Gregor Schumacher, Sujay Joshy & Marcel Gocke
New AI-Centric SDLC: Rethinking Software Development with Knowledge Graphs
#1about 1 minute
Rethinking productivity beyond just writing code faster
Software engineering productivity gains come from optimizing the entire process, as coding itself is only a small fraction of the total work.
#2about 3 minutes
Learning from failed large context window experiments
Attempts to refactor a large application by feeding the entire codebase into an LLM failed due to the inability to handle vast corporate context.
#3about 2 minutes
The inadequacy of vector databases for code
Vector databases are not ideal for codebases because similar code snippets and branches produce nearly identical embeddings, making it difficult to retrieve precise information.
#4about 4 minutes
Using knowledge graphs to model code structure
By representing code as a graph of interconnected nodes like classes and methods, it becomes possible to precisely query and retrieve specific call chains for LLM context.
#5about 1 minute
Creating a unified platform for corporate knowledge
A centralized platform was built to ingest code, documentation from tools like Jira and Confluence, and other data into a single, queryable knowledge graph.
#6about 4 minutes
Managing autonomous agents with graph-based systems
A knowledge orchestration platform provides agents with the right context, while a "knowledge graph of thought" audits their actions for reproducibility and control.
Related jobs
Jobs that call for the skills explored in this talk.
Matching moments
28:49 MIN
How AI will reshape software development and documentation
Coffee with Developers - Scott Chacon on growing GitButler and the future of version control
04:13 MIN
The impact of GenAI on team collaboration and culture
The Future of Developer Experience with GenAI: Driving Engineering Excellence
34:19 MIN
A final summary of Stack Overflow's AI journey
The Data Phoenix: The future of the Internet and the Open Web
26:34 MIN
Q&A on AI limitations and practical application
How to become an AI toolsmith
09:55 MIN
Shifting from traditional code to AI-powered logic
WWC24 - Ankit Patel - Unlocking the Future Breakthrough Application Performance and Capabilities with NVIDIA
36:52 MIN
The future of developer tools in an AI-driven world
Are frameworks like React redundant in an AI world?
22:03 MIN
Exploring other AI use cases in the development lifecycle
Engineering Velocity in the Age of AI: Lessons from Mobile CI/CD
21:20 MIN
Using human knowledge to overcome AI's limitations
Collaborative Intelligence: The Human & AI Partnership
Featured Partners
Related Videos
31:39Livecoding with AI
Rainer Stropek
39:11Agents for the Sake of Happiness
Thomas Dohmke
28:09The AI-Ready Stack: Rethinking the Engineering Org of the Future
Jan Oberhauser, Mirko Novakovic, Alex Laubscher & Keno Dreßel
29:18Getting to Know Your Legacy (System) with AI-Driven Software Archeology
Markus Harrer
04:17Leapter: The Reinvention of Software Development? A Future Built On AI Generated Code.
Robert Werner
27:12Beyond the IDE: A new era of agent collaboration
Ryan J. Salva
27:43Reimagining the Developer Experience: The AI Advantage
Anu Bharadwaj & Tobias Schlottke
32:26Bringing the power of AI to your application.
Krzysztof Cieślak
From learning to earning
Jobs that call for the skills explored in this talk.
Team Lead and Senior Software Engineer with focus on AI
Dynatrace
Linz, Austria
Senior
Java
Team Leadership
Senior Systems/DevOps Developer (f/m/d)
Bonial International GmbH
Berlin, Germany
Senior
Python
Terraform
Kubernetes
Elasticsearch
Amazon Web Services (AWS)
AI Engineer / Machine Learning Engineer / KI-Entwickler
Agenda GmbH
Remote
Intermediate
API
Azure
Python
Docker
+10
AI & Software Engineer - KI-gestützte Softwareentwicklung mit Zukunft
BS Gottschall GmbH
€80K
Senior
API
.NET
Azure
React
+6