Tag: AI
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From Vibe-Coded Prototype to Production: The 12-Point Audit
Your AI-built prototype works and someone wants to pay for it. The twelve checks we run before that is safe — and the one question that decides whether it needs hardening or a rebuild.
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How to Build an MVP with Claude Code: The Six-Week Shape That Actually Ships
Claude Code changed how fast an MVP gets built, not what an MVP is. The six-week structure we use — what to scope, what to cut, and the four decisions that decide whether week six ends in a launch.
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How to Vet an AI-Assisted Development Agency: 9 Questions to Ask in 2026
Every agency says it builds with AI. Nine questions that separate a disciplined engineering process from a prompt-and-ship one — plus the data on why it matters.
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Claude Code + Claude Design: A Friendly Guide to Shipping Apps That Are Actually Good
A step-by-step walkthrough of how we build with Claude Design and Claude Code in 2026 — the spec, the design system, plan mode, verification loops, subagents and the failure patterns to avoid. Plus an honest look at the last 20% that still needs a professional developer and designer.
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MCP Explained: What the Model Context Protocol Means for Your Business in 2026
MCP has become the standard for connecting AI models to real business systems. What it is, why it matters in 2026, the security risks vendors gloss over, and how to pilot it in weeks — explained without the jargon.
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Lessons from Building Production Apps with Claude Code at Syntaxa
What we learned using Claude Code on real client projects with real deadlines: where it saves the most time, where human oversight is essential, and the prompt structure that works.
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Claude vs. Copilot vs. Cursor: Which AI Coding Tool Wins in 2026?
Claude Code, GitHub Copilot and Cursor compared on real production work in 2026: strengths, blind spots, pricing, and which one fits which kind of team.
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Claude Code and the MVP Gap: 80% Built, 0% Shipped
Your MVP is 80% built and 0% shipped. How Claude Code closes the last-mile gap: the edge cases, the tests, and the unglamorous work between a demo and a launch.
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Integrating LLMs in 2026: Beyond the Hype Cycle
The demo phase of AI is over. A practical guide to integrating LLMs into real products: where they earn their keep, where they do not, and how to scope a pilot.