Tag: sdlc
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programmers are managers now
The central task becomes describing an objective precisely enough for the system to divide it, establishing the rules under which the agents operate, and judging whether their collective output belongs in the codebase. 🔗 Claude Code Turns Software Development Into a Management Job
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Inside OpenAI’s agentic software factory
We’re talking about roughly a 10x increase in load on some systems. At most companies, that kind of growth might happen over two or three years. At OpenAI, we see it in about six months. 🔗 Inside OpenAI’s agentic software factory
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The Interfaces Are Arriving
For an engineering organization, the immediate consequence is reuse. An MCP server for an internal ticketing system can serve every compatible IDE, chat application, and agent. Models and hosts will keep changing; the interface contract, server implementation, schemas, and authorization wiring can endure. The integration becomes an asset shared across applications. Language servers followed the…
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Reframing the AI-native SDLC in terms of stewardship boundaries
To make AI agents succeed, we must inject very clear, tightly constrained context. This is where the platform patterns we popularized in Team Topologies become essential. A well-designed internal platform acts like a “vending machine,” providing self-service, reliable access to clean data, APIs, and operational capabilities. By reducing cognitive load on human teams and narrowing…
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Enterprise Java apps are much more than just code, AI benchmarks don’t measure the Java SDLC enough
There’s countless dependencies in other frameworks and libraries, plus the build pipeline and even production platform are part of the app. Enterprise Java applications frequently span hundreds or thousands of modules connected through Maven or Gradle builds, Spring dependency injection, Jakarta EE services, annotation processors, generated code, legacy XML configuration, container orchestration, proprietary build plugins,…

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