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Notes on AI-native development and building with LLMs.

by shinpr

Feb 11, 2026 · 13 min

What Makes Development AI-Native?

AI-Native development requires four structural pillars most organizations lack. Assess your readiness with a 100-point diagnostic criteria.

#AI-Native#Context Closure#LLM

Jan 26, 2026 · 12 min

Planning Is the Real Superpower of Agentic Coding

Turn LLM execution into verification with explicit planning. Research shows this approach improves task success by 33% in complex agentic coding scenarios.

#Agentic Coding#Planning#LLM

Jan 21, 2026 · 11 min

The Leadership Bottleneck in AI-Native Development

AI productivity metrics look great, but outcomes haven't changed. Discover why the leadership bottleneck—not tools—determines AI-Native transformation success.

#AI-Native#Leadership#Engineering Management

Jan 19, 2026 · 9 min

Stop Putting Everything in AGENTS.md

Learn where to write LLM rules, what to write, and how to verify they work. Keep AGENTS.md lean while ensuring your rules actually stick.

#AGENTS.md#Agentic Coding#Rule Externalization

Jan 12, 2026 · 9 min

Why LLMs Are Bad at 'First Try' and Great at Verification

Stop optimizing for first-shot perfection. LLMs perform better at verifying and improving existing artifacts than at controlled first-time generation.

#LLM#Verification#Workflow Design

Jan 12, 2026 · 9 min

Building a Local RAG for Agentic Coding: From Fixed Chunks to Semantic Search with Keyword Boost

Started with a simple RAG for MCP—ended up implementing semantic chunking and rethinking hybrid search. For people who've built RAG systems and started hitting quality limits.

#RAG#Semantic Chunking#MCP

Jan 12, 2026 · 17 min

Rethinking Team Development in the Age of LLMs

Code reviews shift from reviewing code to reviewing specs. Design the whole Spec → Plan → Test → Implementation cycle. Small teams work better—scale by adding teams, not people.

#LLM#Team Development#Process Design

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