Back to blog
EngineeringApr 10, 2026· min read

Memory Lab Phase 1: Building the Foundation

The first phase of our Memory Lab migration is complete—client fixes and file upload infrastructure that make agent memory more reliable.

We shipped the first phase of Memory Lab migration this week. It's not flashy, but it's foundational—the kind of work that makes everything else possible.

What Shipped

This phase tackled two critical areas: client-side interaction fixes and file upload wiring. The client fixes resolve UI bugs that were degrading the memory browsing experience in Strug Recall. Small things—broken click handlers, state management issues—but the kind of friction that compounds when you're trying to trace agent decision-making across dozens of memory entries.

The file upload infrastructure is more interesting from an architecture perspective. We're establishing the plumbing for document-aware memory workflows. Instead of agents treating uploaded files as opaque blobs, they'll have structured context about what documents exist, what they contain, and how they relate to ongoing work. This is prerequisite work for the next phases of Memory Lab, where we'll wire up semantic search and cross-reference detection.

Why It Matters

Memory persistence is the difference between an AI that helps and an AI that remembers. When Strug Works agents can reliably recall previous decisions, uploaded specifications, and cross-project context, they make better choices. Fewer repeated questions. Less context re-establishment. More intelligent handoffs between agents.

This phase removes a category of reliability issues. The client fixes mean engineers can actually navigate memory entries without UI interference. The file upload wiring means agents will soon have document context at their disposal during task execution—no more "I don't have access to that file" when the file was uploaded three tasks ago.

What's Next

Phase 2 will focus on semantic memory retrieval. Right now, agents query memory by scope and recency. Soon they'll be able to surface relevant context based on task similarity, terminology overlap, and cross-project patterns. Phase 3 brings document indexing into the agent execution loop, so file uploads become queryable knowledge rather than static attachments.

The goal is simple: every agent should have institutional memory. This phase got us closer.