session.json
{
"messages": [
{ "role": "user",
"content": "Don't touch auth"
}, {
"role": "assistant",
"content": "Using Redis for cache"
}
],
"tool_calls": [
{ "type": "function",
"name": "edit_file"
"arguments": {
"path": "src/redis/client.ts"
}
}
],
"tool_results": [{
"error": "ECONNRESET"
}]
}
Strata
Session Archaeology for AI Agents
TL;DR: AI agents lose their minds when conversations get long. Strata compacts session history into structured "fossils" (not paragraph summaries) so a new agent can pick up where the last one left off without repeating your mistakes.
The problem
Why every compaction system makes the same mistake, and why it matters
The solution
A 4-phase pipeline that extracts structure instead of summarizing prose
The tradeoffs
When to use it, when not to, and what it costs
Read this like strata
Each section starts sealed at the surface.
Excavate it to reveal the main layer, then dig deeper only if you want the technical internals.
By Jeff Nash·February 2026·~8 min surface skim · ~15 min fully excavated
The Problem
Your Agent Has Amnesia
sealedBrush away the surface to reveal the section.
Surface fossilsealedWhy the normal recap fails
Most compaction systems preserve the story of a session while destroying the sharp edges that matter operationally: hard constraints, failed approaches, and the exact decisions the next agent must inherit.
sealed
TL;DR
AI agents summarize long conversations into useless paragraphs, losing the constraints, failed approaches, and decisions that actually matter. Strata preserves structured artifacts instead of prose summaries, more like archaeology than journalism.
Key takeaway
Compaction breaks when it optimizes for coherence instead of survivable operational memory.
Excavation site
This surface layer preserves the diagnosis. Excavate it for the examples, the failure modes, and the exact argument for extraction over summary.
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Proof
Before We Go Deeper: A Real Fossil
Before I explain how the pipeline works, I want to show you what comes out the other side. While fixing SVG animations on this very page, Strata fossilized the session. The fossil below is real, not a mockup, not sanitized. Click any section to see what the next agent would actually inherit.
Surface fossilsealedA handoff, not a mockup
This is the punchline before the theory: a real fossil from work on this very page, showing the kind of structured inheritance a new agent would receive instead of a vague paragraph recap.
sealed
Captured artifact
fossil-aced9743
Session: fixing SVG mobile animations in the Strata article
Key takeaway
If the output already feels more actionable than a normal compaction summary, the rest of the article has done its job.
Excavation site
The specimen is catalogued here at the surface. Excavate this section to inspect the real fossil explorer and the recursive joke at the footer.
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The Output
The Resurrection Protocol
sealedBrush away the surface to reveal the section.
Surface fossilsealedWhat the next agent inherits
A Resurrection Protocol is the structured handoff artifact: enough context for a fresh agent to answer what we were doing, what is broken, and what the next move should be without re-reading the whole transcript.
sealed
TL;DR
A Resurrection Protocol is a durable handoff the next agent can act on: what's happening, what's blocked, and what to do next.
Key takeaway
The artifact is only as valuable as its ability to get a new agent productive fast.
Excavation site
This fossil layer preserves the handoff thesis. Excavate it for the before/after examples, protocol anatomy, and budget trimming logic.
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How It Works
The Pipeline
sealedBrush away the surface to reveal the section.
Surface fossilsealedFour passes, one hard rule
Strata turns raw session logs into a handoff by normalizing events, compacting noise, segmenting the work, and extracting typed artifacts while refusing to compact away the constraints and failures that matter.
sealed
TL;DR
Four passes: normalize everything into one format, collapse redundant tool output, split into episodes and score by importance, then extract typed artifacts. The pipeline never touches a constraint for compaction, no matter how tight the token budget gets.
Key takeaway
The pipeline is deterministic where it can be and only spends model intelligence where judgment is genuinely useful.
Excavation site
The surface fossil captures the pipeline shape. Excavate it for the four phases, visuals, and the concrete compaction and triage examples.
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Deep Dive
Pipeline Internals
sealedBrush away the surface to reveal the section.
Surface fossilsealedCore sample
This is the audit layer for people who want the exact mechanics. The story layer keeps the internals buried; the deep dig exposes the thresholds, formulas, and schema-driven extraction logic in full.
sealed
TL;DR
Four pipeline phases (normalize, chunk, extract, compile) each with specific thresholds, schemas, and pruning rules. Every number in this section is the actual production default.
Key takeaway
If the system makes claims about preserving sharp edges, the implementation details should be inspectable.
Excavation site
This surface layer preserves the audit promise. Excavate it, then dig deeper if you want the actual formulas and defaults.
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Trust
Trust & Verification
sealedBrush away the surface to reveal the section.
Surface fossilsealedWhy this can be audited
A fossil is only useful if the next agent can trust it. Strata makes every claim point back to source evidence, assigns confidence instead of bluffing certainty, and gives you enough structure to audit the handoff like a PR.
sealed
TL;DR
Every claim in a fossil links back to the exact message that produced it. You can check. That's the whole model.
Key takeaway
Structured memory only matters if bad claims stay traceable instead of becoming lore.
Excavation site
This fossil layer preserves the trust model. Excavate it for the confidence playground, citation compiler, and the verification mechanics behind each claim.
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Integration
Plugging In
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Surface fossilsealedWhere this plugs into an agent
The integration pattern is narrow: catch the moment an agent would normally summarize a full context window, fossilize that session instead, and hand the next model a structured protocol plus retrieval tools.
sealed
TL;DR
It's one extension with one hook point, and it replaces compaction at the exact seam where context gets thrown away while giving the agent retrieval tools to pull deeper context on demand.
Key takeaway
You do not need to rebuild the agent. You need to intercept the one seam where it currently throws memory away.
Excavation site
This surface layer preserves the integration story. Excavate it for the pi hook point, the compaction flow, and the code-context extraction details.
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In Practice
What Makes This Different
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Surface fossilsealedWhat category this actually belongs to
Strata is not trying to be codebase-wide memory or generic RAG. It is a conversation-handoff system, optimized for preserving actionable session state across compaction without pretending to solve every memory problem.
sealed
TL;DR
Other compaction tools optimize for a human reading a recap. Strata optimizes for an agent inheriting work. Different product.
Key takeaway
The difference is not just better summaries. It is a different unit of memory and a stricter definition of trust.
Excavation site
This surface layer preserves the positioning. Excavate it for the comparison grid, the verification gate, and the explicit boundaries where Strata loses.
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Wrapping Up
The Verdict
Surface fossilsealedUse it when the sharp edges matter
Strata is worth the overhead when agent sessions are long-lived, constraint-heavy, and likely to require handoffs. If your workflows are short and forgiving, a normal summary is usually the right trade.
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Key takeaway
The whole bet is that preserving operational memory beats re-learning it under time pressure.
Excavation site
The verdict is preserved here at the surface. Excavate it for the tradeoffs, the technical appendix, and the final recommendation.
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