Keep Human Judgment in AI: The Hidden Signal in Automation
Automation scales, but trust comes from principled pauses and visible lifelines. Here’s how to keep human judgment in AI without losing velocity.
Continuity-first engineering to prevent AI agent context loss
Continuity-first agentic systems anchor today’s changes to yesterday’s decisions with memory and rationale. Learn how to prevent AI agent context loss using constraints, ledgers, and fail-closed workflows.
When to Use Multi-Agent LLMs: Choose Structure Over Orchestration
Most demos confuse delegation with intelligence. This piece explains when to use multi-agent LLMs—only when distinct value functions conflict—and how to design arbitration to resolve real tradeoffs.
Design for Outcomes: Make Content Machine-Actionable
Design for outcomes, not clicks. Learn how to make content machine-actionable by encoding intent and exposing callable actions so agents can complete tasks end-to-end.
Build Resilient LLM Systems: Proven Patterns for Reliability
LLMs fail in quiet, language-driven ways. This piece shows how to build resilient LLM systems with observability, agent introspection, and variability-aware tests so silent breaks surface before production.
Align Incentives: Reward Responsible AI Use
AI use shouldn’t be punished or mandated blindly. Learn how to reward responsible AI use with clear guidelines, verification, and evaluation that center human judgment.
AI-assisted authorship attribution guidelines: clear roles and credit
This sets out AI-assisted authorship attribution guidelines that separate authorship (why) from production (how) with clear, role-based disclosures. Use a 'human-authored, AI-produced' framing and the value-without-AI test to keep credit defensible.
Accelerate project setup with AI: A proven workflow to start faster
Use AI to accelerate project setup so you start faster with clean outlines and minimal boilerplate, while staying in control through review and tweaks. This repeatable workflow reduces startup friction and keeps your focus on what matters.
Get critical AI feedback: turn mimicry into rigorous critique
When you guide tone and demand specifics, AI shifts from mimicry to evaluation. This protocol helps engineers get critical AI feedback that strengthens designs.
AI self coaching prompts: a 60-second check-in to reset focus
Use AI self coaching prompts as a context-aware mirror to cut decision fatigue and regain momentum. In one minute, get a personalized nudge and choose your next step.