2+ day, 1+ hour ago   (1647+ words) Databricks disk cache speeds up repeated reads from curated Parquet or Delta tables, but it works best with good table design and partitioning. In many analytics platforms, there are performance issues that do not always come from complex transformations. Sometimes…...

1+ day, 20+ hour ago   (223+ words) Learn in this article how to treat LLM output as unknown until runtime schema validation proves it safe for typed application logic. The practical goal is a pipeline in which model output becomes domain data only after passing a runtime…...

2+ day, 19+ hour ago   (897+ words) Apache Flink on the IBM mainframe connects real-time processing with core systems, enabling hybrid cloud and AI without full migration. A few months ago, I wrote about integrating Apache Kafka with mainframe systems. The blog covered various real-world examples across…...

3+ day, 25+ min ago   (731+ words) This piece covers the managed AI teammate apps, the open-source runtimes you host yourself, and the developer frameworks you write code. Before the table, it helps to sort these into buckets, because comparing CrewAI to Grok Bot is like comparing…...

4+ day, 2+ hour ago   (610+ words) Learn how SQL Server 2025 memory-first indexing can accelerate hybrid transactional and analytical workloads by reducing disk I/O and latency. Modern database environments rarely run a single type of workload. Most production systems handle both transactional operations and analytical queries…...

4+ day, 23+ hour ago   (722+ words) Databricks Lakebase introduces database branching, giving each agent an isolated workspace to safely experiment, test changes, and merge validated updates. There's an awkward moment in every agentic data project. The agent works. It writes decent SQL, it reasons about schema,…...

4+ day, 22+ hour ago   (708+ words) Single AI agents fail during incidents. Four specialized agents — supervisor, telemetry, reasoning, action — handle observability more reliably. Usually it doesn't fail catastrophically. It fails quietly, in ways that are hard to debug. And quiet failures during incident response are the…...

5+ day, 25+ min ago   (1022+ words) Learn how to test, monitor, and deploy reliable agentic AI and multi-agent systems in enterprise environments using modern testing and CI/CD strategies. With industry analysts recording a massive surge in multi-agent system deployments, including a staggering 1,445% increase in enterprise…...

5+ day, 19+ hour ago   (696+ words) Past ~20-30 tools, sending every schema every turn hurts cost and accuracy. A lexical scorer plus a registry-search hatch fixes most of it — no embeddings needed. I stumbled onto this pattern while building agents with Deep Agents, watching a tool registry…...

6+ day, 2+ hour ago   (814+ words) Learn how to build a production-ready multi-agent AI framework in Python that improves reliability, reduces hallucinations, and scales enterprise LLM workflows. Through these failures, I realized the core problem: we are expecting a single inference step to manage an entire…...