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.

China’s Great Firewall is often spoken about but is rarely understood. It is one of the most sophisticated and opaque censorship systems on the planet, and it shapes how over a billion people interact with the global internet, influences the design of privacy and proxy tools worldwide, and continues to evolve in ways that challenge

The post Inside China’s Great Firewall with Jackson Sippe appeared first on Software Engineering Daily.

LLM -powered systems continue to move steadily into production, but this process is presenting teams with challenges that traditional software practices don’t commonly encounter. Models and agents are non-deterministic systems, which makes it difficult to test changes, reason about failures, and confidently ship updates. This has created the need for new evaluation tooling designed specifically

The post Optimizing Agent Behavior in Production with Gideon Mendels appeared first on Software Engineering Daily.

AI-assisted programming has moved far beyond autocomplete. Large language models are now capable of editing entire codebases, coordinating long-running tasks, and collaborating across multiple systems. As these capabilities mature, the core challenge in software development is shifting away from writing code and toward orchestrating work, managing context, and maintaining shared understanding across fleets of agents.

The post Gas Town, Beads, and the Rise of Agentic Development with Steve Yegge appeared first on Software Engineering Daily.