Working product tool · system architecture
AI Systems blueprint lab
Choose one or more outcomes, use practical presets or write in what you know, skip what you do not, then keep a structured first build, architecture, controls, evidence plan, and production-gap record—or explicitly share it with contact details for Arian's review.
- Status
- Working demo
- Date
- July 2026
- Role
- Agent Layer product strategy, system architecture, deterministic planning logic, interface design, implementation, and QA
- Context
- Public Agent Layer planning tool using deterministic browser-side generation. Optional AI refinement is bounded, explicit, and non-essential; contact details and the blueprint are persisted only after a separate consented follow-up submission.
- Stack / direction
- Next.js · React · TypeScript · Local deterministic state · Cloudflare D1 lead handoff
Agent Layer working demonstrationProblem and constraints
Buyers can recognize that AI might help but still lack a usable map of the first workflow, data, integrations, controls, evidence, and production decisions.
- The core result must work without an AI provider
- Visitor context cannot be submitted or retained automatically
- Contact storage requires explicit privacy and reply consent
- Recommendations must expose limitations and production gaps
Key decisions
Make the smallest useful system visible before scope expands.
- 01
Require only a useful business outcome
- 02
Offer presets, optional write-ins, and explicit skip paths for discovery context
- 03
Generate one deterministic recommendation and four-stage system map
- 04
Make every result copyable and downloadable before any sharing decision
- 05
Offer a separate consented follow-up form with durable storage, deduplication, abuse controls, and protected staff retrieval
Architecture
From business context to a four-stage implementation blueprint.
- 1Multi-outcome selection
- 2Guided organization and workflow context
- 3Deterministic blueprint engine
- 4Visitor-owned exports
- 5Consented D1 lead handoff
Evidence currently available
Functional blueprint builder
The public route generates a localized blueprint with a recommended solution, smallest first build, journey, four stages, data, integrations, controls, evidence, gaps, and next decisions.
Source: Local Agent Layer implementation and Playwright coverage · 2026-07-15Privacy and provider boundary
Deterministic generation is local and complete. Copy, downloads, optional AI refinement, and contact handoff occur only after explicit visitor actions; lead storage additionally requires privacy and reply consent.
Source: Public interface disclosure, schema, and implementation · 2026-07-18Durable human-review handoff
The optional form stores normalized contact details, source, consent, and the selected blueprint in D1, returns a durable lead ID, deduplicates retries, rate-limits abuse, expires records after 180 days, and exposes records only through a protected operator API.
Source: Lead schema, D1 migration, Worker routes, privacy notice, and regression coverage · 2026-07-18Confidentiality: No visitor description or blueprint is retained automatically. A follow-up record is stored only after explicit privacy and reply consent; it excludes marketing consent, uses hashed abuse identifiers, and expires after 180 days.
Contribution and transparency
Arian's contribution
- Product framing
- Capability model
- Deterministic blueprint rules
- Interface implementation and testing
Assistance and platforms
- AI-assisted development tools used under Agent Layer direction and review
- Phosphor icon library
No client delivery or external team contribution is claimed for this self-initiated demonstration.