Training for every team.
AI is not just for engineers. Every team in your organization has work that AI can improve. The key is training that's specific to their actual tasks, not generic AI overviews that leave people wondering how to apply it.
Engineering Teams
The challenge
Your developers are using AI inconsistently. Some love Copilot, some tried Cursor once and went back to their old workflow. Nobody has a shared approach to AI-assisted development, and code quality from AI suggestions varies wildly.
What we cover
- -Cursor workflows: AI pair programming, multi-file edits, and codebase-aware prompting
- -Claude Code for terminal-based development and complex refactoring
- -GitHub Copilot patterns that actually produce good code
- -AI-assisted code review, testing, and debugging
- -When to trust AI suggestions and when to override them
- -Security review of AI-generated code
The outcome
Your engineering team writes better code faster, with consistent AI workflows and shared best practices. Fewer bugs from AI suggestions because they know what to watch for.
Product Teams
The challenge
Product managers and designers spend hours on research, synthesis, and documentation. AI could cut that time in half, but generic prompt tips from Twitter don't translate to real product work.
What we cover
- -User research synthesis and interview analysis with AI
- -PRD drafting and specification writing
- -Competitive intelligence and market research automation
- -Feature prioritization frameworks with AI support
- -Customer feedback analysis at scale
- -Presentation and stakeholder communication preparation
The outcome
Product decisions get made faster. Research that took a week takes two days. Documentation goes from dreaded to done in an afternoon.
Marketing Teams
The challenge
Your marketing team is using ChatGPT to write content, and it shows. Generic AI content is everywhere. You need AI that speeds up the work without making everything sound the same.
What we cover
- -Brand voice training for AI tools (so output sounds like your brand, not generic AI)
- -Content ideation and research workflows
- -Copy variation testing and A/B draft generation
- -SEO content optimization with AI assistance
- -Social media content pipelines
- -Campaign planning and audience research automation
The outcome
Marketing output doubles without doubling headcount. Content sounds like your brand. AI becomes a tool that amplifies creativity instead of replacing it.
Operations Teams
The challenge
Operations runs on repetitive tasks: report generation, data entry, status updates, email triage. These are exactly the tasks AI handles well, but nobody has set up the workflows.
What we cover
- -Process mapping and automation opportunity identification
- -Report generation and dashboard automation
- -Email triage and communication workflows
- -Data entry and extraction automation
- -Vendor communication and procurement support
- -Zapier/Make.com integration with AI steps
The outcome
Hours of repetitive work per week get automated. Your operations team focuses on decisions and improvements instead of manual data wrangling.
Leadership and Executives
The challenge
You keep hearing that AI will change everything. Vendors pitch you constantly. Your teams are asking for tools and budget. You need to make informed decisions, not guesses.
What we cover
- -Strategic AI literacy: what AI can and cannot do today (not hype, reality)
- -ROI framework for evaluating AI initiatives
- -Vendor and tool evaluation criteria
- -Building an AI adoption roadmap for your organization
- -Managing AI risks: security, compliance, and quality
- -Setting realistic expectations and timelines
The outcome
You make AI investment decisions based on understanding, not vendor pitches. You know which initiatives will deliver ROI and which are distractions.
Non-Technical Teams
The challenge
HR, legal, finance, customer support. These teams hear about AI but assume it's for developers. It's not. Most of the biggest productivity gains from AI come from non-technical workflows.
What we cover
- -AI fundamentals: what these tools actually are and how they work
- -Document processing: contracts, policies, reports, summaries
- -Communication assistance: email drafting, meeting preparation, follow-ups
- -Data analysis without code: natural language data questions
- -Customer and client communication templates
- -Privacy and compliance: what to share with AI and what not to
The outcome
Non-technical team members become confident AI users. Tasks that took hours happen in minutes. The entire organization benefits, not just the engineering department.
Don't see your team?
We customize training for any team type. If your people do work, AI can probably help them do it better. Let's talk about what that looks like.
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