Agentic development as a process, not a product, and other expensive failures of understanding
Research Report 6: Agentic Shopping is Complicated and Contingent
This is the sixth in a series of short reports that help business, education, and policy leaders understand the technical details of working with AI through rig
Skills, forks, and self-surgery: how agent harnesses grow
Claude Code, NanoClaw, and Pi take radically different approaches to harness extensibility. The tradeoff is always safety vs. agent agency.
How to Train Your Agent: Building Reliable Agents with RL — Kyle Corbitt, OpenPipe
Agentic Product Development - Erlend Sogge Heggen
We are all Product Engineers now | Seldo.com
Agents are eating the software development lifecycle from the bottom up — code generation already gone, review and ops following fast. What remains is figuring out what people actually want, which can't be automated or scaled. That job is called product engineering, it pays $240k, and nobody's training for it.
Signals: Toward a Self-Improving Agent | Factory.ai
Traditional product analytics tell you what happened. Session duration, tool calls executed, completion rates. But they...
Agent experience: How to design products that agents can actually use — WorkOS
What engineers and founders need to know about designing APIs, tools, and interfaces for agent-driven workflows
Agentic AI Governance: Securing Autonomous AI Agents in Enterprise
When AI agents start making decisions, calling tools, and coordinating with other agents without waiting for human approval, the governance playbook most...
A guide to the anatomy of effective commerce agents | Claude by Anthropic
The architecture, latency & cost techniques, and eval practices for agents that make it easier to buy and sell online.
Harness engineering: leveraging Codex in an agent-first world
By Ryan Lopopolo, Member of the Technical Staff
Harness engineering: leveraging Codex in an agent-first world
By Ryan Lopopolo, Member of the Technical Staff
Adoption and Impact of Command-Line AI Coding Agents: A Study of Microsoft's Early 2026 Rollout of Claude Code and GitHub Copilot CLI
Organizations rolling out agentic command line tools like Anthropic's Claude Code and GitHub's Copilot CLI need to know who will try them, who will keep using them, and whether the tools produce enough output to justify their cost. At organizational scale, token spend can run into millions of dollars annually, so misreading adoption, retention, or impact can make a rollout expensive without changing engineering velocity. Studying tens of thousands of engineers at Microsoft over its early-2026 rollout, we find that first use spread primarily through social networks, retention was associated more with engineers' coding activity than with demographics, and adopters merged roughly 24% more pull requests than they would have otherwise. We use merged pull requests as our proxy for output -- acknowledging that a merged PR is not the same as the value it delivers -- and the lift persists across our four-month window. These results suggest that CLI coding agents are neither uniformly adopted nor mere novelty effects and that organizations should treat visible peer use as central to rollout strategy.
StrongDM Software Factory
StrongDM's field notes on non-interactive agentic development: specs + scenarios, validation harnesses, feedback loops, and the supporting components.
StrongDM Software Factory
StrongDM's field notes on non-interactive agentic development: specs + scenarios, validation harnesses, feedback loops, and the supporting components.
Agentic AI Governance: A Strategic Framework for Autonomous Systems
Agentic AI is moving from chat to action. Learn how to govern autonomous systems using the "Digital Contractor" framework and the 3-Tiered Guardrail system.
