Data engineers should be working faster than ever. AI-powered tools promise to automate pipeline optimization, accelerate data integration and handle the repetitive grunt work that has defined the profession for decades.Yet, according to a new survey of 400 senior technology executives by MIT Technology Review Insights in partnership with Snowflake, 77% say their data engineering teams' workloads are getting heavier, not lighter.The culprit? The very AI tools meant to help are creating a new set of problems.While 83% of organizations have already deployed AI-based data engineering tools, 45% cite integration complexity as a top challenge. Another 38% are struggling with tool sprawl and fragmentation."Many data engineers are using one tool to collect data, one tool to process data [...]
One year after emerging from stealth, Strella has raised $14 million in Series A funding to expand its AI-powered customer research platform, the company announced Thursday. The round, led by Bessemer [...]
Chronosphere, a New York-based observability startup valued at $1.6 billion, announced Monday it will launch AI-Guided Troubleshooting capabilities designed to help engineers diagnose and fix producti [...]
Egnyte, the $1.5 billion cloud content governance company, has embedded AI coding tools across its global team of more than 350 developers — but not to reduce headcount. Instead, the company continu [...]
AI coding, vibe coding and agentic swarm have made a dramatic and astonishing recent market entrance, with the AI Code Tools market valued at $4.8 billion and expected to grow at a 23% annual rate. [...]
A San Francisco-based startup has demonstrated what it calls a breakthrough in hardware development: an artificial intelligence system that designed a fully functional Linux computer in one week — a [...]
The software industry is racing to write code with artificial intelligence. It is struggling, badly, to make sure that code holds up once it ships.A survey of 200 senior site-reliability and DevOps le [...]