VP of Engineering
David writes about engineering culture, team building, and leadership — the human side of building technology companies. With experience leading engineering at both remote-first and hybrid organizations, he brings a practical perspective on how to attract, retain, and develop top engineering talent. His writing on 1-on-1 meetings, remote management, and career frameworks has been shared by thousands of engineering leaders.
In 2026, inference—not training—became the runaway cost center. Here’s how top teams are redesigning stacks, budgets, and reliability to ship AI features without blowing the margin.
David Kim
Agent features are easy to demo and hard to operate. Here’s how product teams can build reliable, governable agentic workflows that actually move core metrics.
David Kim
Inference has become the dominant AI cost center. Here’s how leading teams are redesigning stacks—models, routing, caches, and GPUs—to slash spend without hurting UX.
David Kim
In 2026, the winners aren’t the teams with the smartest agents—they’re the teams with the most reliable ones. Here’s the practical stack to ship and govern AI agents at scale.
David Kim
Agentic AI is moving from demos to production. Here’s the 2026 playbook: reliability metrics, cost controls, evals, and governance that keep autonomous workflows shippable.
David Kim
Agentic AI is moving from wow-factor to workflow. Here’s how 2026 startups are building reliable, governed agents that survive security reviews and drive real ROI.
David Kim
In 2026, the winning startups aren’t adding AI features—they’re rebuilding operations around agents, evals, and governance. Here’s the playbook and stack.
David Kim
In 2026, leadership is the ability to ship with agent-heavy workflows without sacrificing security, quality, or accountability.
David Kim
AI agents are moving from demos to production. Here’s how top teams are building identity, guardrails, and observability so agents can ship work safely at scale.
David Kim
In 2026, the winners aren’t shipping bigger models—they’re shipping tighter eval loops, safer tool use, and agentic ML ops that keeps quality rising after launch.
David Kim
Agents are leaving the demo stage. Here’s how modern product teams design, price, and operate AI-native workflows that ship outcomes—not prompts.
David Kim
Agentic AI is turning software into a spend-and-risk surface area. Here’s the 2026 playbook for shipping agents that are affordable, auditable, and dependable.
David Kim
The practical playbook for building high-performing distributed engineering teams, covering async communication and team rituals.
David Kim