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Every time you hand a task to an agent, you pay a hidden cost.
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AI makes first drafts faster.
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Code got cheaper.
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Getting agents to start is trivial.
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Agent systems that work on day one don't automatically keep working.
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What changes when one engineer runs a fleet
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Multi-agent coordination is an organizational design problem wearing an engineering costume
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What happens when optimization becomes a loop you design, not work you do
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AI demos feel instant.
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A 95% accurate model still requires 100% of your review attention.
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Why giving agents more tools makes them worse—and how to design tool sets that actually work
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The hard part was never getting code written
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What happens to software development when the work doesn't stop when you do
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It compounds faster than technical debt, and it's invisible until it isn't
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The reckoning comes at the maintenance window
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Why reviewing every agent output is killing your productivity—and what to do instead
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Why the best AI work you'll ever do isn't the task—it's what you leave behind
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Why one capable agent beats a swarm of specialists
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From Always-On to Event-Driven AI Assistants
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Why Your Agent Keeps Forgetting and What Actually Works
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Isolation as a First Principle in Agentic Development
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The Most Important Role Nobody's Hiring For
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Scheduled AI as Creative Partner
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Building Specialized Agents from One Model
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From Reasoning Engine to Operating System
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Why Prompts Are the New Source Code
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Why Your Coding Assistant Is Actually a Reasoning Engine
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Why Teams Can't Just Multiply Gas Town
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2025 in review, and what comes next
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We built the voice.
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When Code is Cheap, Ownership Becomes Capital
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Managing AI Development at Scale (Without Shipping Vibe-Coded Slop)
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Project Management in the Age of AI Agents
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Why AI Demands Context-Driven Development
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The revolution in software development starts with clarity