Welcome to the Beta Version of Geekbot's AI

At Geekbot, we strive to deliver tools that enhance your team's productivity and streamline your daily tasks. Our latest innovation does just that, taking your Geekbot experience to the next level with artificial intelligence.

Geekbot's AI introduces a more conversational dynamic with the bot, introduces knowledge extraction methods coupled with conversational interaction in natural language, that utilizes everything your team has said in their reports to enable fluid interactions that allow you to do things like:

Engage in meaningful conversations that deliver real-time insights into your team's activities, projects, and meetings;
Ask questions and follow-up queries to summarize, compare, or classify the data;
Gain a deeper understanding of your team's performance, enabling more data-driven decision-making.

Thanks to Geekbot's AI, you now have real-time knowledge based on what your team has reported right at your fingertips.

Let's run through how you can get the most out of an even smarter Geekbot.

Get Real-Time Knowledge With Simple Prompts

The Conversational AI is designed to understand and respond to a variety of user intents expressed in natural language, enabling more dynamic interactions that go beyond simple queries. Here are a variety of ways you can use Geekbot to get the insights you need in seconds.

Get Status Reports
"Give me a status report summarizing all team activity for {given time period}" or "Provide a team summary for last year."
See Team Activities per Topic/Period
"What is the team doing this month?" or "What has the team done on bugs in the last six months?"
Find out Task Duration
"How long has @John spent working on the dashboard in the last two years?" or "How much time did @Theo spend on code reviews last year?"
See Individual Contributions
"What has @Mike done on bug fixing?" or "What have @John, @Mary, and @George worked on in the last four months?"
Find Someone To Help
"Who can help me with Python?" or "Who can provide some assistance with onboarding?"
View Resource Allocation
"Who worked on the dashboard feature?" or "Who worked on bug fixing last month?"
See Who's Reporting
"Who has reported last month?" or "Who reported last year for the Daily Standup?"
Get A Report Count
"How many participants reported last month?" or "How many participants reported between 03-23-2024 and 04-20-2024?"
Surface Detailed Insights
"What did @Roland report in Daily Standup last week?" or "What did @Alex write in Daily Standup last month?"
Find Topic Mentions
"What did @Mary say about onboarding last year?" or "What has @Laura said about onboarding?"
Identify Blockers
"Who was blocked last month?" or "Whose work is currently blocked?"
Get Meeting Insights
"What meetings took place last year?" or "Show me what meetings happened in the last month?"
Check Your Team's Emotional State
"How's the team feeling?" or "What's the mood of @Alex and @Liz?"
Spot Patterns In Collaboration
"Who usually works with @Kate?" or "Who works with @Mike?"

Dive Deeper With Follow-ups

Beyond answering direct queries, the bot's Conversational AI can process the content of previous answers and deliver deeper insights.

Here are four ways you can put the Enhanced AI to good use.

1. Attribute Reports

Follow-up queries could help you determine the percentage of reports for each workflow in a team. This type of analysis can then help you visualize engagement and participation across different team segments.

This is how the interaction might look:

User: Who reported last year?
Geekbot: There were 822 reports made by 28 members in 11 workflows during 2023-01-01 to 2024-01-01: . . . (rest of response)
User: Use the above to make a list with each workflow and the percentage of reports from the total reports
Geekbot: Here is the list of workflows and the percentage of reports from the total reports during 2023-01-01 to 2024-01-01:
1. Infrastructure Changelog had 3.77% of the reports
2. CS&Marketing changelog had 1.09% of the reports
3. Smart Standup Survey had 1.34% of the reports
4. Billing Team had 1.34% of the reports
5. Product changelog had 3.04% of the reports
6. Meeting notes had 4.25% of the reports
7. Team Bugs/Issues Log had 1.95% of the reports
8. New Proposal had 0.61% of the reports
9. Daily had 70.79% of the reports
10. Sprint Goals had 2.19% of the reports
11. Friday Screenshot had 9.73% of the reports

2. Create Announcements

You could also automatically generate team announcements based on reported data, focusing on issues like 'task completion' or 'mood analysis over a specific period.'

Here's how to go about it:

User: Give me a status report for the last five months
Geekbot: The following is a team briefing for the period 2023-08-01 to 2024-01-01 :
- there were 461 reports made by 26 members
- there were 680 tasks done by 19 members
- there were 77 blockers mentioned, specifically:
38 for various issues
17 dependencies
12 for technical issues
5 for health issues
3 related to weather
2 for fatigue issues
- there were 6 meetings mentioned by 5 members
- and the team was in a positive mood, specifically:
11 members in positive mood
6 members in neutral mood
1 members in negative mood
User: Use the above to create an engaging announcement about what the team achieved in this period
Geekbot: 🎉 Team Update: Celebrating the Last Five Months 🎉

Team, let's take a moment to appreciate our collective achievements over the last five months. We've seen incredible dedication and hard work from everyone, resulting in a total of 680 tasks completed by 19 team members. Our collaborative efforts have led to 461 insightful reports and 77 blockers addressed, showcasing our commitment to transparency and problem-solving.

Moreover, our positive mood has been contagious, with a11 members radiating positivity and enthusiasm. It's fantastic to see our team spirit shining through, especially during the 6 meetings held during this period. Let's keep up the great work and continue to support each other as we strive for success. Here's to the outstanding progress we've made together! 🚀

3. Make Comparisons

Another valuable task is to compare team activities across different periods, which can offer insights into trends or shifts in focus.

You could do this with the following prompts:

User: What did the team do in 2022?
Geekbot: Here are some of the team's most mentioned topics (2022-01-01 - 2023-01-01): . . . (rest of response)
User: What did the team do in 2023?
Geekbot: Here are some of the team's most mentioned topics (2023-01-01 - 2024-01-01): . . . (rest of response)
User: use the above information to compare the team’s activities and direction for these two years
Geekbot: In 2022, the team was involved in activities such as . . . There was also a focus on design implementation, ideation for new product, and product research release policies. The team seemed to be engaged in a mix of design, research, and product development activities.

In 2023, the team's activities included tasks like . . . There was also a focus on . . . The team's direction in 2023 appears to be more oriented towards engineering, code reviews, and sprint planning activities, with an emphasis on refining and releasing product features.

Overall, the team's activities in 2022 seemed to be more diverse, including design, research, and product development, while in 2023, the focus appeared to be more on engineering, code reviews, and sprint planning, indicating a potential shift in the team's direction towards more technical and development-oriented tasks.

4. Analyze Team Reporting Progress

Evaluating team growth and reporting progress over the years can also provide a picture of how team engagement and collaboration have evolved.

All it takes is a few short queries:

User: Who reported in 2021?
Geekbot: There were 911 reports made by 25 members in 8 workflows during 2021-01-01 to 2022-01-01: . . . (rest of response)
User: Who reported in 2022?
Geekbot: There were 598 reports made by 28 members in 9 workflows during 2022-01-01 to 2023-01-01: . . . (rest of response)
User: Who reported in 2023?
Geekbot: There were 822 reports made by 28 members in 11 workflows during 2023-01-01 to 2024-01-01: . . . (rest of response)
User: Based on the above create a summary which compares a) growth of the team b) reporting in workflows for these three years
Geekbot: In 2021, there were 911 reports made by 25 members in 8 workflows, while in 2022, there were 598 reports made by 28 members in 9 workflows. In 2023, the number of reports increased to 822, with 28 members participating in 11 workflows. This indicates a growth in both the number of reports and the level of participation in workflows over the three years. The team has expanded in terms of both reporting activity and the number of members involved in the standup process.

There you have it; we hope you enjoy interacting with the smartened-up bot.

If you have any comments or questions — or if you'd like further assistance — please reach out to our support team, as they'd love to hear your thoughts. Meanwhile, we all remain on hand to help you maximize your productivity with Geekbot's AI.

Happy collaborating!

💡 Remember — Geekbot's AI is in beta: we welcome your feedback as we look to enhance your experience further.

Reporting guidelines - How do I report?

AI features: Team Topics

AI features: Activity Viewer