Paweł Huryn
@pawelhuryn.bsky.social
Product @ Ideals | Actionable Insights & Resources for PMs | The Product Compass Newsletter: productcompass.pm
Thanks for finding me here! 😅
April 7, 2025 at 3:52 PM
Thanks for finding me here! 😅
Want to learn more?
You can explore MCP yourself. It's not hard.
Or get ready-to-use configuration to copy from my new post: www.productcompass.pm/p/mcp-case-s...
Plus, my support on Slack anytime.
(7/7)
You can explore MCP yourself. It's not hard.
Or get ready-to-use configuration to copy from my new post: www.productcompass.pm/p/mcp-case-s...
Plus, my support on Slack anytime.
(7/7)
MCP for PMs: How To Automate Figma → Jira (Epics, Stories) in 10 Minutes
Case Study: Using an LLM Agent & MCP (Model Context Protocol) to transform Figma into 6 epics and 20 user stories in 10 minutes. Without touching the keyboard.
www.productcompass.pm
March 30, 2025 at 2:47 PM
Want to learn more?
You can explore MCP yourself. It's not hard.
Or get ready-to-use configuration to copy from my new post: www.productcompass.pm/p/mcp-case-s...
Plus, my support on Slack anytime.
(7/7)
You can explore MCP yourself. It's not hard.
Or get ready-to-use configuration to copy from my new post: www.productcompass.pm/p/mcp-case-s...
Plus, my support on Slack anytime.
(7/7)
Its popularity has exploded (Google, MCP AI):
(6/7)
(6/7)
March 30, 2025 at 2:47 PM
Its popularity has exploded (Google, MCP AI):
(6/7)
(6/7)
Before I share more, why is MCP so powerful?
It's banal to use, with 300+ supported systems:
(5/7)
It's banal to use, with 300+ supported systems:
(5/7)
March 30, 2025 at 2:47 PM
Before I share more, why is MCP so powerful?
It's banal to use, with 300+ supported systems:
(5/7)
It's banal to use, with 300+ supported systems:
(5/7)
What this means:
1. Spending too much time working with the backlog?
- You might easily save 10+ hours/week.
2. Is your job about creating User Stories, rather than discovery?
- Bad news. AI can do that for you. Learn fast.
(4/7)
1. Spending too much time working with the backlog?
- You might easily save 10+ hours/week.
2. Is your job about creating User Stories, rather than discovery?
- Bad news. AI can do that for you. Learn fast.
(4/7)
March 30, 2025 at 2:47 PM
What this means:
1. Spending too much time working with the backlog?
- You might easily save 10+ hours/week.
2. Is your job about creating User Stories, rather than discovery?
- Bad news. AI can do that for you. Learn fast.
(4/7)
1. Spending too much time working with the backlog?
- You might easily save 10+ hours/week.
2. Is your job about creating User Stories, rather than discovery?
- Bad news. AI can do that for you. Learn fast.
(4/7)
High-level steps to do the same:
1. Download Claude Desktop
2. Get Figma access token
3. Get Atlassian API token
4. Configure MCP servers for Figma and Jira
5. Ask AI to create epics and stories based on Figma
6. Wait 10 minutes. Done.
(3/7)
1. Download Claude Desktop
2. Get Figma access token
3. Get Atlassian API token
4. Configure MCP servers for Figma and Jira
5. Ask AI to create epics and stories based on Figma
6. Wait 10 minutes. Done.
(3/7)
March 30, 2025 at 2:47 PM
High-level steps to do the same:
1. Download Claude Desktop
2. Get Figma access token
3. Get Atlassian API token
4. Configure MCP servers for Figma and Jira
5. Ask AI to create epics and stories based on Figma
6. Wait 10 minutes. Done.
(3/7)
1. Download Claude Desktop
2. Get Figma access token
3. Get Atlassian API token
4. Configure MCP servers for Figma and Jira
5. Ask AI to create epics and stories based on Figma
6. Wait 10 minutes. Done.
(3/7)
First, the demo.
Kind of boring.
AI creates 6 epics and 30 user stories.
I'm watching: youtu.be/-J1T4dF8zqo
(2/7)
Kind of boring.
AI creates 6 epics and 30 user stories.
I'm watching: youtu.be/-J1T4dF8zqo
(2/7)
Case study: How to Automate Figma → Jira (Epics, Stories) With MCP
YouTube video by The Product Compass
youtu.be
March 30, 2025 at 2:47 PM
First, the demo.
Kind of boring.
AI creates 6 epics and 30 user stories.
I'm watching: youtu.be/-J1T4dF8zqo
(2/7)
Kind of boring.
AI creates 6 epics and 30 user stories.
I'm watching: youtu.be/-J1T4dF8zqo
(2/7)
P.S. Enjoy it?
- Follow me @pawelhuryn.bsky.social to master AI PM together
- Share this thread with others: bsky.app/profile/pawe...
I appreciate it!
- Follow me @pawelhuryn.bsky.social to master AI PM together
- Share this thread with others: bsky.app/profile/pawe...
I appreciate it!
I built a RAG chatbot in 15 minutes. No coding.
A great way to learn, automate your work, or create a solution for a PM portfolio.
(That's probably the only tutorial to do it end-to-end without installing anything locally)
(1/8) 🧵
A great way to learn, automate your work, or create a solution for a PM portfolio.
(That's probably the only tutorial to do it end-to-end without installing anything locally)
(1/8) 🧵
March 17, 2025 at 8:14 AM
P.S. Enjoy it?
- Follow me @pawelhuryn.bsky.social to master AI PM together
- Share this thread with others: bsky.app/profile/pawe...
I appreciate it!
- Follow me @pawelhuryn.bsky.social to master AI PM together
- Share this thread with others: bsky.app/profile/pawe...
I appreciate it!
(8/8) You can repeat it, to:
- Learn about RAG
- Develop a better intuition for managing AI products
- Build an AI-powered RAG chatbot for your portfolio
- Automate your work
Probably the only no-code, no-install tutorial.
How-to and templates: www.productcompass.pm/p/how-to-bui...
- Learn about RAG
- Develop a better intuition for managing AI products
- Build an AI-powered RAG chatbot for your portfolio
- Automate your work
Probably the only no-code, no-install tutorial.
How-to and templates: www.productcompass.pm/p/how-to-bui...
How to Build a RAG Chatbot Without Coding (AI PM Series)
Learn about RAG, develop a better AI product intuition, and build an AI-powered chatbot for your PM portfolio. A step-by-step guide with ready-to-use templates.
www.productcompass.pm
March 17, 2025 at 8:12 AM
(8/8) You can repeat it, to:
- Learn about RAG
- Develop a better intuition for managing AI products
- Build an AI-powered RAG chatbot for your portfolio
- Automate your work
Probably the only no-code, no-install tutorial.
How-to and templates: www.productcompass.pm/p/how-to-bui...
- Learn about RAG
- Develop a better intuition for managing AI products
- Build an AI-powered RAG chatbot for your portfolio
- Automate your work
Probably the only no-code, no-install tutorial.
How-to and templates: www.productcompass.pm/p/how-to-bui...
(7/8) In my new post, I present everything you need to create a functional chatbot using LLM and RAG with ready-to-use templates.
The process takes 15-45 minutes and doesn’t require coding or installing anything locally.
The process takes 15-45 minutes and doesn’t require coding or installing anything locally.
March 17, 2025 at 8:12 AM
(7/8) In my new post, I present everything you need to create a functional chatbot using LLM and RAG with ready-to-use templates.
The process takes 15-45 minutes and doesn’t require coding or installing anything locally.
The process takes 15-45 minutes and doesn’t require coding or installing anything locally.
(6/8) 3. Tech stack
You can build it virtually for free:
- UI: Lovable(free version)
- Orchestration: n8n (free trial)
- LLM: GPT-4o-mini by OpenAI (less than $2)
- Embedding model: text-embedding-3-small
- Vector database: Pinecone (free tier)
- Documents: Google Drive
You can build it virtually for free:
- UI: Lovable(free version)
- Orchestration: n8n (free trial)
- LLM: GPT-4o-mini by OpenAI (less than $2)
- Embedding model: text-embedding-3-small
- Vector database: Pinecone (free tier)
- Documents: Google Drive
March 17, 2025 at 8:12 AM
(6/8) 3. Tech stack
You can build it virtually for free:
- UI: Lovable(free version)
- Orchestration: n8n (free trial)
- LLM: GPT-4o-mini by OpenAI (less than $2)
- Embedding model: text-embedding-3-small
- Vector database: Pinecone (free tier)
- Documents: Google Drive
You can build it virtually for free:
- UI: Lovable(free version)
- Orchestration: n8n (free trial)
- LLM: GPT-4o-mini by OpenAI (less than $2)
- Embedding model: text-embedding-3-small
- Vector database: Pinecone (free tier)
- Documents: Google Drive
(5/8) 2. Runtime
When the user asks a question, the question is also converted into a vector and used to retrieve the most similar document chunks.
Finally, an LLM uses retrieved chunks and the original request to generate an answer.
When the user asks a question, the question is also converted into a vector and used to retrieve the most similar document chunks.
Finally, an LLM uses retrieved chunks and the original request to generate an answer.
March 17, 2025 at 8:12 AM
(5/8) 2. Runtime
When the user asks a question, the question is also converted into a vector and used to retrieve the most similar document chunks.
Finally, an LLM uses retrieved chunks and the original request to generate an answer.
When the user asks a question, the question is also converted into a vector and used to retrieve the most similar document chunks.
Finally, an LLM uses retrieved chunks and the original request to generate an answer.
(4/8) TL;DR: We can use those vectors to measure the similarity of text strings, e.g., when performing search, clustering similar data, detecting anomalies, or labeling data.
March 17, 2025 at 8:12 AM
(4/8) TL;DR: We can use those vectors to measure the similarity of text strings, e.g., when performing search, clustering similar data, detecting anomalies, or labeling data.
(3/8) 1. Preprocessing
When you use RAG, your data (e.g., documents) is not stored in the original format.
Instead, it's split into chunks (e.g., 500-1000 characters each), which are then converted into multi-dimensional vectors and stored in a vector database.
When you use RAG, your data (e.g., documents) is not stored in the original format.
Instead, it's split into chunks (e.g., 500-1000 characters each), which are then converted into multi-dimensional vectors and stored in a vector database.
March 17, 2025 at 8:12 AM
(3/8) 1. Preprocessing
When you use RAG, your data (e.g., documents) is not stored in the original format.
Instead, it's split into chunks (e.g., 500-1000 characters each), which are then converted into multi-dimensional vectors and stored in a vector database.
When you use RAG, your data (e.g., documents) is not stored in the original format.
Instead, it's split into chunks (e.g., 500-1000 characters each), which are then converted into multi-dimensional vectors and stored in a vector database.
(2/8) Unlike an LLM, RAG can work with millions of documents.
But how does it work?
But how does it work?
March 17, 2025 at 8:12 AM
(2/8) Unlike an LLM, RAG can work with millions of documents.
But how does it work?
But how does it work?
Have you ever considered your IQ is actually 110-120? Nothing wrong with that.
IQ is what IQ tests measure. Many use this circular definition on purpose as IQ doesn't account for all intelligence aspects.
I mean, you're publicly claiming to have an IQ higher than Einstein's (160).
IQ is what IQ tests measure. Many use this circular definition on purpose as IQ doesn't account for all intelligence aspects.
I mean, you're publicly claiming to have an IQ higher than Einstein's (160).
March 15, 2025 at 8:07 AM
Have you ever considered your IQ is actually 110-120? Nothing wrong with that.
IQ is what IQ tests measure. Many use this circular definition on purpose as IQ doesn't account for all intelligence aspects.
I mean, you're publicly claiming to have an IQ higher than Einstein's (160).
IQ is what IQ tests measure. Many use this circular definition on purpose as IQ doesn't account for all intelligence aspects.
I mean, you're publicly claiming to have an IQ higher than Einstein's (160).
(5/5) Hope that helps!
Enjoy this?
Follow me @pawelhuryn.bsky.social and repost this to help your friends: bsky.app/profile/pawe...
I appreciate it.
--
P.S. You can download my infographic (PDF) and 30+ others for free by subscribing to my newsletter: www.theproductcompass.tech/download-pm-...
Enjoy this?
Follow me @pawelhuryn.bsky.social and repost this to help your friends: bsky.app/profile/pawe...
I appreciate it.
--
P.S. You can download my infographic (PDF) and 30+ others for free by subscribing to my newsletter: www.theproductcompass.tech/download-pm-...
Product management is, at its heart, about managing risks.
Product teams usually focus on Value, Usability, Viability, and Feasibility.
But I’ve seen products and initiatives fail for reasons that didn't easily match those categories.
🧵
Product teams usually focus on Value, Usability, Viability, and Feasibility.
But I’ve seen products and initiatives fail for reasons that didn't easily match those categories.
🧵
March 3, 2025 at 1:49 PM
(5/5) Hope that helps!
Enjoy this?
Follow me @pawelhuryn.bsky.social and repost this to help your friends: bsky.app/profile/pawe...
I appreciate it.
--
P.S. You can download my infographic (PDF) and 30+ others for free by subscribing to my newsletter: www.theproductcompass.tech/download-pm-...
Enjoy this?
Follow me @pawelhuryn.bsky.social and repost this to help your friends: bsky.app/profile/pawe...
I appreciate it.
--
P.S. You can download my infographic (PDF) and 30+ others for free by subscribing to my newsletter: www.theproductcompass.tech/download-pm-...
(4/5) Finally, make sure your teams feel safe to experiment:
“A good failure is when the value of the lesson is greater than the cost of the lesson. A bad failure is when the value of the lesson is much less than the cost of the lesson.” - Alberto Savoia, author of The Right It
“A good failure is when the value of the lesson is greater than the cost of the lesson. A bad failure is when the value of the lesson is much less than the cost of the lesson.” - Alberto Savoia, author of The Right It
March 3, 2025 at 1:47 PM
(4/5) Finally, make sure your teams feel safe to experiment:
“A good failure is when the value of the lesson is greater than the cost of the lesson. A bad failure is when the value of the lesson is much less than the cost of the lesson.” - Alberto Savoia, author of The Right It
“A good failure is when the value of the lesson is greater than the cost of the lesson. A bad failure is when the value of the lesson is much less than the cost of the lesson.” - Alberto Savoia, author of The Right It
(3/5) Remember that you can’t eliminate risks.
The key to making decisions is taking calculated risks informed by data, qualitative insights, and intuition.
The ultimate test is users interacting with your product in the real world, using their own data.
The key to making decisions is taking calculated risks informed by data, qualitative insights, and intuition.
The ultimate test is users interacting with your product in the real world, using their own data.
March 3, 2025 at 1:47 PM
(3/5) Remember that you can’t eliminate risks.
The key to making decisions is taking calculated risks informed by data, qualitative insights, and intuition.
The ultimate test is users interacting with your product in the real world, using their own data.
The key to making decisions is taking calculated risks informed by data, qualitative insights, and intuition.
The ultimate test is users interacting with your product in the real world, using their own data.
(2/5) For example, a business model being copied.
Depending on the context, three other risk areas to consider:
- Go-to-market (I recommend separating it from viability for new products)
- Strategy and objectives
- Teams
Depending on the context, three other risk areas to consider:
- Go-to-market (I recommend separating it from viability for new products)
- Strategy and objectives
- Teams
March 3, 2025 at 1:47 PM
(2/5) For example, a business model being copied.
Depending on the context, three other risk areas to consider:
- Go-to-market (I recommend separating it from viability for new products)
- Strategy and objectives
- Teams
Depending on the context, three other risk areas to consider:
- Go-to-market (I recommend separating it from viability for new products)
- Strategy and objectives
- Teams
𝐇𝐨𝐰 𝐜𝐚𝐧 𝐈 𝐮𝐬𝐞 𝐢𝐭?
Examples, best practices, and free access: www.productcompass.pm/p/deep-marke...
Hope that helps!
Examples, best practices, and free access: www.productcompass.pm/p/deep-marke...
Hope that helps!
Deep Market Researcher AI Agent for Product Managers
Things just got serious. This is probably the most specialized and fastest AI research agent for Product Managers.
www.productcompass.pm
March 2, 2025 at 10:02 AM
𝐇𝐨𝐰 𝐜𝐚𝐧 𝐈 𝐮𝐬𝐞 𝐢𝐭?
Examples, best practices, and free access: www.productcompass.pm/p/deep-marke...
Hope that helps!
Examples, best practices, and free access: www.productcompass.pm/p/deep-marke...
Hope that helps!