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1 OKR example for Large Language Models

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What are Large Language Models OKRs?

The OKR acronym stands for Objectives and Key Results. It's a goal-setting framework that was introduced at Intel by Andy Grove in the 70s, and it became popular after John Doerr introduced it to Google in the 90s. OKRs helps teams has a shared language to set ambitious goals and track progress towards them.

OKRs are quickly gaining popularity as a goal-setting framework. But, it's not always easy to know how to write your goals, especially if it's your first time using OKRs.

We've tailored a list of OKRs examples for Large Language Models to help you. You can look at any of the templates below to get some inspiration for your own goals.

If you want to learn more about the framework, you can read our OKR guide online.

The best tools for writing perfect Large Language Models OKRs

Here are 2 tools that can help you draft your OKRs in no time.

Tability AI: to generate OKRs based on a prompt

Tability AI allows you to describe your goals in a prompt, and generate a fully editable OKR template in seconds.

Watch the video below to see it in action 👇

Tability Feedback: to improve existing OKRs

You can use Tability's AI feedback to improve your OKRs if you already have existing goals.

AI feedback for OKRs in Tability

Tability will scan your OKRs and offer different suggestions to improve them. This can range from a small rewrite of a statement to make it clearer to a complete rewrite of the entire OKR.

Large Language Models OKRs examples

We've added many examples of Large Language Models Objectives and Key Results, but we did not stop there. Understanding the difference between OKRs and projects is important, so we also added examples of strategic initiatives that relate to the OKRs.

Hope you'll find this helpful!

OKRs to become an expert in large language models

  • ObjectiveBecome an expert in large language models
  • KRDemonstrate proficiency in implementing and fine-tuning large language models through practical projects
  • TaskContinuously update and optimize large language models based on feedback and results obtained
  • TaskComplete practical projects that showcase your proficiency in working with large language models
  • TaskCreate a large language model implementation plan and execute it efficiently
  • TaskIdentify areas of improvement in large language models and implement necessary fine-tuning
  • KRComplete online courses on large language models with a score of 90% or above
  • KREngage in weekly discussions or collaborations with experts in the field of large language models
  • TaskSchedule a weekly video conference with language model experts
  • TaskDocument key insights and lessons learned from each discussion or collaboration
  • TaskShare the findings and new knowledge with the team after each engagement
  • TaskPrepare a list of discussion topics to cover during the collaborations
  • KRPublish two blog posts sharing insights and lessons learned about large language models

Large Language Models OKR best practices

Generally speaking, your objectives should be ambitious yet achievable, and your key results should be measurable and time-bound (using the SMART framework can be helpful). It is also recommended to list strategic initiatives under your key results, as it'll help you avoid the common mistake of listing projects in your KRs.

Here are a couple of best practices extracted from our OKR implementation guide 👇

Tip #1: Limit the number of key results

The #1 role of OKRs is to help you and your team focus on what really matters. Business-as-usual activities will still be happening, but you do not need to track your entire roadmap in the OKRs.

We recommend having 3-4 objectives, and 3-4 key results per objective. A platform like Tability can run audits on your data to help you identify the plans that have too many goals.

Tip #2: Commit to weekly OKR check-ins

Don't fall into the set-and-forget trap. It is important to adopt a weekly check-in process to get the full value of your OKRs and make your strategy agile – otherwise this is nothing more than a reporting exercise.

Being able to see trends for your key results will also keep yourself honest.

Tip #3: No more than 2 yellow statuses in a row

Yes, this is another tip for goal-tracking instead of goal-setting (but you'll get plenty of OKR examples above). But, once you have your goals defined, it will be your ability to keep the right sense of urgency that will make the difference.

As a rule of thumb, it's best to avoid having more than 2 yellow/at risk statuses in a row.

Make a call on the 3rd update. You should be either back on track, or off track. This sounds harsh but it's the best way to signal risks early enough to fix things.

Save hours with automated OKR dashboards

AI feedback for OKRs in Tability

Your quarterly OKRs should be tracked weekly if you want to get all the benefits of the OKRs framework. Reviewing progress periodically has several advantages:

We recommend using a spreadsheet for your first OKRs cycle. You'll need to get familiar with the scoring and tracking first. Then, you can scale your OKRs process by using Tability to save time with automated OKR dashboards, data connectors, and actionable insights.

How to get Tability dashboards:

That's it! Tability will instantly get access to 10+ dashboards to monitor progress, visualise trends, and identify risks early.

More Large Language Models OKR templates

We have more templates to help you draft your team goals and OKRs.

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