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Can AI help modernize legacy automotive C++ code?
C++ code can pose a significant challenge in modernization efforts. That's particularly troublesome for the automotive industry which practically runs on the language. How might AI help us? In this blog post, Henning Strüber explains how CodeConcise, a tool developed at Thoughtworks, helped us accelerate the modernization of a C++ codebase for a client.
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Black box reverse engineering
Usually, one of our approaches to accelerating legacy modernization with AI is to use it to accelerate the reverse engineering part first, feed AI with the existing code and then let it help us create a comprehensive description of the application’s functionality, which can be used in the forward engineering. But what if we don’t have the code, or it’s so messy that it’s useless? How can Generative AI accelerate reverse engineering in this case?
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AI evals for MCP in AIOps
As AI agents in operations shift to autonomous decision-makers through the Model Context Protocol, they gain powerful access to logs, metrics, traces, and runbooks, along with new risks. AI evaluations embedded in these workflows provide essential trust, safety, and accountability. They combine automated metrics, LLM-driven reasoning checks, and expert human reviews to ensure relevance and reliability. This layered approach delivers visibility and governance for complex operational decisions. The result is AI that supports operations with confidence, safety, and oversight.
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Ephemeral test environments: Kill your darlings
What happens when you need to scale your tests? Ephemeral test environments can help. In this interview with Thoughtworks' Effy Elden, we explore when they're useful, how they work, and compare them with the related technique, continuous previews.
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Martin Fowler, Chief Scientist at Thoughtworks, is a world renowned author and speaker, and a pioneer of agile software development.
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Research, review, rebuild: Intelligent modernization with MCP and strategic prompting