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📘 Playbook
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Aug 20, 2026
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6 min read
A practical guide to deciding where agents get autonomy and where software keeps control.
Aug 13, 2026
5 min read
A five-layer operating model for leaders
+1
Aug 10, 2026
How mapping tasks, decisions, and handoffs reveals where AI can create real value.
Aug 6, 2026
4 min read
A practical framework for using project directories, taxonomy files, templates, assets, and approval rules to keep AI outputs consistent and reliable.
Aug 3, 2026
3 min read
Why vague inputs produce polished misses, while clear goals, context, and criteria produce useful results.
Jul 27, 2026
How an AI application moves from development to production through testing, controlled release, monitoring, and rollback.
Jul 9, 2026
Why AI applications need different database layers for memory, retrieval, operations, and analytics
Jul 6, 2026
Why building an AI-native product is less about one big launch and more about moving through the right sequence of decisions
Jul 3, 2026
Why deployment choices are becoming part of the AI app architecture decision.
Jun 29, 2026
Why modern AI applications require a wider stack than a model, an interface, and an API
Jun 26, 2026
Why reliable AI agents need maintained workbenches, clear guardrails, and regular pruning.
Jun 23, 2026
Why founders and builders need a simple path from idea to working AI app.
Jun 22, 2026
A founder-led walkthrough of Anthropic's design canvas — what it is, when to reach for it, and how to fit it into a real build workflow without burning your plan limits.
Jun 19, 2026
Why production agents need workflow design, not just better models.
Jun 15, 2026
2 min read
Why AI memory helps, but source-of-truth governance matters more.
