Train your engineers to work alongside AI agents. New workflows, new review processes, new ways of thinking about code.
Adoption is universal. But adoption without infrastructure is just expensive experimentation.
The gap between "using Copilot" and "agents shipping features" is the infrastructure gap. That's what we close.
AI projects that never reach production. Not because the AI failed — because the codebase wasn't ready.
At L3, AI agents can fix bugs, add tests, and implement features autonomously. Most repos are L1. We get you to L3.
You're under pressure to prove AI productivity gains. Get a board-ready score that shows exactly where you stand and what the path to ROI looks like.
Your board wants an AI strategy. Give them a maturity framework they understand: L1 today, L3 in 12 weeks, with measurable criteria at every step.
Stop the ad-hoc "some teams use Copilot" approach. Get a systematic assessment across all repos and a clear transformation playbook.
Start with a free Nerva Score™ assessment. Then we embed in your team and make the transition happen — agents writing code, running tests, and shipping features.