AI / Software Engineering
My Agentic Web Development Setup Is Basically a `while True` Loop
A multi-model web development pipeline — research, design, implementation, review — eventually orchestrated by a boring Python while True loop.
Topic19 articles
AI
AI systems, coding agents, context engineering and automation that does useful work beyond the chat window.
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Carbon Chooses, Silicon Scales
AI may surpass humans at many kinds of thinking without replacing humanity. The real question is whether that intelligence stays accessible to everyone.
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AI Feels Faster. The Data Is Less Certain.
AI coding tools feel transformative, but the productivity evidence is mixed. Part 2: perceived speed vs measured outcomes, and why review is the bottleneck.
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AI-Native Software Engineering Isn’t About AI
AI-native engineering isn't about how much AI you use. It's a development model where AI is a primary participant in building software, not an assistant.
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The Future of Software Engineering Is an Operating Model
AI-native engineering isn't about removing humans. Part 5: how roles, teams, economics and accountability shift when implementation stops being the main work.
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The Model Is Only One Part of the System
A useful AI workflow takes more than a better prompt. Part 3: specifications, context engineering, agent workflows, and the harness that enforces boundaries.
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When Agents Scale, Coordination Becomes the Product
One agent can misunderstand a requirement; several misunderstand it differently. Part 4: coordination, multi-agent orchestration and verification at scale.
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The Model Is Not the Development Environment
I spent 12 million input tokens on a small monorepo change. The problem was not the model. It was the development environment around it.
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AI Speeds Up Coding, Not Engineering
An opinionated workflow for building good-enough software with AI coding agents without surrendering architecture, judgment, or security.
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I Tried Too Many Coding Agents. Here Is What I Would Actually Pay For
A subjective comparison of Claude Code, Codex, Cursor, OpenCode, and the models inside them, based on ordinary application work rather than benchmarks.
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I Couldn't Become a 10x Developer
Chasing 10x across six projects, several languages and a pile of AI agents — and the quiet realization that 1.5x is honest work.
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Your AI Agent Should Be a Folder
After testing agent frameworks, I found the best personal AI agent isn't a platform — it's a well-organized folder of Markdown, scripts, logs and state.
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I Automated an Entire Course Production Pipeline. Then I Decided Not to Use It.
I built an AI pipeline turning storyboards into assets, narration, slides and captions. It almost worked, and showed why courses are authored, not manufactured.
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AI Doesn't Need to Become a Better Doctor. It Needs to Become a Better Historian.
AI spends 30 minutes building a medical history; a doctor gets 10. The gap isn't intelligence, it's information. Build AI historians, not AI doctors.
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Human-in-the-Loop Is a Lie We Tell Ourselves Before Clicking "Approve All"
Human-in-the-loop sounds responsible, but tired humans rubber-stamping prompts isn't governance. Real answer: programmatic boundaries, human accountability.
AI 6 min read
Learning in an AI-Driven World is a Paradox
AI changed the feedback loop between learning and building. I ship faster than ever, yet some days I know less than ever. What that paradox means for you.
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I Tried Building My AI Agent With Existing Agent Frameworks. Then I Chose the Boring Deterministic Way.
After evaluating multiple AI agent frameworks, I found that deterministic automation with an LLM inside beats magic autonomy for real operational work.
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Not Everyone Needs Frontier LLMs for Coding
Frontier models are brilliant, but most everyday coding runs fine on smaller ones if your workflow is clear. Choose tools for your use case, not the hype.
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Why Use LangGraph for Your First Agentic AI Project
LangGraph forces you to learn state, tools, routing and human approval — the agentic AI fundamentals that survive framework churn.
