Agentic Team Setup & Training
We set up structured agentic workflows on Anthropic, OpenAI, or Gemini — then train your developers to build, test, and deploy with semi- and fully autonomous AI systems.
Scaffolding for Safety
Wrap before you touch
Decomposition with AI
Monolith → bounded domains
Test Harnesses
Every change verified
AI Genius Teams
Senior devs × AI agents
Project Visibility
Real-time, always
Scaffolding for Safety
Wrap before you touch
Decomposition with AI
Monolith → bounded domains
Test Harnesses
Every change verified
AI Genius Teams
Senior devs × AI agents
Project Visibility
Real-time, always
Scaffolding for Safety
Wrap before you touch
Decomposition with AI
Monolith → bounded domains
Test Harnesses
Every change verified
AI Genius Teams
Senior devs × AI agents
Project Visibility
Real-time, always
Iftherateofchangeontheoutsideexceedstherateofchangeontheinside,theendisnear.
— Jack Welch
We embed with your dev team for 4 weeks. Week 1: assess your workflows and pick the right LLMs. Week 2: build the agentic pipelines on your real codebase. Week 3: your team runs them on production work with us coaching. Week 4: self-improvement systems, handoff, and your team is autonomous.
Your developers learn to orchestrate AI agents that generate, review, and refine code through structured workflows — writing specs, not typing every line.
Agent pipelines that generate test suites, run adversarial edge cases, and self-heal when tests fail. Your QA capacity scales without adding headcount.
CI/CD automation, deployment agents that monitor and rollback, infrastructure-as-code generated by agents — with human gates where they matter.
Every failure teaches the system. Agents log decisions, analyze patterns, and auto-adjust — CMM-5 process improvement, but it runs itself.
Your team doesn't need to be replaced. They need to be upgraded. Here's what changes after 4 weeks with us.
CODING THROUGHPUT
Each developer goes from writing code line-by-line to orchestrating agents that generate, test, and refine in parallel. Same people, radically more output — with better test coverage than they had before.
DEPLOYMENT CYCLE
Manual deploys, flaky pipelines, and Friday afternoon rollbacks become a thing of the past. Agent-powered CI/CD monitors, validates, and deploys with human approval at the gates that matter.
CONTINUOUS IMPROVEMENT
The feedback system learns from every test failure, code review, and production incident. Agent behavior auto-adjusts. Your workflow gets better every week without anyone configuring it.
Yes — because they're not learning AI research. They're learning to use tools that already work. We've structured the engagement so your team is running real agentic workflows on their own codebase by week 2. By week 4, they're autonomous. The hardest part isn't the technology — it's unlearning the old way of working.
Copilot is autocomplete — it suggests the next line. Agentic workflows are autonomous systems that take a spec, decompose it into tasks, generate code, run tests, fix failures, and submit reviewed PRs. It's the difference between a spell-checker and a team of junior developers who never sleep, managed by your seniors.
You won't, because we help you choose. We assess your stack, your workflows, and your constraints — then set up the right model for each task. Most teams end up using Anthropic for deep reasoning and code review, OpenAI for breadth and tool use, and Gemini for multimodal tasks. The architecture is model-agnostic so you can swap later.
If your question isn't here, the feasibility review will cover it — with specifics for your codebase, not generics.
It depends on the work. Anthropic (Claude) excels at deep code reasoning and long-context analysis. OpenAI (GPT) has the broadest tool ecosystem. Gemini handles multimodal tasks well. Most teams end up using two. We help you pick the right model for each workflow and set up the integrations.
No. If they can write code and use a CLI, they can run agentic workflows. We teach them prompt engineering, agent orchestration, and workflow design from scratch. The goal is to make your existing developers dramatically more productive — not to hire new ones.
Copilot is autocomplete. Agentic workflows are autonomous systems that take a spec, decompose it into tasks, write the code, run the tests, fix the failures, and submit a reviewed PR — with your developers overseeing the process, not typing every line. It’s the difference between a spell-checker and a ghostwriter.
As autonomous as you want. We build in graduated autonomy — start with human approval at every step, then progressively remove gates as the team builds confidence. Some clients run fully autonomous test generation and CI/CD within weeks. Code generation typically stays human-in-the-loop.
Agents log every decision, test failure, and code review outcome. A feedback loop analyzes patterns — which prompts produce bugs, which specs are ambiguous, which test gaps keep recurring — and automatically adjusts agent behavior. It’s CMM-5 process improvement, but automated.
Final Step
A team assessment takes one call. We'll map your current workflow, identify the highest-leverage automation points, and show you what the engagement looks like.