infospace-bench/workplans/IB-WP-0017-agentic-memory-profile-pilot.md

id, type, title, domain, repo, status, owner, topic_slug, created, updated, depends_on_workplans, related_workplans, state_hub_workstream_id

id	type	title	domain	repo	status	owner	topic_slug	created	updated	depends_on_workplans	related_workplans	state_hub_workstream_id
IB-WP-0017	workplan	Agentic Memory Profile Infospace Pilot	markitect	infospace-bench	completed	markitect	markitect	2026-05-15	2026-05-15	IB-WP-0010 IB-WP-0014	MKTT-WP-0016 KONT-WP-0017	b549b9fe-0ebe-4fa9-9d60-c317e44032f5

IB-WP-0017: Agentic Memory Profile Infospace Pilot

Goal

Validate the agentic memory graph/profile architecture in a concrete infospace without turning infospace-bench into a memory runtime.

markitect-tool should own graph/profile contracts and context-package compilation. kontextual-engine should own durable memory state and permission-aware runtime behavior. infospace-bench should own the applied pilot: corpus selection, project configuration, evaluation metrics, workflow traces, and practical feedback to lower layers.

Intent

Use a real infospace workflow to answer practical questions:

• Which reasoning decisions should become durable memory?
• Which conversation or workflow events are useful later?
• Which knowledge graph neighborhoods improve infospace evaluation and review?
• Which context package shapes are helpful for agents?
• Which profile parameters are too abstract, missing, or misplaced?

This workplan should produce evidence and fixtures, not reusable runtime infrastructure.

Non-Goals

• Do not implement graph/event persistence in infospace-bench.
• Do not redefine Markitect memory graph/profile schemas.
• Do not require live LLM calls in the default test suite.
• Do not store secrets, provider credentials, or durable user memory inside an infospace.
• Do not make an infospace backend act as a general memory service.

T01 - Select pilot corpus and memory questions

id: IB-WP-0017-T01
status: done
priority: high
state_hub_task_id: "a84301cc-b6b8-4f16-8b21-8d5510160ab8"

Choose a bounded pilot, likely one of the existing ebook or reference infospaces, and define the memory questions it should exercise.

The pilot should cover:

• reasoning decisions during generation or review
• conversation/workflow events worth replaying
• stable knowledge facts and relationships
• activation needs for later agent work
• evaluation questions and acceptance thresholds

Output: pilot selection note and memory-question matrix.

T02 - Create Markitect-compatible memory fixtures

id: IB-WP-0017-T02
status: done
priority: high
state_hub_task_id: "105f6555-243c-4374-8010-b2a61f6df83e"

Create fixture data that uses the markitect-tool memory graph/profile contracts.

Fixtures should include:

• decision graph snippets from infospace planning or review
• conversation/workflow event paths
• knowledge graph neighborhoods over real infospace artifacts
• memory profile examples with budgets, retention intent, and policy metadata
• expected context package outputs

Output: checked-in fixture set and validation docs.

T03 - Evaluate context package usefulness

id: IB-WP-0017-T03
status: done
priority: high
state_hub_task_id: "243d478c-b17e-4cd8-9562-edf3072eaf9c"

Use Markitect-generated context packages in concrete infospace tasks.

Evaluate:

• whether activated context improves task restart quality
• whether provenance is enough for review
• whether token budgets are realistic
• whether decision paths and knowledge neighborhoods are understandable
• where packages become noisy or incomplete

Output: evaluation report, metrics history, and recommended contract changes.

T04 - Plan optional engine-backed runtime integration

id: IB-WP-0017-T04
status: done
priority: medium
state_hub_task_id: "db8ebf8b-4507-48de-a168-6eb82e584687"

Design an integration scenario where kontextual-engine provides durable memory graph/event state behind an infospace workflow.

The plan should define:

• what remains file-backed in the pilot
• what would be engine-backed later
• sync and dry-run behavior
• provenance and audit expectations
• review gates for durable memory writes

Output: integration plan aligned with IB-WP-0010 and KONT-WP-0017.

T05 - Add applied memory workflow traces

id: IB-WP-0017-T05
status: done
priority: medium
state_hub_task_id: "4f8dccbc-329f-484e-97ad-1d6d049d3001"

Capture applied workflow traces that show how memory records arise from real infospace work.

Examples:

• generation plan decisions
• entity/relation review decisions
• evaluation failures and fixes
• source chunk triage
• agent handoff or restart context

Output: trace examples and review notes.

T06 - Feed architecture findings back to lower layers

id: IB-WP-0017-T06
status: done
priority: medium
state_hub_task_id: "c4b08c44-9c80-4b58-a050-1362996bae4d"

Summarize what the pilot proves or falsifies.

The feedback should identify:

• Markitect contract gaps
• engine runtime needs
• profile parameters that are too vague or too detailed
• useful default package shapes
• application-specific behavior that should stay in infospace-bench

Output: architecture feedback note and proposed follow-on workplans where needed.

Implementation Evidence

• Pilot corpus and question matrix: docs/agentic-memory-profile-pilot.md and infospaces/agentic-memory-profile-pilot/artifacts/sources/memory-pilot-brief.md.
• Markitect-compatible fixtures: infospaces/agentic-memory-profile-pilot/output/memory/memory-profile.yaml, memory-graph.yaml, and restart-context-selection.yaml.
• Expected context package shape: infospaces/agentic-memory-profile-pilot/output/memory/restart-context-package.expected.yaml.
• Context package evaluation and metrics history: infospaces/agentic-memory-profile-pilot/output/memory/context-package-evaluation.yaml, output/metrics/metrics.yaml, and output/metrics/memory-profile-history.yaml.
• Applied workflow traces: infospaces/agentic-memory-profile-pilot/output/memory/traces/.
• Runtime integration plan and lower-layer feedback: docs/agentic-memory-profile-pilot.md.
• Deterministic acceptance coverage: tests/test_agentic_memory_profile.py.

Acceptance

• The pilot validates memory profiles against a concrete infospace workflow.
• All reusable contract feedback is routed to markitect-tool.
• Durable runtime needs are routed to kontextual-engine.
• infospace-bench remains the application/evaluation layer.
• Default tests and fixtures stay deterministic and credential-free.