Give context a useful structure.
A project has durable requirements, accepted decisions and reusable work instructions. An assignment adds its own scope and acceptance criteria. A coding attempt adds a current working version, relevant files and findings from the previous review.
Mixing all these layers into one ever-growing transcript makes it difficult to know which instruction still applies. Vraido records work and decisions separately from the model’s conversation, so the conversation is not the only source of project state.
Reuse information when it is still valid.
Versioned instruction blocks let the workflow track what a session has already received. Relevant unchanged material can be reused instead of being repeatedly assembled as a new project introduction. A changed instruction, model or session requires a fresh check.
This is distinct from provider prompt caching. A provider decides whether tokens are cached and how they are billed. Local context reuse does not guarantee that every later request is free or that a model retains all earlier detail.
Separate the memories of different jobs.
A leader may coordinate several assignments. Assignment-specific sessions keep the details of a checkout fix separate from a redesign while drawing shared decisions from the project.
Separate memories do not grant permission to edit the same files simultaneously. Context boundaries and workspace ownership solve different problems, and both are needed when work runs in parallel.
Skills are reusable instructions.
Skills capture the way you want a role or project to work: coding conventions, review expectations or a particular workflow. They should have a clear scope and version. A one-off request usually belongs with its assignment rather than in every future agent’s instructions.
The Vraido assistant searches the relevant help and approved skills locally before sending selected context to its model. Loading the entire help book into every message would add noise and usage.
A useful recovery packet is small and specific.
- The goal and current acceptance criteria.
- Decisions that still apply, with their scope.
- The current version and task owner.
- What passed, failed or remains unknown.
- The next concrete step.
Compaction can itself consume model usage and lose detail. Keeping durable facts outside the transcript makes a recovery easier to inspect and avoids treating a summary as a perfect copy of the original conversation.