PROJECT 07 / 07 · AI SYSTEMS · SECURITY ARCHITECTURE
AI-assisted planning. Deterministic checks. Human authority.
DESIGN IN PROGRESS · NO CONNECTED RUNTIME
01 / THE CONTEXT
Professional workflows span documents, technical requirements and applications. Useful AI assistance needs more than a plausible answer: its proposed actions must stay within authorized scope, deterministic checks must test critical claims, and reviewers need evidence they can trace. This project investigates how those responsibilities could fit into a privately deployable workspace.
02 / MY ROLE
Independent architecture-stage research: defining module boundaries, evaluating execution and retrieval approaches, designing approval and evidence contracts, and assessing a replaceable AI runtime. This personal project is separate from employer-related internship work. The Codex and DeepSeek Harness environments have been downloaded for evaluation; integration, model selection and local inference remain under investigation.
03 / ENGINEERING NOTES
Defining a workspace for Chat, Projects, Documents, Tasks, Results and Approvals, with a planning layer that coordinates specialized tools within an explicitly authorized task scope.
Evaluating API integrations, Playwright and isolated desktop workers alongside document parsing, semantic retrieval and planned RAG workflows. These are proposed capabilities, not validated integrations.
Designing deterministic validation, supervised test execution, traceable evidence, least-privilege access and human approval gates. Critical decisions remain the responsibility of deterministic checks and authorized people.
04 / HIGH-LEVEL SYSTEM
Public-facing conceptual overview — not a disclosure of internal implementation.
05 / TECHNOLOGIES UNDER EVALUATION
06 / PROPOSED ARCHITECTURE
Explore the proposed architecture and its two application domains. Selecting a layer reveals its intended responsibility, interface and decision boundary; it does not execute an agent or contact a professional application.
An approved requirement, followed by evidence.
A planning and coordination layer would break down an authorized goal, select specialized tools and track the state of proposed work.
A model-generated plan is a proposal. It cannot approve its own access, bypass an approval gate or declare a critical check passed.
Interactive architecture explanation only. Selecting a layer or domain changes this diagram’s text; it does not run an agent, process documents or connect to an application.
Proposed architecture and feasibility research. No connected runtime, operational integration, validated security guarantee or production deployment is shown.
PRIVATE AGENTIC ENTERPRISE WORKSPACE / PROPOSED ARCHITECTURE / ARCHITECTURE DIAGRAMS
Three selected architecture illustrations explain the proposed platform layers, the intended orchestration relationships and a human-supervised task path.
Architecture & Feasibility — In Progress. These are conceptual diagrams, not screenshots of an implemented platform. Codex and DeepSeek Harness remain under evaluation; no connected runtime, completed integration, validated security boundary or production deployment is claimed.
A proposed system boundary for a private workspace: authorized users and interface layers lead toward orchestration, specialized responsibilities, controlled tools and human governance. Every capability shown is an architecture target, not implementation evidence.
AI-generated architecture illustration. Private model serving, storage, access control, monitoring and integrations remain proposed or under evaluation.07 / TWO PROPOSED DOMAINS
Both domains are feasibility targets. The architecture is intended to keep task scope, validation and human responsibility explicit across either workflow.
Investigate AI-assisted analysis of XML, Word, Excel and approved technical requirements. Deterministic validation and supervised software tests would produce evidence-based reports for authorized review.
Explore document, procurement, logistics and administrative workflows through scoped integrations. Structured outputs, meaningful approval gates and audit trails are proposed design requirements.
08 / ENGINEERING RESPONSIBILITIES
Current work centers on architectural reasoning: defining responsibilities, comparing integration paths, and making the future proof of concept testable.
Design explicit contracts between planning, permission, execution and validation. AI may propose a step or interpret evidence; it must not become the sole authority for a critical action or result.
Evaluate scoped APIs first, Playwright when a browser workflow is appropriate, and isolated desktop workers where needed. Compare feasibility and failure modes before selecting an integration approach.
Plan structured results that retain approved source references, rule definitions, test artifacts and unresolved findings. Reports should let an authorized reviewer retrace how a conclusion was reached.
Evaluate harnesses, models, databases and retrieval approaches against clear interfaces. The downloaded Codex and DeepSeek Harness environments are evaluation starting points, not validated platform integrations.
2026–present · Architecture-stage research
09 / PROPOSED DEVELOPMENT ROADMAP
The sequence is proposed, with no completion dates or performance promises. A successful proof of concept would guide later architectural decisions.
Define module contracts, trust boundaries and feasibility criteria; evaluate harness and model options.
Test one narrowly authorized task in an isolated environment with synthetic or approved public inputs.
Evaluate XML, Word and Excel parsing, source provenance, retrieval and deterministic rule checks.
Explore supervised API, browser and desktop test execution with explicit expected results and recovery paths.
Produce reviewable result bundles, approval records and source-linked reports from the proof of concept.
Challenge isolation, access controls, approval gates, untrusted-document handling and audit-log confidentiality.
AI provides planning and assistance. Deterministic checks and authorized humans retain responsibility for critical decisions.
All demonstrations will use synthetic or explicitly approved public data. Confidential clients, organizations, internal applications, specifications, private source code and internal documents will not be disclosed.
Code will be published after validation and confidentiality review. No public repository or live platform is linked at this stage.
Architecture & Feasibility — In Progress. Codex and DeepSeek Harness remain under evaluation; integration, model selection and local inference are not complete. All future demonstrations will use synthetic or explicitly approved public data. Confidential clients, organizations, internal applications, specifications, private source code and internal documents are excluded. No working platform, validated security boundary or production deployment is claimed.