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12 articlesThe Anatomy of an Agent Harness
The model is almost interchangeable — the harness is what determines whether your AI agent works in production. A breakdown of the six core components every production-grade agent harness needs.
How AI Agents Actually Learn Over Time
AI agents can improve at three distinct layers—model weights, harness code, and runtime context—and most teams are only using one of them. Here's how to build the feedback loops that let agents compound in quality over time.
Context Engineering for Personalization: How to Build Long-Term Memory Into AI Agents
Building truly personalized AI agents requires more than a large context window. A structured memory lifecycle — inject, distill, trim, consolidate — is what separates agents that remember from agents that reset.
Routines and Handoffs: The Two Primitives Behind Every Reliable Multi-Agent System
Most multi-agent failures trace back to leaky plumbing, not bad models. Learn how routines and handoffs — two simple primitives — give you the structure to build reliable, production-grade agent systems.
Measuring AI Agent Autonomy in Production: What the Data Actually Shows
Large-scale production data reveals counterintuitive patterns in AI agent autonomy: experienced users approve more AND interrupt more, agents initiate oversight at 2x the rate of humans, and only 0.8% of actions are truly irreversible.
Building Effective AI Agents: Patterns That Actually Work in Production
Most AI agent projects fail because engineers reach for complexity before they've earned it. A practical guide to the mental models, patterns, and operational principles that separate reliable agents from ones that hallucinate and loop.
Going Viral on Twitter by Reverse-Engineering The Algorithm
Gain insights into Twitter's recommendation algorithm through an analysis of its open-source code, revealing the mechanisms behind content visibility and virality. Align content strategies with the algorithm's core logic for maximum engagement.
Organizational Economics: How Do Structure and Management Style Affect Performance?
An organization's structure and management directly impact its performance. This analysis of real-world cases reveals how good organizational practices solve problems of coordination and incentives, enhance efficiency, and determine business success or failure.
Jenni Romaniuk: Building Distinctive Brand Assets
Distinctive brand assets are the core of brand identity, encompassing elements like colors, logos, and sounds that help consumers quickly recall a specific brand without its name. By systematically creating and consistently using these assets, brands can stand out from the competition and form lasting memory structures.
Inspired: How to Create Tech Products Customers Love (2017) by Marty Cagan
Marty Cagan's *Inspired* provides essential insights into building tech products that resonate with customers. The article breaks down key practices in product management, emphasizing team dynamics, vision clarity, and the importance of experimentation, illustrated with examples from industry leaders like Amazon and Google.
The Design of Everyday Things by Don Norman
Everyday objects often frustrate users due to poor design. Don Norman emphasizes that design should make actions obvious, highlighting the importance of discoverability and understanding in everyday interactions. The article examines how effective design communicates necessary actions without reliance on labels, using the example of "Norman doors" to illustrate common design pitfalls.
Competition Demystified: A Radically Simplified Approach to Business Strategy
Competitive advantage is the foundation of effective business strategy, shaped by the presence or absence of barriers to entry. This principle influences how companies navigate market dynamics and respond to competition, providing a clear framework for strategic decision-making.
About Tian Pan
I'm Tian Pan, an engineer-founder focused on agentic engineering — building autonomous AI systems and scaling engineering teams. I write practical guides on system design, technical leadership, and shipping with AI agents. Previously an early engineer at Uber, Brex, and IoTeX.
