Rollout Playbook

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Rollout Process

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0. Planning the rollout

After having the set up with leadership buy-in, the AI owner (and team) plan the rollout. Before starting, it makes sense to have a rough plan of measures and initiatives to educate users. On this page, you can find a rollout process example.

We recommend to prepare the following items:

• Add your logo, security hints and custom links to the platform

• Set up SSO

• Fill the prompt library and assistant library with suitable use cases

• Set up a shared channel with your users and the Langdock team

• Plan the following meetings and invite your users

• Choose pilot participants

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1. Exploration and first use cases

Now we can onboard users to the platform. This moment will create momentum and ascitement we should use to organically adopt the tool and find use cases (bottom-up). To utilize this, we have the following rollout steps:

1. Week: Kickoff (45-60 min)

• Initial meeting to get to know the Langdock team and the platform

• Q&A and understand the next steps

• First 1-2 company-specific use cases

• Users are added into a shared Slack/Teams channel

2. Week: Deep Dive - Prompt Engineering (45-60 min)

• Input from the Langdock team about prompt engineering

• 1-2 company-specific use cases from users

• Q&A and sharing learnings

3. Week: Deep Dive - How to build an assistant (45-60 min)

• Input from the Langdock team about assistants

• 1-2 company-specific use cases from users

• Q&A and sharing learnings

4. Week: Check-In

• 1-2 company-specific use cases from users

• Q&A and sharing learnings

• Higher focus on use cases than in sessions before

In parallel, the Langdock team is available for 1:1 sessions for individual questions, ideas, to build a use case / assistant together etc.

At this point, you will have some champions - ideally 1-2 in each department. They are very excited about AI, know how to prompt and how to build use cases. They are the ones who will educate and excite others. Now it is important to keep the momentum by keeping a regular exchange and diving into attractive use cases.

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3. Building out more use cases

After the first phase, we can onboard more users and build more use cases. The more AI champions you have, the easier is the next phase where you find and build out use cases. You will have some examples already, but should also encourage users to find their use cases organically. Below is a framework to do this. You can find more details here.

Group Session - Defining Use Cases (45-60 min)

• Collect 5 tasks that are repetitive and time consuming

• Prioritize based on impact and feasibility

• Get started with 1-2 individual use cases

Group Session(s) - Check-In after 1-2 weeks (45-60 min)

• Sharing learnings

• Checking on use cases: What worked, what did not work, how did users build the use cases?

In the first session, everyone finds use cases that would help in daily work. After the session, everybody has time to experiment and try to build the use cases. It makes sense to check in with users and ask if they need help in this phase. After 1-2 weeks, you can meet again and share learnings and check in how the use cases were built.

You will still have input on the previous topics like prompting or building assistants to help everyone here.

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4. Grow sustainably

Over time, users will organically build assistants, share prompts and use Langdock more and more. You should keep doing what you were doing to roll out Langdock. Continue doing workshops, helping users individually and maintaining the momentum of AI. At the bottom, you find all measures we have collected to roll AI out.

Also, you can slowly integrate other tools and work on higher-effort tasks. This includes:

• Search integrations to read information from other tools,

• Assistant actions to read, update and create data in other tools,

• Using the API to access Langdock from other tools and

• Agents for building highly individualized workflows.

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General measures

You don’t have to do all of these initiatives, but some of these measures might help to keep momentum. These initiatives will and should also evolve over time.

• Hackathons or Promptathons - have one day where teams of 4-5 people have the time to work on any problem they want to and use AI to find/build a solution

• 30 day AI challenge - have one small task with AI everyday. This helps to learn in a gamified way as well as get used to include AI in daily work.

• AI newsletter - start a newsletter about current developments in AI, internal success stories and tips and tricks.

• Write sticky notes to be put on screen “Use Langdock” to remind yourself to think how to improve daily tasks and work on them differently.

• Share small tricks and knowledge bites 1-2 times a week (max 2 sentences, easy and fast to try it out and learn).

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How does a good rollout look like

• People are sharing their use cases and learnings

• A lot of people book 1:1s

• Users have many questions in check-ins

• The user base creates pull; they want more content, are eager to learn and proactively build use cases

• Celebrate successes to keep momentum and motivation

• Admins and leadership communicate clear goals and motivation

• Good KPIs: Growing number of active users and an increasing number of prompts being sent.

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What to avoid

• Don’t try to build many use cases at once. Focus on 1-2 first and adopt them first.

• Don’t overengineer a rollout. Just get started and see what works. Then adapt based on what works and what does not.