Adoption & Training

Make your whole team AI-native, and keep them there

Buying AI tools is easy. Getting a whole team to actually work the AI-native way is the hard part. Runwork's adoption layer scores where each person stands, shows them what to learn next, and nudges them forward week after week, so adoption becomes a habit, not a one-time announcement.

My Journey

Your score: 71 team avg 58

Setup

Usage

Building

Knowledge

Your capability map

Mastered Ready next Upcoming

Active in AIUse a skillConnect an integrationHand off a conversationCreate a skillBuild a workflowBuild an appModel dataExpose an endpoint

What's next for you

Create your first skill
Build a workflow

Fading: give it a refresh

You connected an integration 2 months ago and haven't since. A quick reconnect keeps the skill fresh.

Marcus T. leads the team on Building. A good person to ask.

Updated just now · /journey

What Adoption & Training gives you

My Journey: a personal adoption dashboard

Every member gets their own page showing where they stand with AI: an overall score plus a breakdown across Setup, Usage, Building, and Knowledge, always compared against the team average so progress feels real.

Capability map

A visual graph of every capability: green for what you've mastered, amber for what you're ready to learn next, and gray for what's still ahead. It turns "get good at AI" into a concrete, walkable path.

Skill-decay nudges

Mastery isn't forever. Capabilities you haven't exercised in a while fade, and guidance resurfaces them for a refresh. Adoption reflects what your team can do today, not what they did once, six months ago.

Next-best-step guidance

Instead of a generic checklist, Runwork surfaces the one thing that's just beyond your current reach: the step that actually moves you forward, drawn from a catalog of guidance tuned to your role.

Weekly training emails

Each member gets a personalized weekly nudge toward their next best step. Admins see exactly how each piece of guidance performs: who it reached, who clicked, and who was emailed.

Guidance everywhere they work

Smart empty states, next-step cards, and celebration moments appear right where the work happens: across the web app, desktop app, CLI, and even inside MCP. Teaching meets people in the moment, not in a manual.

Persona-aware paths

An operations teammate and an engineer have different definitions of "fully adopted." Everyday, curious, and engineer personas each get their own target path, so nobody is pushed toward capabilities they'll never need.

Team champions

See who on your team leads each area, so when someone needs help they know exactly who to ask. Knowledge spreads peer-to-peer, instead of waiting to trickle down from the top.

runwork reflect

A weekly, privacy-safe reflection on your own AI work patterns. It analyzes how you actually work, from your own messages and tool usage, never assistant output, and points out capabilities you're not using yet.

Access from anywhere

AI Agents

Ask your AI agent:

Connect your AI agent

Desktop & Web

Runwork Desktop

Your AI Tools 13 detected

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Claude Code

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+10 more

Your Team's Skills 39 shared

press-release-lead-monitor

dtp-demand-tracker

Your Integrations 18 connected

HubSpot Sheets lemlist +15

Open My Journey at /journey to see your capability map, score, and next steps. Admins open the Training tab in the Team Dashboard at /team.

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CLI

Why Adoption & Training matters

Nobody else turns AI adoption into a guided, personal journey
Decay-aware scoring measures current fluency, not lifetime history
Guidance meets people where they work: web, desktop, CLI, MCP
Persona-aware: the right path for operators and engineers alike
Weekly nudges make adoption a habit, not a launch-day event
Grounded in real learning science, not gamified vanity points

How Adoption & Training works

Honest measurement

Runwork watches what each person actually does (connect an integration, use a skill, build an app) and scores it across Setup, Usage, Building, and Knowledge. No surveys.

Mastery that decays

Skills you haven't used in a while fade, like real memory. The score reflects current fluency, not a résumé of things done once.

The next right thing

From what you've mastered, Runwork finds your frontier: the capabilities you're ready for next, and surfaces exactly those.

Where you work

Guidance shows up as hints, next-step cards, and a weekly email, across the web app, desktop, CLI, and MCP.

Frequently Asked Questions

How is this different from the Team Dashboard?

The Team Dashboard is the admin's view of the whole team. Adoption & Training is the layer underneath it: the personal "My Journey" experience for each member, the capability map, the decay model, and the guidance and weekly emails that actually move people forward. The Training tab in the Team Dashboard is where admins watch it all work.

Is the scoring just gamification?

No. Scores come from real activity, not points for logging in, and mastery decays when capabilities go unused, so the number reflects current fluency. The selection of what to teach next is grounded in established learning theory (retention curves and the zone of proximal development), not a leaderboard.

Does everyone get pushed toward the same skills?

No. Personas (everyday, curious, and engineer) each define their own "fully adopted." An operations teammate can reach 100% without ever building an app, because that's genuinely complete for their role.

Is runwork reflect private?

Yes. Reflection runs on a privacy-safe digest of your own activity: your messages, tool taxonomy, and skill usage. Assistant output and tool results are dropped before analysis. It surfaces patterns you can't see yourself, not a transcript of your work.

Who can see my journey and my score?

You see your own My Journey page in full. Workspace admins see team-level mastery and trends to know where to help. Team champions are surfaced so people know who to ask. Adoption is meant to be collaborative, not a ranking.

Use Cases

AI adoption that sticks Onboarding new hires to AI-native work Upskilling non-technical teammates Spotting who has stalled, and why Keeping skills fresh as the platform grows

Related Features

Team Dashboard Desktop App Skills AI Agents CLI

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Team Collaboration AI Ecosystem

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