Before GTC 2026 Announcements Land: Enterprise AI Platform Readiness Checklist
Use keynote season to improve model lifecycle, capacity planning, and governance so new hardware/software updates become deployable value.
Writes about AI, product strategy, and the intersection of technology and business.
101 articles
Use keynote season to improve model lifecycle, capacity planning, and governance so new hardware/software updates become deployable value.
A practical operating model for teams adopting GitHub Copilot’s expanded agentic features in JetBrains without losing code ownership.
Practical architecture patterns for using Gemini Embedding 2 in search, RAG, and recommendation pipelines.
A practical operating model for turning GitHub CLI-triggered Copilot review into auditable, low-noise engineering governance.
How engineering teams can use issue fields to improve prioritization, automation, and delivery governance.
A practical drill program for testing whether coding-agent workflows can resist malicious open-source suggestions.
Google is embedding assistant capabilities directly into browser workflows, forcing teams to redesign governance, observability, and data controls.
A practical operating model for teams adopting new GitHub Copilot agentic capabilities in JetBrains IDEs.
A practical governance design for rolling out GPT-5.4 in Copilot without turning pull request reviews into chaos.
How teams can safely adopt per-thread model selection in pull request workflows without losing review quality.
How teams can combine GPT-5.4, editor policy, and review telemetry to scale AI-assisted coding without losing control.
A practical operating model for teams using Figma MCP layer generation in VS Code while preserving design-system integrity and delivery speed.
A practical framework for integrating coding agents into Scrum without losing ownership, estimation quality, or review accountability.
How engineering leaders can safely scale GPT-5.4-powered Copilot with policy controls, metrics, and review discipline.
A contract-first operating model for teams using Figma MCP generated layers directly inside engineering workflows.
How built-in browser translation AI changes multilingual publishing pipelines, QA strategy, and compliance review.
A practical operating model for teams adopting Copilot coding agents, Jira integration, and model selection in pull requests.
How teams combine model routing, session filters, PR comment controls, and Jira-linked coding agents without losing auditability.
IDE workflows are rapidly shifting from autocomplete to autonomous task execution and design-to-code collaboration.
With model selection and agent session controls expanding in GitHub workflows, engineering teams must treat AI usage in pull requests as a governed production process.