Roman Bordo

Offer

Context Systems

Turn fragmented docs, chats, tools, and handoffs into usable operating context for people and AI.

For teams where AI-assisted work depends on background knowledge, source clarity, reviewable evidence, and context that survives beyond one chat.

Send the context problem

When this is useful

Context keeps resetting

Important background lives across chats, docs, screenshots, tools, and memory instead of one maintained operating layer.

Sources are unclear

Teams cannot tell what is current, what is draft, what is evidenced, and what should be ignored.

AI gets partial truth

Outputs depend on whatever context was pasted into the chat, not the actual source-of-truth structure.

Knowledge does not compound

Reviews, decisions, corrections, and failure patterns disappear instead of improving the system.

What gets designed

source-of-truth layers
context routing
evidence handling
metadata and versioning rules
human / AI handoff paths
stale-context checks

Output

The work is not a knowledge-base cleanup.

It is a context architecture pass: what counts as truth, where it lives, how it gets routed, and how humans and AI know when it is stale.

  • context system map
  • source-of-truth assessment
  • context routing recommendations
  • governance and review boundaries
  • proof artifacts to prepare next

Proof to build

Future proof artifacts

  • LifeOS source-of-truth case
  • context routing diagram
  • source layer map
  • evidence handling example
  • before / after context reconstruction

Context

Start with the context that keeps getting re-explained.

Send the workflow, source materials, and examples of where AI loses the thread.