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AI WORKFLOWS / LOCAL APPLICATION

Project Echo

A local workspace for coordinating AI-style roles, examining their contributions, and keeping the cost and authority of a workflow explicit.

MY ROLE

Product concept, workflow requirements, evaluation constraints, interface direction, and integration priorities.

PROJECT MILESTONE

Verified local prototype

PROJECT ECHO01
echo

Build. Investigate. Challenge. Synthesize.

AIARCHITECTURE STUDY
01 / THE CHALLENGE

Many perspectives. One workspace.

Multi-agent workflows become difficult to evaluate when the final answer hides the intermediate decisions, costs, and failed attempts. Echo explores a more inspectable way to coordinate work.

02 / THE THINKING

Decisions that
shape the system.

01

Give each role a clear job

Builder, Investigator, Challenger, and Synthesizer roles support collective, focused-pair, and critical-review workflows.

02

Make execution visible

Keep contributions, attachments, cancellation, search, and durable run receipts in the same local workspace.

03

Treat budgets as shared constraints

Integrate the token-counter project for estimates, policy checks, and usage normalization. Live dispatch depends on validated shared accounting authority.

04

Keep evaluation proportionate

Use a small set of safe, meaningful scenarios and clearly identify simulated execution.

HOW THE PIECES CONNECT Conceptual architecture
  1. Define the task
  2. Build / investigate
  3. Challenge
  4. Synthesize
  5. Review the receipt

Inside the implementation

A bounded script sandbox adds a place for controlled calculations without granting arbitrary filesystem or network access. The wider architecture separates the interface, orchestration, and accounting authority so adding live model execution requires an explicit integration, not a browser-side API key.

03 / THE RESULT

What the work
demonstrates.

The local application and zero-token simulation path were verified with 36 recorded checks. The workspace demonstrates workflow orchestration, persistence, and integration behavior.

Why it matters to a client

A practical example of shaping AI-assisted tools around visibility, cost discipline, and human review.

Local desktop workflowRole orchestrationToken accountingQuickJS sandboxPersistent receipts
KEEP EXPLORINGAPI token accounting
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