Uploaded August 2026 | Updated September 2026, 2 weeks ago
š Recorded at PyCon DE & PyData 2026, 14.04.2026
2026.pycon.de/talks/RRLTBU
š Watch Serhii Sokolenko demonstrate how to move beyond "vibe coding" to build production-ready Python data systems using a disciplined, engineering-first approach to AI code assistants.
Speakers:
Serhii Sokolenko
Description:
Building production-ready Python data systems with AI coding agents requires moving beyond linear prompting toward a structured framework of skills, personas, and state management. While LLMs can rapidly generate initial code, they often struggle with existing codebases, environment configurations, and the non-linear nature of debugging and deployment. To solve this, a system can be implemented using a combination of persona-based skills, a fuzzy state machine for workflow orchestration, and a specialized runtime environment.
The approach utilizes markdown-based skill files to define specific roles, such as a business analyst for requirement reviews or a data architect for structural validation. Instead of a simple chain of commands, a fuzzy state machine identifies the user's intentāsuch as deploying a hotfix versus building a new featureāand assesses the current state of the repository to determine the necessary path. This is complemented by hooks that monitor tool calls and suggest debugging utilities, such as increasing logging verbosity or limiting data samples, when a pipeline fails during its first execution.
In a practical application, this framework was used to build a data pipeline that fetches issues from a public GitHub repository using DLT and loads them into DuckDB. The process involved using the Tower platform to manage secrets via a built-in vault and deploying the application through a unified CLI. The final system expanded the pipeline to write data to Apache Iceberg and integrated a Discord webhook for real-time bug notifications. This methodology transforms AI agents from simple code generators into expert collaborators capable of maintaining architectural standards and operational reliability.
āļø About PyCon DE:
PyCon DE is the leading conference on open-source Python applications in AI and data science. It brings together industry professionals, researchers, AI and data science practitioners, and software engineering communities, providing a unique platform for collaboration, knowledge sharing, and innovation.
The PyCon DE & PyData 2026 conference delivered an exceptional experience, fostering stronger connections within the Python community while showcasing the latest advancements in artificial intelligence and data science. Attendees enjoyed a diverse and engaging program of talks, workshops, and networking opportunities, further establishing the conference as a premier event for Python, AI, and data science enthusiasts across Germany.
PyCon DE 2027 will take place in Heidelberg from 19 to 23 April 2027.
Follow us:
ā¢ Newsletter: 2027.pycon.de/newsletter
ā¢ LinkedIn: linkedin.com/company/pyconde
ā¢ X: x.com/pyconde
Links:
ā¢ Conference website: pycon.de
ā¢ Other sessions: 2026.pycon.de/talks
The conference was organized by
ā¢ Python Softwareverband e.V.: pysv.org
ā¢ Pioneers Hub gemeinnĆ¼tzige GmbH: pioneershub.org
in collaboration with NumFOCUS Inc.: numfocus.org
If you enjoyed this session, please like, and subscribe to our channel for more insightful talks and discussions.
Share this video with your network to spread the knowledge!
Hashtags:
#Python #PyConDE #PyData #OpenSource #AI #DataScience #MachineLearning #SoftwareEngineering #LLMs #Community #Sovereignty
Acknowledgements:
Special thanks to all the volunteers and sponsors who made this event possible.
About:
Python Softwareverband e.V.:
PySV is a non-profit that promotes the use and development of Python in Germany through events, education, and advocacy, fostering an open Python community.
Pioneers Hub gemeinnĆ¼tzige GmbH:
is a non-profit fostering innovation in AI and tech by connecting experts and promoting knowledge exchange through events and collaborative initiatives.
NumFOCUS Inc.
supports open-source scientific computing by providing financial and logistical support to key projects like NumPy and Jupyter, promoting sustainable development and collaboration.
pydata.org
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
š Recorded at PyCon DE & PyData 2026, 14.04.2026
2026.pycon.de/talks/RRLTBU
š Watch Serhii Sokolenko demonstrate how to move beyond "vibe coding" to build production-ready Python data systems using a disciplined, engineering-first approach to AI code assistants.
Speakers:
Serhii Sokolenko
Description:
Building production-ready Python data systems with AI coding agents requires moving beyond linear prompting toward a structured framework of skills, personas, and state management. While LLMs can rapidly generate initial code, they often struggle with existing codebases, environment configurations, and the non-linear nature of debugging and deployment. To solve this, a system can be implemented using a combination of persona-based skills, a fuzzy state machine for workflow orchestration, and a specialized runtime environment.
The approach utilizes markdown-based skill files to define specific roles, such as a business analyst for requirement reviews or a data architect for structural validation. Instead of a simple chain of commands, a fuzzy state machine identifies the user's intentāsuch as deploying a hotfix versus building a new featureāand assesses the current state of the repository to determine the necessary path. This is complemented by hooks that monitor tool calls and suggest debugging utilities, such as increasing logging verbosity or limiting data samples, when a pipeline fails during its first execution.
In a practical application, this framework was used to build a data pipeline that fetches issues from a public GitHub repository using DLT and loads them into DuckDB. The process involved using the Tower platform to manage secrets via a built-in vault and deploying the application through a unified CLI. The final system expanded the pipeline to write data to Apache Iceberg and integrated a Discord webhook for real-time bug notifications. This methodology transforms AI agents from simple code generators into expert collaborators capable of maintaining architectural standards and operational reliability.
āļø About PyCon DE:
PyCon DE is the leading conference on open-source Python applications in AI and data science. It brings together industry professionals, researchers, AI and data science practitioners, and software engineering communities, providing a unique platform for collaboration, knowledge sharing, and innovation.
The PyCon DE & PyData 2026 conference delivered an exceptional experience, fostering stronger connections within the Python community while showcasing the latest advancements in artificial intelligence and data science. Attendees enjoyed a diverse and engaging program of talks, workshops, and networking opportunities, further establishing the conference as a premier event for Python, AI, and data science enthusiasts across Germany.
PyCon DE 2027 will take place in Heidelberg from 19 to 23 April 2027.
Follow us:
ā¢ Newsletter: 2027.pycon.de/newsletter
ā¢ LinkedIn: linkedin.com/company/pyconde
ā¢ X: x.com/pyconde
Links:
ā¢ Conference website: pycon.de
ā¢ Other sessions: 2026.pycon.de/talks
The conference was organized by
ā¢ Python Softwareverband e.V.: pysv.org
ā¢ Pioneers Hub gemeinnĆ¼tzige GmbH: pioneershub.org
in collaboration with NumFOCUS Inc.: numfocus.org
If you enjoyed this session, please like, and subscribe to our channel for more insightful talks and discussions.
Share this video with your network to spread the knowledge!
Hashtags:
#Python #PyConDE #PyData #OpenSource #AI #DataScience #MachineLearning #SoftwareEngineering #LLMs #Community #Sovereignty
Acknowledgements:
Special thanks to all the volunteers and sponsors who made this event possible.
About:
Python Softwareverband e.V.:
PySV is a non-profit that promotes the use and development of Python in Germany through events, education, and advocacy, fostering an open Python community.
Pioneers Hub gemeinnĆ¼tzige GmbH:
is a non-profit fostering innovation in AI and tech by connecting experts and promoting knowledge exchange through events and collaborative initiatives.
NumFOCUS Inc.
supports open-source scientific computing by providing financial and logistical support to key projects like NumPy and Jupyter, promoting sustainable development and collaboration.
pydata.org
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
![Dynamic Knowledge Graphs [PyCon DE & PyData 2026]](https://i.ytimg.com/vi/tDy8UzEO2cg/mqdefault.jpg "Dynamic Knowledge Graphs [PyCon DE & PyData 2026]
š Recorded at PyCon DE & PyData 2026, 16.04.2026
https://2026.pycon.de/talks/TST9LF/
š Watch Jakob Leander MĆ¼ller explain how to build a production-ready dynamic knowledge graph that overcomes the limitations of traditional RAG to handle real-time data evolution.
Speakers:
Jakob Leander MĆ¼ller
Description:
Dynamic knowledge graphs address the fragmentation of information across disconnected sources, such as Jira tickets, Git repositories, and Swagger documentation. While vector stores offer fast similarity searches, they lack global connectivity and struggle with conflicting entries. Static graph-based RAG systems provide holistic views but are slow to update and often lose traceability to source documents.
The proposed approach utilizes a property graph implemented in FalkyDB to maintain a machine-readable integration pipeline. The schema consists of four node types: document nodes (anchors with content hashes), entity nodes (deduplicated via similarity matching), fact nodes (atomic nuggets of information), and relationship nodes. Document nodes use outgoing edges to support all other nodes, ensuring full traceability and enabling precise deletions of outdated information without collapsing the entire graph.
Insertion involves a multi-stage pipeline using LLMs for structured output via Pydantic classes. To maximize connectivity, the system merges new nodes with existing ones using a hierarchy of matching techniques: exact matches, Jaro-Winkler string similarity, and semantic embedding comparisons, all verified by an LLM. Inference is handled by AI agents that explore the graph using tools for embedding queries, keyword searches, and neighborhood exploration, or by generating Cypher queries directly.
āļø About PyCon DE:
PyCon DE is the leading conference on open-source Python applications in AI and data science. It brings together industry professionals, researchers, AI and data science practitioners, and software engineering communities, providing a unique platform for collaboration, knowledge sharing, and innovation.
The PyCon DE & PyData 2026 conference delivered an exceptional experience, fostering stronger connections within the Python community while showcasing the latest advancements in artificial intelligence and data science. Attendees enjoyed a diverse and engaging program of talks, workshops, and networking opportunities, further establishing the conference as a premier event for Python, AI, and data science enthusiasts across Germany.
PyCon DE 2027 will take place in Heidelberg from 19 to 23 April 2027.
Follow us:
ā¢ Newsletter: https://2027.pycon.de/newsletter/
ā¢ LinkedIn: https://www.linkedin.com/company/pyconde
ā¢ X: https://www.x.com/pyconde
Links:
ā¢ Conference website: http://pycon.de
ā¢ Other sessions: https://2026.pycon.de/talks/
The conference was organized by
ā¢ Python Softwareverband e.V.: http://pysv.org
ā¢ Pioneers Hub gemeinnĆ¼tzige GmbH: http://pioneershub.org
in collaboration with NumFOCUS Inc.: http://numfocus.org
If you enjoyed this session, please like, and subscribe to our channel for more insightful talks and discussions.
Share this video with your network to spread the knowledge!
Hashtags:
#Python #PyConDE #PyData #OpenSource #AI #DataScience #MachineLearning #SoftwareEngineering #LLMs #Community #Sovereignty
Acknowledgements:
Special thanks to all the volunteers and sponsors who made this event possible.
About:
Python Softwareverband e.V.:
PySV is a non-profit that promotes the use and development of Python in Germany through events, education, and advocacy, fostering an open Python community.
Pioneers Hub gemeinnĆ¼tzige GmbH:
is a non-profit fostering innovation in AI and tech by connecting experts and promoting knowledge exchange through events and collaborative initiatives.
NumFOCUS Inc.
supports open-source scientific computing by providing financial and logistical support to key projects like NumPy and Jupyter, promoting sustainable development and collaboration.
www.pydata.org
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.")
![Making bad CLIs fun with Small Language Models [PyCon DE & PyData 2026]](https://i.ytimg.com/vi/tNAOyH1DS6o/mqdefault.jpg "Making bad CLIs fun with Small Language Models [PyCon DE & PyData 2026]
š Recorded at PyCon DE & PyData 2026, 16.04.2026
https://2026.pycon.de/talks/GMNE3E/
š Watch Senior Data Scientist Moritz Bauer demonstrate how to transform frustrating command-line interfaces into intuitive, natural-language experiences using fine-tuned Small Language Models.
Speakers:
Moritz Bauer
Description:
Complex command-line interfaces (CLIs) often suffer from steep learning curves due to intricate syntax and obscure flags. While large language models (LLMs) can translate natural language into CLI commands, they typically require cloud connectivity, API keys, and significant computational resources. To address this, a local implementation using small language models (SLMs) with fewer than one billion parameters enables fast, on-device inference without internet dependency.
The approach centers on supervised fine-tuning (SFT) using synthetic datasets. Initial data pairs of natural language instructions and corresponding CLI arguments are generated by prompting a coding LLM (such as Claude Opus) with the tools source code. To prevent the SLM from overfitting to rigid patterns, these pairs undergo prompt mutation, where a teacher model (such as Qwen 3.5 9B or GLM 4.5) generates multiple natural language variations for each command. To maintain data integrity, a filtering step removes variants that omit critical identifiers, such as customer names or dates, which would otherwise force the SLM to hallucinate.
The implementation utilizes the Gemma 2B or smaller variants (specifically a quarter-billion parameter model) fine-tuned via the Hugging Face stack on a MacBook M3 Pro. Training 100,000 pairs takes approximately 10 hours. Testing on an internal plotting tool and FFmpeg yielded an accuracy rate of roughly 85%, with errors typically manifesting as missing or extra flags. Using the Lama CPP inference engine, the system generates commands in under 2.5 seconds, demonstrating that SLMs can effectively map domain-specific natural language to complex technical syntax locally.
āļø About PyCon DE:
PyCon DE is the leading conference on open-source Python applications in AI and data science. It brings together industry professionals, researchers, AI and data science practitioners, and software engineering communities, providing a unique platform for collaboration, knowledge sharing, and innovation.
The PyCon DE & PyData 2026 conference delivered an exceptional experience, fostering stronger connections within the Python community while showcasing the latest advancements in artificial intelligence and data science. Attendees enjoyed a diverse and engaging program of talks, workshops, and networking opportunities, further establishing the conference as a premier event for Python, AI, and data science enthusiasts across Germany.
PyCon DE 2027 will take place in Heidelberg from 19 to 23 April 2027.
Follow us:
ā¢ Newsletter: https://2027.pycon.de/newsletter/
ā¢ LinkedIn: https://www.linkedin.com/company/pyconde
ā¢ X: https://www.x.com/pyconde
Links:
ā¢ Conference website: http://pycon.de
ā¢ Other sessions: https://2026.pycon.de/talks/
The conference was organized by
ā¢ Python Softwareverband e.V.: http://pysv.org
ā¢ Pioneers Hub gemeinnĆ¼tzige GmbH: http://pioneershub.org
in collaboration with NumFOCUS Inc.: http://numfocus.org
If you enjoyed this session, please like, and subscribe to our channel for more insightful talks and discussions.
Share this video with your network to spread the knowledge!
Hashtags:
#Python #PyConDE #PyData #OpenSource #AI #DataScience #MachineLearning #SoftwareEngineering #LLMs #Community #Sovereignty
Acknowledgements:
Special thanks to all the volunteers and sponsors who made this event possible.
About:
Python Softwareverband e.V.:
PySV is a non-profit that promotes the use and development of Python in Germany through events, education, and advocacy, fostering an open Python community.
Pioneers Hub gemeinnĆ¼tzige GmbH:
is a non-profit fostering innovation in AI and tech by connecting experts and promoting knowledge exchange through events and collaborative initiatives.
NumFOCUS Inc.
supports open-source scientific computing by providing financial and logistical support to key projects like NumPy and Jupyter, promoting sustainable development and collaboration.
www.pydata.org
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.")
![Using Sensor Fusion and ML to Navigate Underground When GPS Fails [PyCon DE & PyData 2026]](https://i.ytimg.com/vi/uyrlnwzsW1U/mqdefault.jpg "Using Sensor Fusion and ML to Navigate Underground When GPS Fails [PyCon DE & PyData 2026]
š Recorded at PyCon DE & PyData 2026, 16.04.2026
https://2026.pycon.de/talks/LVJXK3/
š Watch Ćtienne Tremblay explain how to leverage sensor fusion and ML to maintain precise navigation in GPS-denied underground environments.
Speakers:
Ćtienne Tremblay
Description:
Underground navigation is challenging because GPS signals cannot penetrate subway tunnels, leaving smartphones to rely on imprecise cell tower mapping or Wi-Fi scanning with accuracy radii often exceeding one kilometer. To solve this, a system was developed that estimates location by fusing motion sensor data, train schedules, and sparse device locations. The core logic treats the problem as a sequence of events: by detecting when a train moves and stops, the system can count stations traveled from a known starting point.
The technical approach utilizes a two-stage machine learning pipeline. First, a Convolutional Neural Network (CNN) is trained on millions of unlabeled user trips using a pretext task to classify general motion modes (stationary, walking, or automotive) based on accelerometer and gyrometer data. Second, transfer learning is applied to a smaller, high-quality dataset of 300 manually annotated trips to refine a binary classifier that specifically identifies moving metro states. This model is converted to TensorFlow Lite and deployed on-device via Core ML for iOS and Android to ensure functionality during network outages.
A mixer module integrates the binary motion predictions with offline train schedules and any available high-accuracy device locations to resolve edge cases, such as trains stopping between platforms. The system achieves approximately 90% accuracy, with predictions typically within one station of the true location. To manage uncertainty, the user interface employs warning banners and asymmetric confidence intervals, acknowledging a bias toward late rather than early predictions. The entire training pipeline is managed using Vertex AI to handle complex dependency graphs and parallel testing.
āļø About PyCon DE:
PyCon DE is the leading conference on open-source Python applications in AI and data science. It brings together industry professionals, researchers, AI and data science practitioners, and software engineering communities, providing a unique platform for collaboration, knowledge sharing, and innovation.
The PyCon DE & PyData 2026 conference delivered an exceptional experience, fostering stronger connections within the Python community while showcasing the latest advancements in artificial intelligence and data science. Attendees enjoyed a diverse and engaging program of talks, workshops, and networking opportunities, further establishing the conference as a premier event for Python, AI, and data science enthusiasts across Germany.
PyCon DE 2027 will take place in Heidelberg from 19 to 23 April 2027.
Follow us:
ā¢ Newsletter: https://2027.pycon.de/newsletter/
ā¢ LinkedIn: https://www.linkedin.com/company/pyconde
ā¢ X: https://www.x.com/pyconde
Links:
ā¢ Conference website: http://pycon.de
ā¢ Other sessions: https://2026.pycon.de/talks/
The conference was organized by
ā¢ Python Softwareverband e.V.: http://pysv.org
ā¢ Pioneers Hub gemeinnĆ¼tzige GmbH: http://pioneershub.org
in collaboration with NumFOCUS Inc.: http://numfocus.org
If you enjoyed this session, please like, and subscribe to our channel for more insightful talks and discussions.
Share this video with your network to spread the knowledge!
Hashtags:
#Python #PyConDE #PyData #OpenSource #AI #DataScience #MachineLearning #SoftwareEngineering #LLMs #Community #Sovereignty
Acknowledgements:
Special thanks to all the volunteers and sponsors who made this event possible.
About:
Python Softwareverband e.V.:
PySV is a non-profit that promotes the use and development of Python in Germany through events, education, and advocacy, fostering an open Python community.
Pioneers Hub gemeinnĆ¼tzige GmbH:
is a non-profit fostering innovation in AI and tech by connecting experts and promoting knowledge exchange through events and collaborative initiatives.
NumFOCUS Inc.
supports open-source scientific computing by providing financial and logistical support to key projects like NumPy and Jupyter, promoting sustainable development and collaboration.
www.pydata.org
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.")
![Tracking Knowledge Diversity in LLM-Generated Responses. [PyCon DE & PyData 2026]](https://i.ytimg.com/vi/vGvXgpWFS_A/mqdefault.jpg "Tracking Knowledge Diversity in LLM-Generated Responses. [PyCon DE & PyData 2026]
š Recorded at PyCon DE & PyData 2026, 16.04.2026
https://2026.pycon.de/talks/P7NYXB/
š Watch Sarah Masud explore the risk of knowledge collapse and discover an open-source framework for tracking and preserving epistemic diversity in LLM-generated responses.
Speakers:
Sarah Masud
Description:
Measuring knowledge diversity in Large Language Model (LLM) responses addresses the problem of information redundancy, where models generate synonymous content across multiple prompts without providing new unique information. To quantify this, text is converted into sentences and grouped into clusters based on semantic similarity and mutual entailment using a BERT-based setup. To penalize random, non-coherent information, the approach employs data mining entropy and the Hill-Shannon diversity metric, which converts log-scale entropy into a linear scale for easier comparison.
Testing across 200 general knowledge topics and 27 models reveals that while model performance improves over time, a significant gap remains compared to the diversity of top 20 Google search results. Model size does not strongly correlate with knowledge diversity. Retrieval-Augmented Generation (RAG) improves diversity, particularly for smaller models, though the effectiveness of RAG varies based on the localization and grounding of the external knowledge source.
āļø About PyCon DE:
PyCon DE is the leading conference on open-source Python applications in AI and data science. It brings together industry professionals, researchers, AI and data science practitioners, and software engineering communities, providing a unique platform for collaboration, knowledge sharing, and innovation.
The PyCon DE & PyData 2026 conference delivered an exceptional experience, fostering stronger connections within the Python community while showcasing the latest advancements in artificial intelligence and data science. Attendees enjoyed a diverse and engaging program of talks, workshops, and networking opportunities, further establishing the conference as a premier event for Python, AI, and data science enthusiasts across Germany.
PyCon DE 2027 will take place in Heidelberg from 19 to 23 April 2027.
Follow us:
ā¢ Newsletter: https://2027.pycon.de/newsletter/
ā¢ LinkedIn: https://www.linkedin.com/company/pyconde
ā¢ X: https://www.x.com/pyconde
Links:
ā¢ Conference website: http://pycon.de
ā¢ Other sessions: https://2026.pycon.de/talks/
The conference was organized by
ā¢ Python Softwareverband e.V.: http://pysv.org
ā¢ Pioneers Hub gemeinnĆ¼tzige GmbH: http://pioneershub.org
in collaboration with NumFOCUS Inc.: http://numfocus.org
If you enjoyed this session, please like, and subscribe to our channel for more insightful talks and discussions.
Share this video with your network to spread the knowledge!
Hashtags:
#Python #PyConDE #PyData #OpenSource #AI #DataScience #MachineLearning #SoftwareEngineering #LLMs #Community #Sovereignty
Acknowledgements:
Special thanks to all the volunteers and sponsors who made this event possible.
About:
Python Softwareverband e.V.:
PySV is a non-profit that promotes the use and development of Python in Germany through events, education, and advocacy, fostering an open Python community.
Pioneers Hub gemeinnĆ¼tzige GmbH:
is a non-profit fostering innovation in AI and tech by connecting experts and promoting knowledge exchange through events and collaborative initiatives.
NumFOCUS Inc.
supports open-source scientific computing by providing financial and logistical support to key projects like NumPy and Jupyter, promoting sustainable development and collaboration.
www.pydata.org
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.")
