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תוכן מסופק על ידי Hugo Bowne-Anderson. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Hugo Bowne-Anderson או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
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Episode 64: Data Science Meets Agentic AI with Michael Kennedy (Talk Python)

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Manage episode 522368997 series 3317544
תוכן מסופק על ידי Hugo Bowne-Anderson. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Hugo Bowne-Anderson או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
We have been sold a story of complexity. Michael Kennedy (Talk Python) argues we can escape this by relentlessly focusing on the problem at hand, reducing costs by orders of magnitude in software, data, and AI.
In this episode, Michael joins Hugo to dig into the practical side of running Python systems at scale. They connect these ideas to the data science workflow, exploring which software engineering practices allow AI teams to ship faster and with more confidence. They also detail how to deploy systems without unnecessary complexity and how Agentic AI is fundamentally reshaping development workflows.
We talk through:
- Escaping complexity hell to reduce costs and gain autonomy
- The specific software practices, like the "Docker Barrier", that matter most for data scientists
- How to replace complex cloud services with a simple, robust $30/month stack
- The shift from writing code to "systems thinking" in the age of Agentic AI
- How to manage the people-pleasing psychology of AI agents to prevent broken code
- Why struggle is still essential for learning, even when AI can do the work for you
LINKS
Talk Python In Production, the Book! (https://talkpython.fm/books/python-in-production)
Just Enough Python for Data Scientists Course (https://training.talkpython.fm/courses/just-enough-python-for-data-scientists)
Agentic AI Programming for Python Course (https://training.talkpython.fm/courses/agentic-ai-programming-for-python)
Talk Python To Me (https://talkpython.fm/) and a recent episode with Hugo as guest: Building Data Science with Foundation LLM Models (https://talkpython.fm/episodes/show/526/building-data-science-with-foundation-llm-models)
Python Bytes podcast (https://pythonbytes.fm/)
Upcoming Events on Luma (https://lu.ma/calendar/cal-8ImWFDQ3IEIxNWk)
Watch the podcast video on YouTube (https://youtube.com/live/jfSRxxO3aRo?feature=share)
Join the final cohort of our Building AI Applications course starting Jan 12, 2026 (35% off for listeners) (https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=vgrav): https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=vgrav
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hugobowne.substack.com
  continue reading

65 פרקים

Artwork
iconשתפו
 
Manage episode 522368997 series 3317544
תוכן מסופק על ידי Hugo Bowne-Anderson. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Hugo Bowne-Anderson או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
We have been sold a story of complexity. Michael Kennedy (Talk Python) argues we can escape this by relentlessly focusing on the problem at hand, reducing costs by orders of magnitude in software, data, and AI.
In this episode, Michael joins Hugo to dig into the practical side of running Python systems at scale. They connect these ideas to the data science workflow, exploring which software engineering practices allow AI teams to ship faster and with more confidence. They also detail how to deploy systems without unnecessary complexity and how Agentic AI is fundamentally reshaping development workflows.
We talk through:
- Escaping complexity hell to reduce costs and gain autonomy
- The specific software practices, like the "Docker Barrier", that matter most for data scientists
- How to replace complex cloud services with a simple, robust $30/month stack
- The shift from writing code to "systems thinking" in the age of Agentic AI
- How to manage the people-pleasing psychology of AI agents to prevent broken code
- Why struggle is still essential for learning, even when AI can do the work for you
LINKS
Talk Python In Production, the Book! (https://talkpython.fm/books/python-in-production)
Just Enough Python for Data Scientists Course (https://training.talkpython.fm/courses/just-enough-python-for-data-scientists)
Agentic AI Programming for Python Course (https://training.talkpython.fm/courses/agentic-ai-programming-for-python)
Talk Python To Me (https://talkpython.fm/) and a recent episode with Hugo as guest: Building Data Science with Foundation LLM Models (https://talkpython.fm/episodes/show/526/building-data-science-with-foundation-llm-models)
Python Bytes podcast (https://pythonbytes.fm/)
Upcoming Events on Luma (https://lu.ma/calendar/cal-8ImWFDQ3IEIxNWk)
Watch the podcast video on YouTube (https://youtube.com/live/jfSRxxO3aRo?feature=share)
Join the final cohort of our Building AI Applications course starting Jan 12, 2026 (35% off for listeners) (https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=vgrav): https://maven.com/hugo-stefan/building-ai-apps-ds-and-swe-from-first-principles?promoCode=vgrav
This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit hugobowne.substack.com
  continue reading

65 פרקים

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