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feat(web): refresh site, book, and social card with "Drafting Table" identity
Landing page: - Drafting-table hero (blueprint grid, redlined brand mark, title block) - Honest 4-command surface (init/new-track/implement/review) + routing diagram - Broadened problem/pipeline/features copy; bughunt recast as review escalation - Accuracy sweep: 159 languages, 33 commands, 6 graph modes, 6 platforms Book (shared css/book.css refresh layer — applies to all 50 pages): - Drawing-label eyebrows, redline reading-progress, calmer surfaces - Landing rebuilt as a drafting sheet with title block - Metadata corrected: "24 chapters" -> "22 chapters and 2 appendices" Social card (social-preview.svg/.png): - Redesigned to Drafting Table identity (grid, redline mark, title block) - Fixed stale stats: v3.2.1 -> 3.3.1, 9 -> 159 languages - Cache-bust og:image/twitter:image (?v=331) + og:image dimensions site-wide - Aligned og:image:alt to new positioning New: web/css/refresh-v4.css. command-reference: row anchors + /draft:jira row. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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web/blog/blast-radius-walkthrough/index.html

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<meta property="og:description" content="A real impact-mode run on a hotspot before a single line gets written. 47 downstream files, 12 tests, 3 config templates — and a refactor plan reshaped before /draft:implement starts.">
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<meta name="twitter:description" content="From 'small change' to 47 downstream files, 12 tests, 3 config templates — and the refactor plan reshaped before any code lands.">
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<meta property="og:description" content="Eight modules, a circular dependency caught and broken before any code, and an LLD with contracts for the two high-complexity modules.">
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<meta name="twitter:description" content="From tangled task list to four cleanly-phased module builds, with a circular dependency caught before a single line of code.">
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<meta property="og:description" content="grep is faster on trivial lookups. It's also wrong more often and costs your AI agent up to 108× more tokens to reach the right answer. Accuracy and tokens — not latency — are the axes that matter in an agent loop.">
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<meta property="og:description" content="Field notes on Context-Driven Development, Draft's knowledge graph, and getting AI to write production code.">
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<meta property="og:description" content="A local, live-queried knowledge graph, powered by codebase-memory-mcp and installed alongside the Draft plugin. No MCP server, no SaaS, no cloud, no API key, no leaked code.">
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<meta property="og:description" content="Loading every MCP tool schema upfront costs 50–140K tokens. Three agents fixed it. One still hasn't. A 2026 field comparison.">
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<meta property="og:description" content="Bug hunting, ACID enforcement, three-stage review, architecture discovery, IDE portability, and a $0 price tag — Kiro vs Draft, the honest comparison.">
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<meta property="og:description" content="Architecture Decision Records — structured decision capture with context, rationale, consequences, and lifecycle management.">
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<meta property="og:description" content="Seven specialized agents — Architect, Debugger, Ops, Planner, RCA, Reviewer, and Writer — each with behavioral protocols tuned for their domain.">
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<meta property="og:description" content="14-dimension bug hunting sweep — from null safety to concurrency, security to algorithmic complexity. Only HIGH/CONFIRMED confidence reported.">
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