How does your team collaborate with AI?
Ilko Kacharov [Team-GPT]
12 replies
Every team has its secrets about team collaboration.
Share some ideas for crossing your team with the AI world.
- method of work
- tools and apps
- prompt sharing and learning
Replies
Iliya Valchanov@iliya_valchanov
Sharing knowledge is the most important
Share
We are Team-GPT-ing to collaborate with AI! :)
Collaboration is crucial when learning new technologies. All the answers of are included in my display name :D
The teams I'm part of use the following:
1. Share chats from ChatGPT via the in-built sharing.
2. Pass around prompts for image generation in Slack.
3. Collaborate and build upon each other prompt work via Team-GPT. Also I love seeing how other people are prompting it - helps me level up my prompting skills.
@veselin_nikolov Thanks for sharing your journey!
Is it approved by the company policy to share ChatGPT links publicly?
@ilko_kacharov No policy like this exists in the team I'm in.
We operate under the assumptions: "If it's not prohibited, then It's allowed" :D
I can see how sharing ChatGPT links can be a problem for other organizations.
For creative projects, we use AI to generate a plethora of ideas, which the team then refines and develops further.
We've adopted an iterative feedback loop where AI models generate content or solutions, and the team provides feedback. This continuous cycle helps the AI to learn and adapt to our specific needs over time.
Integrating AI into our team collaboration has not only improved efficiency but also sparked creativity and innovation. It's an exciting journey, and we're always on the lookout for new ways to harness the power of AI.
@remilittle Thanks for sharing! Really insightful
@remilittle This sounds like a very practical solution! AI needs feedback to provide greater results.
How many iterations do you often need to polish the end result?
@ilko_kacharov Feedback loops are essential. We typically aim for 2-3 iterations as a baseline. For more complex tasks, we deploy a chain of tasks with several iterations each to ensure optimal results. Consistency and refinement are key!
Our team collaborates with AI to enhance data analysis, automate tasks, and improve decision-making. We use tools like Python and TensorFlow for model development. We've seen tangible benefits, including improved accuracy and cost savings. Challenges like data quality are addressed through better data collection. We prioritize ethical AI use and plan to expand our AI integration in the future.
By incorporating AI into our team's collaboration process, we aim to leverage technology to enhance our capabilities, streamline tasks, and make data-driven decisions. This not only helps us work more efficiently but also positions us to provide better services and products to our customers in an increasingly competitive market.