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Bookiji Inc engineering

Engineering at Bookiji

How we build: products, agents, people decisions, and proof. This page stays current — it is not a claim that every idea is done.

Portfolio and platform architecture

Bookiji Inc is the company hub at www.bookiji.com. Each product lives in its own repo with its own scope. The Bookiji booking app is a sibling product — not this company site.

This page explains the model in public terms. The real proof lives in the product repos and the ops systems that are allowed to hold it.

Agent-assisted delivery

Agents help with bounded work: understand a task, draft a change, dig through evidence, and list what still needs checking. They stay inside repo rules. A change that exists is not the same as a change that works.

We start from the product bootstrap and standards, keep diffs reviewable, and leave enough trail that someone else can re-check the call. Bigger work also gets prompt-history and recon checks so it does not vanish into chat.

Human authorization points

People still own the hard calls: scope, review, sensitive actions, releases, and anything we say in public. Agents speed things up. They do not get to sign off.

Platform standards

Bookiji keeps a numbered set of engineering standards in the umbrella repo. Agents and humans are expected to read the ones that apply before changing behavior. This page lists the topics in public language — the full normative text stays in the private standards docs.

  1. 01·Global engineering rules

    How agents and humans are expected to work in these repos.

  2. 02·Secrets and config

    Secrets stay in the vault — never in Git, chat, or screenshots.

  3. 03·Auth and identity

    Login methods must resolve to one account for the same verified email.

  4. 04·Database and migrations

    Shared database per environment; products stay in their own schemas via migrations, with a fail-closed apply gate before schema-dependent work.

  5. 05·Payments and Stripe

    Billing rules for products that take money.

  6. 06·Testing and verification

    What “tested” means, and how we report PASS / FAIL / NOT_RUN.

  7. 07·Git and repo operations

    How the umbrella and product repos stay in sync.

  8. 08·CI/CD, release, and commit routing

    Where code lands, how we deploy, and what GitHub is (and is not) for.

  9. 09·Agent execution and scheduled automation

    How agents report work, and how recurring jobs are supposed to run.

  10. 10–11·Docs and product manifests

    Keep docs honest; every product declares its scope.

  11. 12·Operational tooling baseline

    Health checks, error capture, and basic ops hygiene.

  12. 13·Operator master access

    Break-glass operator login — separate from normal member accounts.

  13. 14·Work tracking (GitHub)

    Issues and Bookiji Delivery are the work tracker — not chat or memory.

  14. 15·Public demo vs real access

    Demo mode and operator access are not the same thing.

  15. 16·Verification personas

    Prove the product for real users — not only the founder account.

  16. 17·Commercial multi-user products

    Subscription products must support many independent accounts from day one.

  17. 18·Workspace Self identity

    AI drafts stay first-person as the account owner — never invert who “I” is.

Related practice (not numbered 01–18): see Global Fair Pricing, AI standards and Support / Help Center below.

Global Fair Pricing

Verified practice

Bookiji products can use a shared platform pricing policy that adapts commercial offers to governed international markets while respecting sustainable product economics, payment-provider independence, and subscriber protections. The system separates thoughtful market accessibility from unsustainable discounting.

Commercial Pricing Resolution Flow

Product economics
Market policy
Provider capability
Global Fair Pricing
Authoritative Resolver
Explicit local price
Provider fallback

One shared policy

Verified practice

Individual products consume a central platform pricing engine rather than maintaining divergent regional logic.

Local market != FX conversion

Verified practice

A marketable local commercial price is a deliberate policy decision on structured ladders, not a naive daily exchange-rate calculation.

Economic guardrails

Verified practice

Sustainable product profitability floors ensure localized pricing never breaches core unit margins or infrastructure costs.

Provider-independent

Verified practice

Payment processors handle transaction mechanics; Bookiji owns commercial policy and regional market rules.

Safe fallback

Verified practice

When a market is not explicitly governed, provider-localized checkout is used instead of inventing arbitrary prices.

Subscriber protection

Verified practice

Existing subscribers are grandfathered by default; commercial pricing adjustments apply only to new checkouts.

Observe, don’t thrash

Verified practice

Pricing health is evaluated on a regular schedule without automatically thrashing or modifying active subscriber rates.

Traceable explainability

Verified practice

Every commercial price resolution returns structured metadata tracing the applied market rule, currency, and provider strategy.

Status: Shared platform capability available for product adoption. Individual products adopt the policy across scheduled rollout gates.

AI standards

How Bookiji keeps product AI honest: shared runtime rules, Workspace Self, and curated Help retrieval where Help ships. Status tags use the same legend as the operational control plane.

Shared AI runtime contract

Verified practice

Provider modes, a deterministic truth boundary, explicit fallbacks, and structured response metadata — so models explain trusted facts instead of inventing them.

Workspace Self

Verified practice

First-person drafts stay owned by the account (see Platform standard 18). The model must not invert who “I” is.

Curated support retrieval

Implemented control

Products that ship Help ground answers in curated knowledge — notably JobHuntrX, plus Kinetix and the Bookiji Help hub. This is retrieval inside those products, not a company-wide single RAG product.

Portfolio Help + retrieval rollout

In progress

We are rolling the same Help and retrieval pattern across more products. Resolved tickets reach the knowledge base only after operator curation — not by auto-feeding questions into FAQ.

Support / Help Center

Help is written as a standard, then proven product by product. Knowledge improves when resolved tickets are curated by operators into the help knowledge base — not when questions auto-feed FAQ.

Help Center standard

Verified practice

A written standard for AI-first Help: curated knowledge, controlled escalation, and honest fallbacks when AI is unavailable.

JobHuntrX Help reference loop

Implemented control

JobHuntrX is the reference product loop for ask → escalate → resolve → curated reinjection into Help knowledge.

Kinetix Help curated reinjection

Implemented control

Kinetix ships curated reinjection v1 so resolved support knowledge can re-enter Help after operator review.

Ops Center federated Help index

Implemented control

Ops Center shows a portfolio Help index of pointers only — not a second ticket store, and not raw conversations.

Portfolio-wide Help loop

In progress

Extending the same Help loop across the portfolio. Path: resolved tickets → operator curation → help knowledge base.

Verification gates

Keep changes small enough to review. Public UI should be clear, usable, and responsive. When we verify, we report what each check actually did — missing checks stay NOT_RUN, not a silent pass.

Hover or focus each check to see what it covers.

Issue-to-release traceability

Ideal path: issue → change → review → checks → ship or publish. GitHub Issues and PRs hold the live work. Docs keep the longer-lived stuff: standards, architecture, runbooks, evidence.

We also look the other way: real Git work should show up as tracked work, and “done” work should not sit unlanded forever. Recon is there to catch that drift.

Operational control plane

Recurring ops work is moving into one shared view. Not autopilot shipping — just one place to see schedules, outcomes, recommendations, security findings, and unfinished work.

Status legend

Verified practice

We can point to a real standard, doc, or release record that backs the claim.

Implemented control

The control exists in a repo and you can check how it works.

In progress

We wrote down the intent, but we still need proof it works in practice.

Scheduler hub

Implemented control

A simple ops view of scheduler state — no digging through each job by hand.

Structured outcomes

Implemented control

Scheduled jobs can report, recommend, open a tracked issue under rules, or do small maintenance.

Security-advisor intake

Implemented control

Supabase Security Advisor findings can land in the same issue queue instead of a side inbox.

Prompt and work reconciliation

Implemented control

We compare agent session history with Git and Bookiji Delivery so finished or orphaned work is easier to spot.

Migration apply gate

Implemented control

Agents must verify schema is applied before diagnosing missing-table failures; non-prod can auto-apply, production apply stays human-confirmed.

Prompteus dispatch

In progress

Prompteus will help decide and dispatch work. Issues and Bookiji Delivery stay the tracker of record.

Executor gateway

Implemented control

ChatGPT can dispatch local Cursor/Cline executors through GitHub. Process completion is recorded separately from whether the task answer was actually correct. Adaptive routing is not live.

Prompt ledger and work reconciliation

Chat history is useful context. It is not the work tracker. We harvest supported agent sessions into a searchable prompt ledger, and Ops Center has a Recon view that lines that up with Git and Bookiji Delivery.

For serious work, agents should search that history when it helps and link or open a GitHub Issue. Issues and Bookiji Delivery stay the source of truth. Memories and future Prompteus decisions are context — they do not quietly override the board.

Execution-time agent safeguards

This is a new workstation rail (installed Aug 2026), not an old platform tradition. Before a coding agent runs a shell command, Cursor (and other supported tools) call a local guard called DCG. It checks the command against a small rule pack for risky Git and filesystem moves — for example git reset --hard or wiping a root/home tree — and can deny it in a few milliseconds.

The pack stays narrow on purpose. Normal solo work still goes through. Stricter “no direct push to main” rules stay off so day-to-day shipping is not blocked.

Security and environment governance

In public we keep it practical: least privilege, separate environments, secrets stay protected, people approve sensitive moves, and we review what we publish. The detailed evidence stays where it belongs.

Security Advisor findings can now feed the shared issue path so ERROR-level items are less likely to get stranded. Found ≠ fixed. Planned ≠ shipped. Shipped ≠ proven everywhere.

JobHuntrX case study

JobHuntrX is the first real case study for this model, and it is still a controlled preview. You can try the demo. Bigger product, revenue, or “it works” claims need fresh proof from the product itself.

View the JobHuntrX preview

Evidence boundaries

This page does not claim launch readiness, commercial traction, compliance badges, full localization, accessibility certification, bulletproof security, full prompt coverage, unattended releases, or any metric. Tests prove what they cover — not the whole product.

If a gate did not run, we say NOT_RUN. That is not a fail, and it is not a pass.