Company-wide AI training
- Mandatory sessions delivered across global time zones
- When to reach for Claude vs ChatGPT vs Copilot, and how to prompt well
- Pre/post surveys and attendance tracking for concrete adoption data
AI Training & Upskilling
AI adoption you can measure
You have an AI mandate — and someone accountable for proving it worked. We deliver the training, the hands-on engineering track, and the metrics that make adoption real and provable.
What We Deliver
Three programs that work together
AI-native engineering track
- 6–8 weeks of weekly hands-on sessions on real codebases
- Agentic coding, reusable skills, and MCP workflows
- Stability and change-failure rate measured alongside throughput
Measurement and governance
- Usage baseline, license consolidation, and a 60-day metrics report
- AI acceptable-use policy and responsible-use guardrails
- An early high-ROI automation that visibly pays for the program
Per-Team Workshops
Built on each team’s real workflows
Workshops are scoped with team leads beforehand and run hands-on against one real workflow — not a generic AI introduction. From recent engagements:
GTM: sales, marketing & RevOps
AI wired into the CRM and daily revenue workflow — e.g. Claude connected to Salesforce to automate repetitive RevOps tasks, marketing content workflows, account research.
Finance
Invoice processing and routing, vendor payment review, inbox classification, month-end close automation, dashboards, and a finance Q&A bot the team keeps extending.
Product & R&D
Competitive analysis, content and user-data analysis, generating SQL and scripts to answer data questions without waiting on engineering, custom assistants over internal docs.
Operations & delivery
Automating repetitive operational tasks, connecting the systems teams already use, documentation workflows, and delivery handoffs.
In Practice
A recent engagement
An operations executive at a PE-backed cybersecurity company was handed a company-wide "AI-first" mandate. We reached the full ~300-person organization with mandatory training across time zones, ran the 6–8-week engineering track, consolidated the license landscape, and established an AI acceptable-use policy. A baseline plus a 60-day metrics report made the ROI story legible to the PE owners.
Why Node8
Taught by people who ship AI for a living
Practitioners, not presenters
The people running the sessions build production AI systems — MCP connectors, GTM automation, agent workflows. Training draws on real codebases, not generic slides.
400+ leaders trained
Beginner-to-advanced workshops across technology organizations, including leaders from Google, OpenAI, and Amazon.
Measurement built in
Baselines, surveys, usage and token metrics, and a 60-day report — designed for the executive who has to prove adoption to a board or PE owner.
FAQ
Questions from executives and engineering leaders
What does company-wide AI training cover?
How to use AI effectively in day-to-day work: choosing between Claude, ChatGPT, and Copilot, prompting and workflow best practices, and hands-on department workshops built on each team’s real workflows — delivered in multiple sessions to cover global time zones.
How do you measure AI adoption?
Pre- and post-session surveys, attendance tracking, usage baselines, and a 60-day metrics report. For engineering, the program measures stability and change-failure rate alongside throughput, so velocity gains don’t hide quality regressions.
Doesn’t more AI-generated code mean more bugs?
It can, if adoption is unmanaged. The engineering program deliberately tracks code-quality metrics next to velocity, and teaches review habits for AI-authored code — essential for any organization where software quality is non-negotiable.
What is the AI-native engineering track?
A structured 6–8-week program that moves engineers from treating AI as autocomplete to delegating scoped work to it: weekly hands-on working sessions on real codebases, office hours, between-session assignments, starter workflow assets, and an adoption playbook the team keeps.
Who runs the training?
Node8 practitioners who build AI systems in production. We have run beginner-to-advanced AI workshops for 400+ leaders across technology organizations.
Have a mandate to make AI adoption real?
Tell us where your organization stands and we will map the training, metrics, and governance to get adoption you can prove.