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A second image-generation pass became a model-composition tool—and made local inference, memory management and extensibility central to creative control.

Dagger’s approach to coding agents starts with their working environment: isolate parallel work, preserve reusable setup, and let humans inspect what happened.

A research agent’s growing tool history turns context into an engineering problem—one that reaches into retrieval, multi-agent coordination, memory, and the architecture around the model.

From CAD operations to code edits, Cursor’s early development showed why useful generation needs context, tools, and a workflow people can inspect and steer. This historical snapshot accompanies the original recording published August 22, 2023.

Configured cloud computers let agents run applications, demonstrate changes, and work in parallel. The harder handoff is turning that output into software people can confidently ship.

A materials search engine needs generators, progressively tougher evaluations, experimental feedback, and chemists who can recognize missing requirements.

How tokenization, filtering, data mixtures, and training rights shape a model’s knowledge, deployment costs, and benchmark results.

Generating tests is one step toward a larger goal: keeping specifications, tests, and code aligned, with developers deciding what the software should do.

Part 2 of the NVIDIA Brev and Dynamo conversation: adapting inference to changing workloads, giving agents access to compute, and distinguishing longer runs from useful autonomous work.

Apps SDK gives developers an interface inside ChatGPT. AgentKit brings workflow design, evaluation, and deployment together—with consequential limits at launch.

Part 1 of 4 follows developers’ first reactions to OpenAI’s announcements: less conversation plumbing, more tools, and practical questions about billing, context, control and reliable action.

Part 3 follows expense assistants, browser agents, code search, and open models through the practical questions behind DevDay: usable context, reliable outputs, and responsibility for automated actions.