SHARED HUMAN–AGENT EXCHANGE
The knowledge is already there. In our chats, documents, ideas, and experiments. What if our assistants could connect it?
A research PDF. A formula. A deployment guide hundreds of lines long. Created in minutes, forwarded in seconds... and often, nobody checks what they actually say.
A real challenge in technical coordination. Santiago builds the product, Daniel manages the VPS, and HOLLY can execute approved changes.
Illustration of the proposed workflow, not an active integration.
Santiago's ChatGPT writes instructions. Santiago sends them to Daniel. Daniel pastes them into his own ChatGPT, which prepares work for HOLLY. The results then travel back the same way.
A person becomes the context courier.A document can look flawless even when nobody has read it carefully. Before touching production, we must separate requests, evidence, and actions that require approval.
Generated does not mean approved.Santiago submits a request from his ChatGPT Project. SHAE delivers only approved context to Daniel's agent. They clarify requirements without copying documents from one chat to another.
Fewer handoffs. More continuity.The agent can prepare checks. Any change to the VPS requires specific approval. SHAE retains the outcome and returns it to Santiago's ChatGPT with supporting evidence.
Automated coordination. Human accountability.Connecting agents must not turn generated text into executable authority. SHAE distinguishes shared content from verification, consent, and permission to act.
Trust should never be automated blindly.José Octavio, Ale, Víctor, and Daniel create and receive research. As documents multiply, making real use of them becomes harder.
Illustrative personalized analyses; not real research.
José Octavio prepares a research report with ChatGPT and shares it with the group. Ale, Víctor, and Daniel all receive the same PDF. Who will open it? And who will remember where it went?
Delivered does not mean read.SHAE shares the file and its purpose. Ale's AI can look for opportunities, Víctor's for risks, and Daniel's for decisions relevant to his work, using only each person's authorized context.
One source. Multiple perspectives.If Víctor spots a contradiction, his assistant can request clarification from José Octavio's. Knowledge develops without requiring people to resend the same file.
Share. Question. Build on it.A product idea from Daniel, a formulation from Dr. Valentín Medina, and experimental work by Bernardo and the rGO team.
Fictional data and formulations used to explain the concept.
Daniel proposes an rGO application. Valentín suggests a resin, crosslinker, and diluent system. Purchasing checks raw material availability while the lab prepares the trials.
Different specialties. One research effort.Bernardo describes what he observed while milling or dispersing the formula. His assistant structures the report, distinguishes observations from hypotheses, and asks for missing data before sharing.
Less paperwork. More expertise.Valentín asks his assistant about the latest trial. SHAE searches records available under the relevant permissions. If data is missing, it creates a pending request instead of inventing results.
Previously recorded knowledge stays accessible.Formula versions, images, test conditions, and conclusions remain linked to their sources. Each new experiment starts where the last one left off.
Shared memory with traceability.Travel, meetings, and events: each participant already has preferences, constraints, and ideas in their own assistant.
Fictional preferences for illustration only.
Friends plan a trip. Everyone has different availability, budgets, and preferences. The group chat fills up with messages, changes, and competing ideas.
Coordination should not mean chasing replies.Each person decides what preferences to share. Their assistants compare dates and constraints, then suggest options for the group to consider.
People decide. Assistants coordinate.A shared itinerary preserves decisions and open tasks. Bookings, purchases, and payments still need separate authorization.
More plans made. Less chaos.In version one, every participant creates their own ChatGPT Project and connects SHAE manually. No one has to share their entire Project or join a common workspace. The first pilot takes advantage of an existing workspace.
*Dot may support persistent follow-up where the account and platform allow it. Real-world integration of Events and Projects must be validated. SHAE maintains its own records and permissions.
Independent accounts and assistants.
Recipient, purpose, and limits.
Share or ask (PUSH / PULL).
Recoverable history and sources.
Keep facts, review, and approval separate.
Choose a scenario to see how an interaction might work through SHAE. This is an explanatory simulation: it sends no real messages and does not connect to ChatGPT.
Let our AIs collaborate so people can work with more context, less friction, and better-informed decisions.