Build Project Memory for AI
Stop re-explaining your project in every new chat. Capture it once as a context profile the AI keeps across every conversation — stack-inferred conventions and all.
When half the team says "route" and the other half says "trail", AI picks one at random. Standardize the terms so its output uses your words, the same way every time.
Terminology drift is quiet but corrosive: the model calls the same thing three names across one document because nobody fixed the canonical word. This setup standardizes the vocabulary for Trailmark, an offline-first hiking app, so route, waypoint, and sync token mean exactly one thing each. Where a glossary teaches what a term means, standardizing locks which term to use — the profile carries the canonical names verbatim and the never-assume rules keep the model from inventing synonyms. Output reads like one author wrote it, in your words.
Pick the canonical terms
One name per concept — route, not trail; waypoint, not pin.
Carry them verbatim
The profile keeps your exact words; the model doesn't paraphrase them.
Get consistent output
Every answer uses the same vocabulary, document after document.
The Glossary pins each concept to one canonical word — Route, Waypoint, Sync token for Trailmark — carried verbatim, and the Never Assume rules tell the model to ask when a fact is missing rather than invent it. The project-context-builder produces the profile; you paste it into your assistant's project instructions so it loads each chat.
Not quite — this profile draws the line between teaching what a term means and locking which term to use. It standardizes vocabulary so Route always means the ordered series of GPS points and the model uses that exact word, and notFor points you to the glossary-focused setup when the goal is defining unfamiliar terms instead. It's project knowledge, not a task persona.
Stop re-explaining your project in every new chat. Capture it once as a context profile the AI keeps across every conversation — stack-inferred conventions and all.
A reusable profile that tells AI everything constant about your project — type, stack, conventions, glossary, architecture principles, and the rules it must never guess.
Onboard AI to a codebase the way you'd onboard a new hire: what it is, how it's built, the rules that aren't written down, and the things never to assume.
End a working session like a shift change, not an abandonment: state captured, decisions logged, next step named — ready for the next session to pick up.
Convert scattered bug notes, Slack messages, or user complaints into structured engineering tasks with reproduction steps, severity, and root cause hypothesis.
What a converged conversation contains: a rejected voice, an accepted framing, a hard constraint, a format decision, and a final-version moment — each mapped to its prompt section.
Define what AI should permanently know about your project — stack conventions, glossary, and never-assume rules in a profile you paste once.
Give the AI context and it still writes "AI app builder" for your platform and "cart" for your basket — near-synonyms that change your meaning. Build a project glossary so AI uses your terms: define what each word means, name the synonyms to avoid, and paste it in your own tool.