AI
Agent Scale Engineering: 5 Changes in 2026
Agent scale engineering changes the work around code before it changes the code itself. Models can now carry out longer tasks, but a product team still has to…
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Category: AI
How we build AI into real products: LLM integration, AI agents, retrieval, evaluation, and the product and cost decisions behind every AI feature.
AI
Gemini Agent Controls: 5 Checks Before You Delegate
Gemini agent controls matter before a team lets a workplace agent read documents, create tickets, or coordinate work across tools. Google’s new Gemini agent is built for that…
AI
OpenAI Decisions API: 5 Controls for Product Teams
OpenAI Decisions API gives product teams a narrower way to use a model. Instead of asking for open-ended text, an application can ask a defined question and receive…
AI
OpenAI Dots: 5 Essential Controls for Product Teams
OpenAI Dots changes the design problem for teams adopting AI agents. The product is built to keep working between conversations, across connected apps, with its own cloud computer.…
AI
LLM Integration: Adding Language Models to Your Existing Product
How we add language model features to an existing product: swappable models, retrieval over your data, structured outputs, evals in CI and production safeguards.
AI
Generative AI Development for Image, Video, Speech and Music
How we put image, video, speech and music generation into products: model and pipeline choice, safety layers, rights and provenance, queueing and GPU cost.
AI
AI App Development: What Models Do Well and How to Ship Them
Which problems language models actually solve well, how an AI feature is built, evaluated and budgeted, and how we take it from prototype to production.
AI
AI Agent Development: Agents That Take Real Actions, Safely
When an agent is warranted and when a fixed workflow is better, and how we design tools, approvals, sandboxes, scenario evals and audit logs for agents that act.