Where AI-native startups are heading and how to prepare
Where agentic AI for founders heads next — longer horizons, agent fleets, ambient computer use — and the durable investments to make in your startup now.
7 min read
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Where Claude Code in Large Codebases Goes Next
Agentic coding is moving toward longer-horizon autonomy and coordinated agent fleets. Where Claude Code in large codebases is heading and how to prepare now.
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How to Measure Claude Code Success at Scale
The metrics and signals that prove Claude Code is working in a large codebase — lead time, change-failure, test-integrity — and the vanity numbers to ignore.
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How to measure if your AI-native startup is working
The metrics that prove an AI-native startup works — cycle time, defect escape, review-catch rate, eval pass rate, and cost per successful outcome.
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Claude Code Walkthrough: A Bug to Shipped Fix
A realistic end-to-end Claude Code use case: tracing an intermittent double-charge bug through a large codebase from vague report to verified, shipped fix.
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From bug report to shipped fix: a Claude Code walkthrough (Founders Playbook AI Native Startup)
A realistic end-to-end Claude Code walkthrough — vague complaint to reviewed, tested, deployed fix with MCP grounding and evals in an AI-native team.
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Risk management for AI-native founders: blast radius first
Contain agent failures in an AI-native startup — Claude failure modes, blast-radius thinking, sandboxing, and guardrails that keep velocity high.
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Risk Management for Claude Code in Big Codebases
Failure modes, blast radius, and containment patterns for running Claude Code safely in a large codebase — least privilege, diff caps, and verification gates.
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Hiring for an AI-native startup: skills founders need now
The skills and roles founders must hire for to run an AI-native startup on Claude — spec-writing, evals, and agent orchestration in 2026.
8 min read
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