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  <channel>
    <title>MemStrata blog</title>
    <link>https://www.memstrata.dev/blog/</link>
    <description>Ask your files and past conversations. See the evidence behind each answer.</description>
  <item>
    <title>Standard versus Deep Evidence: How to Choose the Context Budget</title>
    <link>https://www.memstrata.dev/blog/standard-versus-deep-evidence/</link>
    <guid>https://www.memstrata.dev/blog/standard-versus-deep-evidence/</guid>
    <pubDate>Sat, 19 Sep 2026 00:00:00 GMT</pubDate>
    <description>Standard mode uses 8,192 evidence tokens; Deep uses 24,000. These are source budgets, not model context windows or the R454 7,000-token research budget. Screenshots were captured on 0.7.13.</description>
  </item>
  <item>
    <title>Local AI Memory: What Stays on Your Device and What Goes to a Model Provider</title>
    <link>https://www.memstrata.dev/blog/local-ai-memory-what-stays-on-your-device/</link>
    <guid>https://www.memstrata.dev/blog/local-ai-memory-what-stays-on-your-device/</guid>
    <pubDate>Sat, 19 Sep 2026 00:00:00 GMT</pubDate>
    <description>Conversational indexes sources on the device. You connect your own AI. Account and licensing still call MemStrata hosted services. Screenshots are from the historical 0.7.13 walkthrough.</description>
  </item>
  <item>
    <title>Why an AI Answer Can Cite a Source and Still Be Wrong</title>
    <link>https://www.memstrata.dev/blog/why-an-ai-answer-can-cite-a-source-and-still-be-wrong/</link>
    <guid>https://www.memstrata.dev/blog/why-an-ai-answer-can-cite-a-source-and-still-be-wrong/</guid>
    <pubDate>Sat, 19 Sep 2026 00:00:00 GMT</pubDate>
    <description>A citation is not a proof. Three small examples show an irrelevant source, an outdated source, and an unsupported conclusion. Inspect the passage, not only the link.</description>
  </item>
  <item>
    <title>How to Ask Questions Across Your Documents and Past Conversations</title>
    <link>https://www.memstrata.dev/blog/how-to-ask-questions-across-documents-and-past-conversations/</link>
    <guid>https://www.memstrata.dev/blog/how-to-ask-questions-across-documents-and-past-conversations/</guid>
    <pubDate>Sat, 19 Sep 2026 00:00:00 GMT</pubDate>
    <description>A historical Conversational walkthrough captured on 0.7.13: import demo notes and inspect the evidence. Use the install selector for the current release.</description>
  </item>
  <item>
    <title>MemStrata Coder with VS Code, Cursor, Windsurf, and Terminal Agents</title>
    <link>https://www.memstrata.dev/blog/coder-mcp-vscode-shims/</link>
    <guid>https://www.memstrata.dev/blog/coder-mcp-vscode-shims/</guid>
    <pubDate>Mon, 31 Aug 2026 00:00:00 GMT</pubDate>
    <description>How Coder connects to VS Code, VS Code shims such as Cursor and Windsurf, JetBrains IDEs, and terminal agents including Claude Code, Codex CLI, Aider, and OpenCode via MCP, harness, or extension.</description>
  </item>
  <item>
    <title>Temporal Validity on Real GitHub Fixes: Paper 2 Is on arXiv</title>
    <link>https://www.memstrata.dev/blog/temporal-validity-real-github-fixes/</link>
    <guid>https://www.memstrata.dev/blog/temporal-validity-real-github-fixes/</guid>
    <pubDate>Fri, 21 Aug 2026 00:00:00 GMT</pubDate>
    <description>arXiv:2608.20685 validates deterministic supersession on 130 marker-free atomic transitions from 707 SWE-bench GitHub issues. MemStrata reaches 0.91 accuracy versus RAG 0.57-0.59, with stale-fact error near 0 versus 36-38%.</description>
  </item>
  <item>
    <title>Why LongMemEval Scores Are Not Comparable Across Memory Products</title>
    <link>https://www.memstrata.dev/blog/longmemeval-same-stack-honesty/</link>
    <guid>https://www.memstrata.dev/blog/longmemeval-same-stack-honesty/</guid>
    <pubDate>Sat, 15 Aug 2026 00:00:00 GMT</pubDate>
    <description>LongMemEval is not one number. A useful comparison states the dataset, reader, evidence budget, judge and failure handling. The public MemStrata R454 figure is 84.0% (420/500) judged by GPT 5.5.</description>
  </item>
  <item>
    <title>Measure Selected Coding Context Without Sending the Whole Repository Upstream</title>
    <link>https://www.memstrata.dev/blog/cutting-ai-coding-token-costs-local-context/</link>
    <guid>https://www.memstrata.dev/blog/cutting-ai-coding-token-costs-local-context/</guid>
    <pubDate>Sat, 11 Jul 2026 00:00:00 GMT</pubDate>
    <description>MemStrata Coder routes selected project context into coding tools and measures each visible user turn. The 81.4% input example is a four-turn controlled test, not a universal savings rate.</description>
  </item>
  <item>
    <title>Comparing MemStrata, Mem0, Graphiti and Letta: what the evidence can tell you</title>
    <link>https://www.memstrata.dev/blog/memstrata-vs-mem0-graphiti-letta/</link>
    <guid>https://www.memstrata.dev/blog/memstrata-vs-mem0-graphiti-letta/</guid>
    <pubDate>Thu, 09 Jul 2026 00:00:00 GMT</pubDate>
    <description>A practical guide to comparing AI memory systems, with MemStrata's scoped LongMemEval and LoCoMo results against Letta and a frozen Zep snapshot.</description>
  </item>
  <item>
    <title>Beyond Code: Temporal Supersession Generalizes to World Knowledge</title>
    <link>https://www.memstrata.dev/blog/temporal-supersession-beyond-code/</link>
    <guid>https://www.memstrata.dev/blog/temporal-supersession-beyond-code/</guid>
    <pubDate>Tue, 07 Jul 2026 00:00:00 GMT</pubDate>
    <description>Oracle experiments on synthetic world-knowledge facts hit 1.000 accuracy / 0.000 stale in that protocol. Remaining error is extraction. This note is not the Paper 4 conversational 27B evaluation.</description>
  </item>
  <item>
    <title>Detect-and-Flag: Honest Memory for the 76% of Code That Is Not a Triple</title>
    <link>https://www.memstrata.dev/blog/detect-and-flag-logic-staleness/</link>
    <guid>https://www.memstrata.dev/blog/detect-and-flag-logic-staleness/</guid>
    <pubDate>Sun, 05 Jul 2026 00:00:00 GMT</pubDate>
    <description>You cannot supersede logic you cannot extract. The earlier structural-staleness design marks scope-level code changes and warns at retrieval — without faking understanding or breaking the deterministic moat.</description>
  </item>
  <item>
    <title>The Value-Change Ceiling: Only ~19% of Real Code Fixes Are Clean Supersessions</title>
    <link>https://www.memstrata.dev/blog/value-change-ceiling-code-evolution/</link>
    <guid>https://www.memstrata.dev/blog/value-change-ceiling-code-evolution/</guid>
    <pubDate>Fri, 03 Jul 2026 00:00:00 GMT</pubDate>
    <description>Across 707 SWE-bench fixes, deterministic temporal memory natively covers ~19% of evolution. Contract extraction lifts to ~24%. The remaining ~76% is logic — and overclaiming extraction is a research risk.</description>
  </item>
  <item>
    <title>SWE-bench Longitudinal: How to Build an Evolving-Code Evaluation</title>
    <link>https://www.memstrata.dev/blog/swe-bench-longitudinal-temporal-memory/</link>
    <guid>https://www.memstrata.dev/blog/swe-bench-longitudinal-temporal-memory/</guid>
    <pubDate>Wed, 01 Jul 2026 00:00:00 GMT</pubDate>
    <description>Paper 2 extracts 130 clean atomic transitions from 707 SWE-bench GitHub fixes. This article explains how that benchmark is constructed and what its scope allows you to conclude.</description>
  </item>
  <item>
    <title>Marker-Free Benchmarks for Evolving Knowledge: Stop Letting Labels Inflate RAG Scores</title>
    <link>https://www.memstrata.dev/blog/marker-free-benchmarks-evolving-knowledge/</link>
    <guid>https://www.memstrata.dev/blog/marker-free-benchmarks-evolving-knowledge/</guid>
    <pubDate>Mon, 29 Jun 2026 00:00:00 GMT</pubDate>
    <description>If your evolving-knowledge benchmark marks outdated chunks as “[OUTDATED]”, baselines win by reading the label. MemStrata’s marker-free protocol removes that contamination — and scores drop up to 14 points when markers are removed.</description>
  </item>
  <item>
    <title>Cosine Similarity Cannot Detect Contradictions (AUROC 0.59): What That Means for Agent Memory</title>
    <link>https://www.memstrata.dev/blog/cosine-cannot-detect-contradictions/</link>
    <guid>https://www.memstrata.dev/blog/cosine-cannot-detect-contradictions/</guid>
    <pubDate>Sun, 28 Jun 2026 00:00:00 GMT</pubDate>
    <description>Calibration results show cosine similarity cannot separate contradicted facts from duplicated ones. Contradictions are more embedding-similar than rephrases. Here is the data and the design implication.</description>
  </item>
  <item>
    <title>Introducing Temporal Validity Memory: How MemStrata Retires Stale Facts Without an LLM</title>
    <link>https://www.memstrata.dev/blog/introducing-temporal-validity-memory/</link>
    <guid>https://www.memstrata.dev/blog/introducing-temporal-validity-memory/</guid>
    <pubDate>Sat, 27 Jun 2026 00:00:00 GMT</pubDate>
    <description>MemStrata maintains temporal validity with deterministic (subject, relation, object) supersession in a bi-temporal ledger. No similarity threshold. No LLM on the read path. ~2.1s retrieval latency.</description>
  </item>
  <item>
    <title>Why RAG Cannot Tell Time: The Stale-Fact Error Problem for AI Agents</title>
    <link>https://www.memstrata.dev/blog/why-rag-cannot-tell-time/</link>
    <guid>https://www.memstrata.dev/blog/why-rag-cannot-tell-time/</guid>
    <pubDate>Fri, 26 Jun 2026 00:00:00 GMT</pubDate>
    <description>When knowledge evolves, the evaluated retrieval baseline retrieves both stale and current facts with near-identical embeddings. Stale-fact errors in that protocol are structural, not a tuning problem.</description>
  </item>
  </channel>
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