A guide to teaching AI how your business actually works. Written for teams, not developers.
Your team’s been trained on AI. They know how to write prompts. They’ve built workflows. Good.
But here’s what happens next: every time someone opens a new conversation with their AI — Claude, Codex, whatever tool they’re using — they start from zero. They re-explain the brand guidelines. They re-type the same setup instructions they typed yesterday.
It works. But each conversation still starts at zero.
We’ve watched this pattern across the organizations we’ve trained. The initial excitement lands. People get good at prompting. Then a few weeks in, the best AI users on the team are spending too much of their time just re-establishing context.
The best prompts your team writes today disappear the moment the conversation ends.
A skill is a set of instructions that teaches your AI how to handle a specific task or workflow. You write it once. It applies the instructions every time.
Think of it this way. Right now, every time you start a new AI conversation — whether it’s Claude, Codex, or another tool — you’re talking to someone capable on their first day at your company. They can do anything you ask. But they don’t know your processes, your preferences, or your quality standards. You have to explain all of it, every time.
A skill is the onboarding manual and the SOPs. It’s the stuff that turns a capable generalist into someone who knows how your business works.
Here’s a useful way to think about it. If you connect your AI to your tools through something called MCP, that gives it access to the kitchen. The equipment, the ingredients, the appliances. But access to a kitchen doesn’t make someone a chef. Skills are the recipes. They tell the AI what to make and how to make it.
Most of the time, you don’t need to understand the kitchen part. You just need the recipes.
Technically, a skill is just a folder with a markdown file inside it. That file contains instructions written in plain language. Both Claude and Codex can read those instructions and follow them. No code required. No integrations to configure. Just clear directions.
You open Claude or Codex. You type:
You do this every time. Or you keep a Google Doc of setup instructions and paste them in. Some people know about the doc. Some don’t. Results vary.
You open Claude or Codex. You type:
The skill already knows your brand voice, your audience, your formatting preferences, and your quality checklist. It writes to spec on the first try. Everyone on the team gets the same result.
That’s the difference. The context that used to live in someone’s head now lives somewhere your AI can access automatically.
A marketing coordinator who joined last month produces content that matches your brand voice on day one. A finance team that runs the same quarterly report doesn’t re-explain the format every time. An operations manager who built a great vendor evaluation process can share it with the whole team.
From what we’ve seen with clients and our own team, skills fall into three categories.
Skills that produce consistent, high-quality output. A blog post skill that knows your brand guide. A proposal template that follows your structure every time. A job description generator that matches your tone. The most common starting point. Easiest to test because you can see the output and compare it to what you’d write yourself.
Skills that handle multi-step processes. A new client onboarding skill that creates the project folder, drafts the welcome email, builds the timeline, and generates the kickoff agenda. Save more time than document skills, but take more thought to design. You need to understand the workflow before you can teach it.
Skills that encode your team’s specialized knowledge. Your head of compliance knows which regulations apply to which scenarios. Your best salesperson knows exactly what questions to ask in discovery. That knowledge lives in their heads. A skill puts it somewhere the rest of the team can use it. When that expert is on vacation, the skill still works.
Everyone prompts differently. Skills make the output consistent without making everyone prompt the same way.
Setup time for repeated tasks drops to near zero. Your team spends AI time on actual work, not preamble.
People leave, get promoted, take vacations. Skills capture knowledge in a format that’s immediately usable.
Not everyone is a power user. A well-built skill turns “figure out the prompt” into “type what you need.”
Skills aren’t one-size-fits-all. Here’s what they look like in practice.
Content briefs that match your format. SEO checks against your checklist. Social media that adapts long-form into platform-specific posts while keeping voice consistent.
Vendor evaluation that scores proposals against weighted criteria. Process documentation from conversations into formatted SOPs. Reporting in the format leadership expects.
Job descriptions matching tone with required legal language. First-week onboarding plans tailored to role. Policy updates from plain language to formal documentation.
Expense review flagging out-of-policy items. Budget summaries in your CFO’s preferred template. Variance analysis comparing actuals to forecasts with narration.
Prospect research briefings from public sources. Proposals mapping client needs to your service catalog. Follow-up emails that know your voice and cadence.
Meeting prep that pulls context from previous notes. Decision briefs that structure complex choices. Quarterly reviews compiled in your preferred format.
Here’s how AI adoption usually goes.
Your team learns the tools. People get excited. Some get really good at prompting. Others use it occasionally.
People who got good keep using it. The rest don’t. The gap between your best AI users and everyone else widens.
You take what your best people figured out and make it available to everyone. The gap narrows. The whole team moves up.
Skills are Phase 3. They’re how what one person figured out becomes available to the whole team. And they’re how you stop depending on a few power users to carry everyone else.
If you’ve already invested in training, skills are the natural next step. Not because they’re expensive. Because they multiply the value of the investment you already made.
Training teaches your team to use AI. Skills capture what they learn so everyone else can use it too.
We’ve built skills for content creation, workflow automation, compliance review, and other use cases. Here’s how it works.
We sit down with the people who actually do the work. Not the people who describe the work in slide decks. The people who live inside the process every day. We document what they do, step by step, including the judgment calls and the exceptions.
We decide what goes into the skill and what stays out. A good skill is focused. It does one thing well. We define what triggers the skill, what the AI should do, and how we’ll know it’s working.
We write the skill, test it against real scenarios, and iterate. Most skills go through 3–5 rounds of refinement before they consistently produce good output. This takes days, not months.
We install the skill for your team, show them how to use it, and document any nuances. Then we watch it in production for a few weeks to catch edge cases.
Skills are living documents. When your processes or tools change, we update the skill. One that never gets updated eventually works against you.
