By playing, you agree to uListen's Terms and Privacy Policy and YouTube's Terms of Service.

“I’m incapable of doing my job without AI”: How this PM uses Claude + ChatGPT as his second brain

Amir Klein is a product manager at Monday.com, leading their AI agents initiative. Despite taking two months of paternity leave, he ranked #4 out of 90 PMs in AI tool usage at his company.

Claire VohostAmir Kleinguest

Oct 5, 202538mWatch on YouTube ↗

Summaries, chapters, transcripts, and FAQs on this page are made by uListen, not YouTube.

WHAT IT’S REALLY ABOUT

A PM’s AI second brain: scrapers, writing coach, voice interviews

Amir Klein (PM at monday.com) explains how he offloads constant PM context switching into separate Claude/ChatGPT “project” workspaces, each stocked with files, instructions, and ongoing threads.
He demos using Claude to build a Reddit scraper, generating a dataset of ~34,000 rows of conversations about AI agents and competitors, then having Claude summarize themes with frequencies and cited quotes for spot-checking.
He shows how he turns internal artifacts (kickoff decks, PRDs, website/support pages printed as PDFs) plus external research into a living knowledge base that he continuously re-uploads as his thinking evolves.
Finally, he shares “personal development” workflows: a custom writing-coach GPT trained on Wes Kao/Lenny-style guidance for concise Slack updates, and GPT Voice Mode for realistic mock product interviews with candid feedback.

IDEAS WORTH REMEMBERING

5 ideas

Treat each initiative as its own AI “brain.”

Amir creates separate Claude/ChatGPT projects per domain, each with dedicated instructions, files, and long-running threads so he can jump between initiatives without losing context.

Start every project with grounding artifacts, then “ping-pong” to an outline.

He seeds the project with kickoff decks/PRDs/any available data, uses iterative back-and-forth to produce a narrative (e.g., PRD/product review), then re-uploads that output to strengthen the knowledge base.

Use AI to build the data pipeline—not just analyze the result.

Instead of manually searching, he asked Claude for an automated, free approach; Claude narrowed feasible sources (Reddit vs. paid/limited Twitter/LinkedIn APIs) and guided him step-by-step through setup and scripting.

Turn messy market chatter into prioritizable themes with numbers.

After scraping ~34,000 Reddit rows, he asked Claude to summarize into a frequency/percentage table so he could identify “hottest topics” and bring quantitative signals back to his team.

Demand citations to keep analysis honest.

To avoid blind trust, he asks the model to include 1–2 direct quotes per theme, then verifies via keyword search in the raw dataset—fast spot-checking without reading everything.

WORDS WORTH SAVING

5 quotes

You can silo, like, brains of conversations and threads in GPT and Claude.

— Amir Klein

I had a vision… to get… thousands and thousands of conversations… with the help of Claude.

— Amir Klein

Now be my analyst… summarize it in a table… frequency… percentage… I need weights.

— Amir Klein

I hate it when the AI will be… super supportive… Push back on things.

— Amir Klein

Just open GPT Voice and just go for it.

— Amir Klein

Read the available transcript

Project folders as AI “second brains”Reducing PM context switching with persistent threadsReddit scraping workflow using Claude step-by-step guidanceLarge-scale conversation analysis (34,000 rows)Fact-checking with quoted referencesBuilding effective GPT knowledge bases (PDFs, decks, support pages)Voice mode for interview rehearsal and feedback loops

High quality AI-generated summary created from speaker-labeled transcript.

Get more out of YouTube videos.

Read along on your phone, search it beside the video, or ask your favorite AI app what was said.