Vibecode Hive CPQ
track this build5 steps, step by step0%KINDA · weekend project
The mechanical core of CPQ is not mysterious: a product tree, option groups, compatibility rules, a pricing formula, a PDF at the end. An agent can produce a working configurator for one product family in a weekend, and if you sell a few hundred SKUs with predictable option logic, that build may genuinely be enough. What you are not one-shotting is the part that makes CPQ a purchase: ERP and CRM sync, dealer accounts with their own price lists and discounts, 3D or 2D visual previews, multi-language catalogs, and someone maintaining the rule set when engineering changes a hinge. Also worth being honest that CPQ failure is expensive: a bad rule ships a quote that cannot be manufactured at the price you promised. So: buildable, and a bad idea to trust for anything you actually invoice on until the rules have been beaten on for months.
the project pack4 files · fastest path to a working personal build
You are building a lean indie version of Hive CPQ. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Hive CPQ indie build ## Goal Build the smallest trustworthy replacement for the core Hive CPQ workflow for one developer or a tiny team. ## Scope A local web app where you define option groups, compatibility rules and pricing formulas in a config file, then walk through a guided configurator that validates choices, prices the result and exports a branded quote PDF. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - ERP and CRM integrations, so accepted quotes become copy-paste work - A dealer or reseller portal with per-account price lists, discount tiers and order history - Visual product previews, 3D or otherwise, which is often the thing that closes the sale - Anyone but you maintaining the rule engine when the catalog changes - Version control on quotes and catalogs, audit trails, and the boring guarantees a buyer expects when a quote is contractual If those capabilities are essential, use Hive CPQ instead of pretending the gap is solved. ===== AGENTS.md ===== # Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs". ===== BUILD_PLAN.md ===== # Build plan ## Original build brief Build a local configure-price-quote tool for a single manufacturer with a configurable product line. Stack, no substitutions: Next.js App Router with TypeScript, Tailwind, SQLite via better-sqlite3, PDF generation with @react-pdf/renderer. Runs with npm run dev. No auth provider, no cloud services, no telemetry. Catalog definition lives in /catalog/*.yaml, loaded at startup and validated with zod. A catalog file defines: product families, option groups (each with a type of single-select, multi-select or numeric), options with id, label, price delta and optional lead time, and rules. Support three rule kinds: requires, excludes, and a constraint expression evaluated against the current selection. Fail loudly on invalid catalog files, do not silently skip. Pricing: each option contributes a delta; support a per-family formula string, evaluated with a small safe expression evaluator over selected values and quantities, plus configurable margin and discount percentages. Show a live price breakdown line by line, never just a total. Configurator UI: pick a family, then step through option groups. Invalid options are disabled with the rule that blocked them shown in plain text. Selections persist in the URL so a configuration is shareable as a link. Quotes: save a configuration as a quote with customer name, quote number, valid-until date, notes and line items. Quotes are immutable once marked sent; edits create a new revision that references the previous one. List view with filter by status. PDF: one branded quote template reading company name, address and logo path from .env. Include the option breakdown, totals, lead time and validity date. Seed with a fake product family of about twenty options and at least four interacting rules, so the rule engine is exercised on first run. Include a rules test suite with vitest: for each catalog file, assert that seeded valid configurations price correctly and that known-invalid combinations are rejected. Out of scope, do not build: ERP or CRM integration, 3D or image visualization, dealer accounts and per-customer price lists, multi-currency, tax calculation, email sending, payments, multi-tenancy. Write a README covering catalog file format, rule syntax, and a blunt warning that pricing rules must be tested before any quote leaves the building. ## Required capabilities - Your own product rules written down: option groups, incompatibilities, required combinations - A pricing model you can express as formulas, base price plus option deltas plus margin - Node 20 and a place to run it, local or a small VPS - Manual re-entry of accepted quotes into whatever ERP or accounting system you actually use ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden. ===== .env.example ===== # Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
You are building a lean indie version of Hive CPQ. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Hive CPQ indie build ## Goal Build the smallest trustworthy replacement for the core Hive CPQ workflow for one developer or a tiny team. ## Scope A local web app where you define option groups, compatibility rules and pricing formulas in a config file, then walk through a guided configurator that validates choices, prices the result and exports a branded quote PDF. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - ERP and CRM integrations, so accepted quotes become copy-paste work - A dealer or reseller portal with per-account price lists, discount tiers and order history - Visual product previews, 3D or otherwise, which is often the thing that closes the sale - Anyone but you maintaining the rule engine when the catalog changes - Version control on quotes and catalogs, audit trails, and the boring guarantees a buyer expects when a quote is contractual If those capabilities are essential, use Hive CPQ instead of pretending the gap is solved. ===== AGENTS.md ===== # Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs". ===== BUILD_PLAN.md ===== # Build plan ## Original build brief Build a local configure-price-quote tool for a single manufacturer with a configurable product line. Stack, no substitutions: Next.js App Router with TypeScript, Tailwind, SQLite via better-sqlite3, PDF generation with @react-pdf/renderer. Runs with npm run dev. No auth provider, no cloud services, no telemetry. Catalog definition lives in /catalog/*.yaml, loaded at startup and validated with zod. A catalog file defines: product families, option groups (each with a type of single-select, multi-select or numeric), options with id, label, price delta and optional lead time, and rules. Support three rule kinds: requires, excludes, and a constraint expression evaluated against the current selection. Fail loudly on invalid catalog files, do not silently skip. Pricing: each option contributes a delta; support a per-family formula string, evaluated with a small safe expression evaluator over selected values and quantities, plus configurable margin and discount percentages. Show a live price breakdown line by line, never just a total. Configurator UI: pick a family, then step through option groups. Invalid options are disabled with the rule that blocked them shown in plain text. Selections persist in the URL so a configuration is shareable as a link. Quotes: save a configuration as a quote with customer name, quote number, valid-until date, notes and line items. Quotes are immutable once marked sent; edits create a new revision that references the previous one. List view with filter by status. PDF: one branded quote template reading company name, address and logo path from .env. Include the option breakdown, totals, lead time and validity date. Seed with a fake product family of about twenty options and at least four interacting rules, so the rule engine is exercised on first run. Include a rules test suite with vitest: for each catalog file, assert that seeded valid configurations price correctly and that known-invalid combinations are rejected. Out of scope, do not build: ERP or CRM integration, 3D or image visualization, dealer accounts and per-customer price lists, multi-currency, tax calculation, email sending, payments, multi-tenancy. Write a README covering catalog file format, rule syntax, and a blunt warning that pricing rules must be tested before any quote leaves the building. ## Required capabilities - Your own product rules written down: option groups, incompatibilities, required combinations - A pricing model you can express as formulas, base price plus option deltas plus margin - Node 20 and a place to run it, local or a small VPS - Manual re-entry of accepted quotes into whatever ERP or accounting system you actually use ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden. ===== .env.example ===== # Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
You are building a production product version of Hive CPQ. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== PRODUCT.md ===== # Hive CPQ product brief ## Problem The mechanical core of CPQ is not mysterious: a product tree, option groups, compatibility rules, a pricing formula, a PDF at the end. An agent can produce a working configurator for one product family in a weekend, and if you sell a few hundred SKUs with predictable option logic, that build may genuinely be enough. What you are not one-shotting is the part that makes CPQ a purchase: ERP and CRM sync, dealer accounts with their own price lists and discounts, 3D or 2D visual previews, multi-language catalogs, and someone maintaining the rule set when engineering changes a hinge. Also worth being honest that CPQ failure is expensive: a bad rule ships a quote that cannot be manufactured at the price you promised. So: buildable, and a bad idea to trust for anything you actually invoice on until the rules have been beaten on for months. ## Product outcome A local web app where you define option groups, compatibility rules and pricing formulas in a config file, then walk through a guided configurator that validates choices, prices the result and exports a branded quote PDF. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - Your own product rules written down: option groups, incompatibilities, required combinations - A pricing model you can express as formulas, base price plus option deltas plus margin - Node 20 and a place to run it, local or a small VPS - Manual re-entry of accepted quotes into whatever ERP or accounting system you actually use ## Explicit non-goals for v1 - ERP and CRM integrations, so accepted quotes become copy-paste work - A dealer or reseller portal with per-account price lists, discount tiers and order history - Visual product previews, 3D or otherwise, which is often the thing that closes the sale - Anyone but you maintaining the rule engine when the catalog changes - Version control on quotes and catalogs, audit trails, and the boring guarantees a buyer expects when a quote is contractual ## Success criteria - The primary workflow is measurable end to end. - Setup is reproducible in a clean environment. - Failure, recovery, and support paths are documented. - Product claims match what the implementation actually guarantees. ===== ARCHITECTURE.md ===== # Architecture ## Starting brief Build a local configure-price-quote tool for a single manufacturer with a configurable product line. Stack, no substitutions: Next.js App Router with TypeScript, Tailwind, SQLite via better-sqlite3, PDF generation with @react-pdf/renderer. Runs with npm run dev. No auth provider, no cloud services, no telemetry. Catalog definition lives in /catalog/*.yaml, loaded at startup and validated with zod. A catalog file defines: product families, option groups (each with a type of single-select, multi-select or numeric), options with id, label, price delta and optional lead time, and rules. Support three rule kinds: requires, excludes, and a constraint expression evaluated against the current selection. Fail loudly on invalid catalog files, do not silently skip. Pricing: each option contributes a delta; support a per-family formula string, evaluated with a small safe expression evaluator over selected values and quantities, plus configurable margin and discount percentages. Show a live price breakdown line by line, never just a total. Configurator UI: pick a family, then step through option groups. Invalid options are disabled with the rule that blocked them shown in plain text. Selections persist in the URL so a configuration is shareable as a link. Quotes: save a configuration as a quote with customer name, quote number, valid-until date, notes and line items. Quotes are immutable once marked sent; edits create a new revision that references the previous one. List view with filter by status. PDF: one branded quote template reading company name, address and logo path from .env. Include the option breakdown, totals, lead time and validity date. Seed with a fake product family of about twenty options and at least four interacting rules, so the rule engine is exercised on first run. Include a rules test suite with vitest: for each catalog file, assert that seeded valid configurations price correctly and that known-invalid combinations are rejected. Out of scope, do not build: ERP or CRM integration, 3D or image visualization, dealer accounts and per-customer price lists, multi-currency, tax calculation, email sending, payments, multi-tenancy. Write a README covering catalog file format, rule syntax, and a blunt warning that pricing rules must be tested before any quote leaves the building. ## Boundaries Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors. ## Production baseline - Configuration: validated at startup with safe local defaults where possible. - Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts. - Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test. ## Decision records For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it. ===== AGENTS.md ===== # Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone. ===== MILESTONES.md ===== # Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations. ===== OPERATIONS.md ===== # Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted Hive CPQ capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
README.md
# Hive CPQ indie build ## Goal Build the smallest trustworthy replacement for the core Hive CPQ workflow for one developer or a tiny team. ## Scope A local web app where you define option groups, compatibility rules and pricing formulas in a config file, then walk through a guided configurator that validates choices, prices the result and exports a branded quote PDF. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - ERP and CRM integrations, so accepted quotes become copy-paste work - A dealer or reseller portal with per-account price lists, discount tiers and order history - Visual product previews, 3D or otherwise, which is often the thing that closes the sale - Anyone but you maintaining the rule engine when the catalog changes - Version control on quotes and catalogs, audit trails, and the boring guarantees a buyer expects when a quote is contractual If those capabilities are essential, use Hive CPQ instead of pretending the gap is solved.
AGENTS.md
# Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs".
BUILD_PLAN.md
# Build plan ## Original build brief Build a local configure-price-quote tool for a single manufacturer with a configurable product line. Stack, no substitutions: Next.js App Router with TypeScript, Tailwind, SQLite via better-sqlite3, PDF generation with @react-pdf/renderer. Runs with npm run dev. No auth provider, no cloud services, no telemetry. Catalog definition lives in /catalog/*.yaml, loaded at startup and validated with zod. A catalog file defines: product families, option groups (each with a type of single-select, multi-select or numeric), options with id, label, price delta and optional lead time, and rules. Support three rule kinds: requires, excludes, and a constraint expression evaluated against the current selection. Fail loudly on invalid catalog files, do not silently skip. Pricing: each option contributes a delta; support a per-family formula string, evaluated with a small safe expression evaluator over selected values and quantities, plus configurable margin and discount percentages. Show a live price breakdown line by line, never just a total. Configurator UI: pick a family, then step through option groups. Invalid options are disabled with the rule that blocked them shown in plain text. Selections persist in the URL so a configuration is shareable as a link. Quotes: save a configuration as a quote with customer name, quote number, valid-until date, notes and line items. Quotes are immutable once marked sent; edits create a new revision that references the previous one. List view with filter by status. PDF: one branded quote template reading company name, address and logo path from .env. Include the option breakdown, totals, lead time and validity date. Seed with a fake product family of about twenty options and at least four interacting rules, so the rule engine is exercised on first run. Include a rules test suite with vitest: for each catalog file, assert that seeded valid configurations price correctly and that known-invalid combinations are rejected. Out of scope, do not build: ERP or CRM integration, 3D or image visualization, dealer accounts and per-customer price lists, multi-currency, tax calculation, email sending, payments, multi-tenancy. Write a README covering catalog file format, rule syntax, and a blunt warning that pricing rules must be tested before any quote leaves the building. ## Required capabilities - Your own product rules written down: option groups, incompatibilities, required combinations - A pricing model you can express as formulas, base price plus option deltas plus margin - Node 20 and a place to run it, local or a small VPS - Manual re-entry of accepted quotes into whatever ERP or accounting system you actually use ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden.
.env.example
# Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
PRODUCT.md
# Hive CPQ product brief ## Problem The mechanical core of CPQ is not mysterious: a product tree, option groups, compatibility rules, a pricing formula, a PDF at the end. An agent can produce a working configurator for one product family in a weekend, and if you sell a few hundred SKUs with predictable option logic, that build may genuinely be enough. What you are not one-shotting is the part that makes CPQ a purchase: ERP and CRM sync, dealer accounts with their own price lists and discounts, 3D or 2D visual previews, multi-language catalogs, and someone maintaining the rule set when engineering changes a hinge. Also worth being honest that CPQ failure is expensive: a bad rule ships a quote that cannot be manufactured at the price you promised. So: buildable, and a bad idea to trust for anything you actually invoice on until the rules have been beaten on for months. ## Product outcome A local web app where you define option groups, compatibility rules and pricing formulas in a config file, then walk through a guided configurator that validates choices, prices the result and exports a branded quote PDF. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - Your own product rules written down: option groups, incompatibilities, required combinations - A pricing model you can express as formulas, base price plus option deltas plus margin - Node 20 and a place to run it, local or a small VPS - Manual re-entry of accepted quotes into whatever ERP or accounting system you actually use ## Explicit non-goals for v1 - ERP and CRM integrations, so accepted quotes become copy-paste work - A dealer or reseller portal with per-account price lists, discount tiers and order history - Visual product previews, 3D or otherwise, which is often the thing that closes the sale - Anyone but you maintaining the rule engine when the catalog changes - Version control on quotes and catalogs, audit trails, and the boring guarantees a buyer expects when a quote is contractual ## Success criteria - The primary workflow is measurable end to end. - Setup is reproducible in a clean environment. - Failure, recovery, and support paths are documented. - Product claims match what the implementation actually guarantees.
ARCHITECTURE.md
# Architecture ## Starting brief Build a local configure-price-quote tool for a single manufacturer with a configurable product line. Stack, no substitutions: Next.js App Router with TypeScript, Tailwind, SQLite via better-sqlite3, PDF generation with @react-pdf/renderer. Runs with npm run dev. No auth provider, no cloud services, no telemetry. Catalog definition lives in /catalog/*.yaml, loaded at startup and validated with zod. A catalog file defines: product families, option groups (each with a type of single-select, multi-select or numeric), options with id, label, price delta and optional lead time, and rules. Support three rule kinds: requires, excludes, and a constraint expression evaluated against the current selection. Fail loudly on invalid catalog files, do not silently skip. Pricing: each option contributes a delta; support a per-family formula string, evaluated with a small safe expression evaluator over selected values and quantities, plus configurable margin and discount percentages. Show a live price breakdown line by line, never just a total. Configurator UI: pick a family, then step through option groups. Invalid options are disabled with the rule that blocked them shown in plain text. Selections persist in the URL so a configuration is shareable as a link. Quotes: save a configuration as a quote with customer name, quote number, valid-until date, notes and line items. Quotes are immutable once marked sent; edits create a new revision that references the previous one. List view with filter by status. PDF: one branded quote template reading company name, address and logo path from .env. Include the option breakdown, totals, lead time and validity date. Seed with a fake product family of about twenty options and at least four interacting rules, so the rule engine is exercised on first run. Include a rules test suite with vitest: for each catalog file, assert that seeded valid configurations price correctly and that known-invalid combinations are rejected. Out of scope, do not build: ERP or CRM integration, 3D or image visualization, dealer accounts and per-customer price lists, multi-currency, tax calculation, email sending, payments, multi-tenancy. Write a README covering catalog file format, rule syntax, and a blunt warning that pricing rules must be tested before any quote leaves the building. ## Boundaries Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors. ## Production baseline - Configuration: validated at startup with safe local defaults where possible. - Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts. - Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test. ## Decision records For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it.
AGENTS.md
# Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone.
MILESTONES.md
# Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations.
OPERATIONS.md
# Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted Hive CPQ capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
$ choose a build depth, inspect the files, then open the complete pack in your agent · this prompt is generated from the build plan · improve it via PR
Because the software is the cheap part. Manufacturers pay for a vendor who will sit with their engineers, turn a messy catalog and a folder of Excel price lists into a rule set that does not produce impossible configurations, then keep it working as products change and push results into ERP. A solo build covers your own product line if you are the engineer, the salesperson and the person who maintains the rules. A company with fifty dealers and a configurable machine cannot staff that with one person and a JSON file.
xERP and CRM integrations, so accepted quotes become copy-paste work
xA dealer or reseller portal with per-account price lists, discount tiers and order history
xVisual product previews, 3D or otherwise, which is often the thing that closes the sale
xAnyone but you maintaining the rule engine when the catalog changes
xVersion control on quotes and catalogs, audit trails, and the boring guarantees a buyer expects when a quote is contractual
Nothing worth pointing at. That's why the prompt exists.
share on X ↗"I just replaced Hive CPQ with one prompt"
Vibecode Hive CPQ
Kinda. The core of Hive CPQ is buildable in a weekend with the prompt on this page, but there are real gaps: ERP and CRM integrations, so accepted quotes become copy-paste work, A dealer or reseller portal with per-account price lists, discount tiers and order history. Read the honest list above before committing.
How much does Hive CPQ cost?
Hive CPQ's pricing is usage-based or varies by plan · No pricing page exists: /pricing returns 404 and the sitemap index lists no pricing URL. Site offers 'Request a trial' and 'Talk to an expert' only..
What do I lose by replacing Hive CPQ?
Honestly: ERP and CRM integrations, so accepted quotes become copy-paste work; A dealer or reseller portal with per-account price lists, discount tiers and order history; Visual product previews, 3D or otherwise, which is often the thing that closes the sale; Anyone but you maintaining the rule engine when the catalog changes; Version control on quotes and catalogs, audit trails, and the boring guarantees a buyer expects when a quote is contractual. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to Hive CPQ?
No mature open-source alternative worth pointing at, which is exactly why the one-shot prompt on this page exists.