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Engineering culture, developer tooling and the working lives of the people who ship software, from The Silicon Ledger.
As Chip Huyen returns to P99 CONF, her framework for reducing AI inference costs without hardware upgrades remains relevant—though the rise of agents and reasoning models has shifted how practitioners think about the problem.
An AI system can return a successful response, pass all evaluation metrics, and still deliver incorrect information to customers. Understanding why requires looking beyond code changes to the execution trace itself.
As Model Context Protocol spreads across enterprise infrastructure, security experts are realizing that the vulnerability isn't in the protocol itself—it's in how organizations grant access to AI agents.
OpenAI has recruited the creators of Git AI, a tool that quantifies code output from AI agents, to help enterprises understand the business value of its Codex product.
Anthropic's AI-Native SDLC Playbook correctly identifies that code generation is no longer the constraint in software development, but organizations need adaptable approval processes tailored to different types of changes rather than rigid, universal workflows.
A developer has created Stonkfly, an open-source project that simulates a male fruit fly's neural system to autonomously trade digital assets based on candlestick charts and dopamine-driven reinforcement signals.
OpenAI has released its Agents API in public beta, enabling developers to run autonomous agents for extended periods without building custom infrastructure. The launch coincides with the company pausing new Pro plan signups due to demand for its GPT-6 Astra model.
As artificial intelligence transforms enterprise software, Dynatrace and Arize AI are converging observability platforms to help operations teams move from detecting problems to acting on them automatically.
