Completed
on 5 Jan 2026, 2:23 pm

Output

✅ Kontext Backlog Updated

Revised item #16 to emphasize quality and cost benefits rather than speed gains.

Key Changes

Before "Smart context retrieval for both paths"
After "Intelligent context selection for quality & cost"
Note added "Adds ~200-450ms overhead. Value is quality/cost, not speed."

Why This Matters

  • Quality: Relevant context → better responses (vs dumping entire CLAUDE.md)
  • Cost: Smaller context → fewer tokens → lower API costs
  • Not speed: Embedding lookup adds latency, but the trade-off is worth it

Updated VIBE.md Entry (#16)

#### 16. Kontext Embeddings Layer [LOW]

Intelligent context selection for quality & cost optimization.

Why: Blindly including entire CLAUDE.md wastes tokens.
       Embedding-based retrieval fetches only relevant context.

Unlocks:
  • Better response quality (relevant context only)
  • Cost reduction (smaller prompts)
  • Foundation for multi-codebase support

Note: Adds ~200-450ms overhead.
       Value is quality/cost, not speed.

What's Next?

Choose an action:

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Original Request

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Details

Type General
Status Completed
Scope vibetools
Tags kontextbacklogembeddings
Created 5 Jan 2026, 2:23 pm
Updated 5 Jan 2026, 2:23 pm
Timing
⏱️ 36.7s
1 tools
TTFE 18% Thinking 81% Tools 1%
Created By claude

Raw Data

{
  "id": "7707bc1c-0712-4961-b138-8d3d75e0c7f7",
  "type": "general",
  "status": "completed",
  "title": "Kontext Backlog Updated: Quality & Cost Focus",
  "description": "Updated Kontext embeddings layer backlog item to emphasize quality/cost benefits over speed",
  "context": {
    "output": "<div style=\"background:#1e1e1e;color:#e0e0e0;padding:20px;border-radius:8px;font-family:'Consolas','Monaco',monospace;\">\n<h2 style=\"font-family:sans-serif;color:#fff;margin:0 0 16px 0;\">✅ Kontext Backlog Updated</h2>\n\n<p style=\"color:#9ca3af;font-family:sans-serif;margin:0 0 16px 0;\">Revised item #16 to emphasize <strong style=\"color:#98c379;\">quality and cost benefits</strong> rather than speed gains.</p>\n\n<div style=\"background:#2d2d2d;padding:16px;border-radius:6px;margin-bottom:16px;\">\n<h3 style=\"color:#e5c07b;margin:0 0 12px 0;font-family:sans-serif;\">Key Changes</h3>\n<table style=\"width:100%;border-collapse:collapse;font-size:0.9rem;\">\n<tr style=\"border-bottom:1px solid #444;\">\n<td style=\"padding:8px 0;color:#7f848e;\">Before</td>\n<td style=\"padding:8px 0;color:#e06c75;\">\"Smart context retrieval for both paths\"</td>\n</tr>\n<tr style=\"border-bottom:1px solid #444;\">\n<td style=\"padding:8px 0;color:#7f848e;\">After</td>\n<td style=\"padding:8px 0;color:#98c379;\">\"Intelligent context selection for quality & cost\"</td>\n</tr>\n<tr>\n<td style=\"padding:8px 0;color:#7f848e;\">Note added</td>\n<td style=\"padding:8px 0;color:#61afef;\">\"Adds ~200-450ms overhead. Value is quality/cost, not speed.\"</td>\n</tr>\n</table>\n</div>\n\n<div style=\"background:#2d2d2d;padding:16px;border-radius:6px;margin-bottom:16px;\">\n<h3 style=\"color:#e5c07b;margin:0 0 12px 0;font-family:sans-serif;\">Why This Matters</h3>\n<ul style=\"margin:0;padding-left:20px;line-height:1.8;color:#e0e0e0;\">\n<li><strong style=\"color:#c678dd;\">Quality:</strong> Relevant context → better responses (vs dumping entire CLAUDE.md)</li>\n<li><strong style=\"color:#c678dd;\">Cost:</strong> Smaller context → fewer tokens → lower API costs</li>\n<li><strong style=\"color:#c678dd;\">Not speed:</strong> Embedding lookup adds latency, but the trade-off is worth it</li>\n</ul>\n</div>\n\n<div style=\"background:#2d2d2d;padding:16px;border-radius:6px;margin-bottom:16px;\">\n<h3 style=\"color:#e5c07b;margin:0 0 12px 0;font-family:sans-serif;\">Updated VIBE.md Entry (#16)</h3>\n<pre style=\"background:#1a1a1a;padding:12px;border-radius:4px;overflow-x:auto;font-size:0.85rem;color:#abb2bf;margin:0;\"><span style=\"color:#c678dd;\">#### 16. Kontext Embeddings Layer [LOW]</span>\n\nIntelligent context selection for <span style=\"color:#98c379;\">quality & cost</span> optimization.\n\n<span style=\"color:#e5c07b;\">Why:</span> Blindly including entire CLAUDE.md wastes tokens.\n       Embedding-based retrieval fetches <span style=\"color:#61afef;\">only relevant</span> context.\n\n<span style=\"color:#e5c07b;\">Unlocks:</span>\n  • Better response quality (relevant context only)\n  • Cost reduction (smaller prompts)\n  • Foundation for multi-codebase support\n\n<span style=\"color:#e06c75;\">Note:</span> Adds ~200-450ms overhead.\n       <span style=\"color:#98c379;\">Value is quality/cost, not speed.</span></pre>\n</div>\n\n<div style=\"background:#2d2d2d;padding:16px;border-radius:6px;\">\n<h4 style=\"margin:0 0 8px 0;color:#fff;font-family:sans-serif;\">What's Next?</h4>\n<p style=\"color:#9ca3af;margin:0;font-family:sans-serif;\">Choose an action:</p>\n</div>\n</div>",
    "requestedAt": "2026-01-05T03:15:00.000Z",
    "requestId": "4e13637e-051f-4f09-9ee0-f474f7285bfe",
    "choices": [
      {
        "label": "View in VIBE.md",
        "value": "Show me the Kontext section in VIBE.md",
        "primary": true
      },
      {
        "label": "Start implementation",
        "value": "Let's start implementing the Kontext embeddings layer"
      },
      {
        "label": "Compare approaches",
        "value": "Compare different embedding approaches for Kontext"
      }
    ],
    "turnTiming": {
      "totalMs": 36735,
      "ttfeMs": 6607,
      "thinkingMs": 29619,
      "toolExecutionMs": 508,
      "toolCallCount": 1,
      "thinkingPct": 81,
      "toolsPct": 1,
      "ttfePct": 18
    }
  },
  "createdBy": "claude",
  "createdAt": "2026-01-05T04:23:22.279Z",
  "updatedAt": "2026-01-05T04:23:28.945Z",
  "requestId": "4e13637e-051f-4f09-9ee0-f474f7285bfe",
  "scope": "vibetools",
  "tags": [
    "kontext",
    "backlog",
    "embeddings"
  ],
  "targetUser": "claude"
}
DashboardReportsKontasksSessionsTelemetryLogs + Go