The technical limitations that created the divide between the inner and outer loops are being solved just in time for agentic workflows to make merging them a necessity.
Tested K8s 1.35's four key features on Azure VM: zero-downtime pod resizing, gang scheduling, structured auth, and node capabilities. All scripts and configs on GitHub.
A significant portion of the front-end performance issues that arise are not due to the frontend at all but to the back-end APIs, dependencies, and infrastructure.
TOON and TRON reduce token consumption by removing JSON's repetitive keys and delimiters, with TOON for tabular data and TRON for schema-stable agent flows.
Learn essential network fundamentals that every backend developer needs to master. Understand TCP/IP, DNS, HTTP protocols, and debugging to build better applications.
S/4HANA migrations break custom ABAP code and interfaces unless you proactively refactor code, SQL, and integrations to support the new data model and semantics.
Bridge the gap between Big Data and production ML. Learn to integrate Azure Databricks with Azure Machine Learning for a seamless, scalable end-to-end MLOps workflow.
Intelligent caching and model routing reduced our AI API costs from $12,340 to $3,680 per month. Production-tested optimizer. Open source. MIT license.
A practical engineering guide to integrating an AI chatbot into your application, covering architecture, backend flow, NLP handling, security, testing, and deployment.
Explore Google Gemini 3 API’s architecture, native multimodality, and agentic workflows with a hands-on guide to building a production-ready multimodal AI.
Permission-aware retrieval ensures that the assistant uses only allowed information. A context graph enforces access control to prevent cross-team leakage.