Microsoft Research Offers Open Source AI Simulation Market
Microsoft Research launched Magentic Marketplace, an open source simulation environment that allows developers to study how AI agents negotiate, transact and collaborate under real-world market dynamics. This project uses lessons from AutoGen to test communications protocols like MCP and A2A to understand the safety and reliability required before public agent marketplaces go live. TNS Senior Editor Richard MacManus explains what researchers have learned thus far from the simulations.
In other technology issues we’re exploring today:
Concerned with security issues, Clickhouse explored rewriting its large C++ codebase in Rust. It chose an incremental approach to integrating Rust modules for specific functionalities like hashing and Delta Lake support. TNS Senior Editor Joab Jackson writes that while Rust offers better memory safety, the Clickhouse team uncovered a variety challenges to changing their codebase.
Pulumi’s Neo AI agent is a new service that automatically identifies and fixes policy violations across cloud infrastructure at scale. It can tackles backlogs that exceed 100,000 issues for companies pursuing HITRUST or FedRAMP certification. TNS Senior Editor Darryl Taft reports on how this new offering can help platform teams.
Many engineering teams feel they are behind on AI, but the truth is that we are all flying a plane that is still being built.
Reliability engineers are the quiet force that keeps modern software running. After decades of refining practices on deterministic systems, many teams are chasing yet another “nine” beyond 99% uptime. But the AI era, especially LLM-backed features, changes the game. Outputs are non-deterministic, data pipelines shift underfoot, and key components behave like black boxes. As a result, many of the...
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Look: Developers Want to Build, Not Battle Friction
A new survey shows that AI and automation are creating new opportunities, but engineers remain burdened by maintenance, technical debt and tool sprawl.
When it comes to AI, says Keith Ballinger of Google, developers need to slow down to speed up the process: write clear guides for AI agents, focus on architecture and create a project plan.
