Software Engineering Daily

Interactive notebooks were popularized by the Jupyter project and have since become a core tool for data science, research, and data exploration. However, traditional, imperative notebooks often break down as projects grow more complex. Hidden state, non-reproducible execution, poor version control ergonomics, and difficulty reusing notebook code in real software systems make it hard to

The post Reinventing the Python Notebook with Akshay Agrawal appeared first on Software Engineering Daily.

AI agents have taken on a growing share of software development work, so much so that the hardest problems are shifting away from code generation towards something new, context. The challenge is now contextualizing why systems work the way they do, how architectural decisions were made, and the sources of truth that exist outside of

The post Organizational Context for AI Coding Agents with Dennis Pilarinos appeared first on Software Engineering Daily.

SED News is a monthly podcast from Software Engineering Daily where hosts Gregor Vand and Sean Falconer unpack the biggest stories shaping software engineering, Silicon Valley, and the broader tech industry. In this episode, they cover the viral rise of OpenClaw and its founder’s move to OpenAI, OpenAI’s exploration of ads inside ChatGPT, and Alibaba’s

The post SED News: OpenClaw Goes Viral, Mistral’s Compute Play, and the Agent Arms Race appeared first on Software Engineering Daily.

AI-assisted coding tools have made it easier than ever to spin up prototypes, but turning those prototypes into reliable, production-grade systems remains a major challenge. Large language models are non-deterministic, prone to drift, and often lose track of intent over long development sessions. Kiro is an AI-powered IDE that’s built around a spec-driven development workflow.

The post Amazon’s IDE for Spec-Driven Development with David Yanacek appeared first on Software Engineering Daily.

Enterprise IT systems have grown into sprawling, highly distributed environments spanning cloud infrastructure, applications, data platforms, and increasingly AI-driven workloads. Observability tools have made it easier to collect metrics, logs, and traces, but understanding why systems fail and responding quickly remains a persistent challenge. As complexity continues to rise, the industry is looking beyond dashboards

The post Engineering AI Systems for Autonomy and Resilience with Krishna Sai appeared first on Software Engineering Daily.