Vibecode Mailient
track this build5 steps, step by step0%KINDA · weekend project
The core trick here, pull mail, classify it, summarize threads, draft replies, is genuinely a weekend of work now that an LLM does the hard part. An agent can wire IMAP plus SQLite plus a cheap web UI and have working triage before dinner. The gaps are all the unglamorous parts: Gmail and Outlook OAuth, push sync instead of polling, threading edge cases, and the fact that you will read this thing on a phone and your build has no app. Nothing here is protected by data or network, so a personal version keeps most of the value if you accept that you are now the ops team for your own mail pipeline. Product details and pricing are thin from the outside, so treat the specifics as unverified.
the project pack4 files · fastest path to a working personal build
You are building a lean indie version of Mailient. 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 ===== # Mailient indie build ## Goal Build the smallest trustworthy replacement for the core Mailient workflow for one developer or a tiny team. ## Scope Polls your IMAP inbox, classifies and summarizes each thread with an LLM, and parks suggested replies in a local review queue you approve before sending. ## 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: - A mobile app and real push notifications, which is where most email actually gets read - Managed OAuth with Google and Microsoft, including the review process and token refresh pain - Someone else absorbing provider API changes, rate limits and broken threading - Polish: keyboard shortcuts, fast search, snooze, undo send, offline behavior - Any sending reputation work if the product handles outbound at scale If those capabilities are essential, use Mailient 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 AI email triage tool called Inbox Warden in this empty folder. Stack, no substitutions: TypeScript on Node 20, Fastify for the server, server-rendered HTML with htmx for the UI, better-sqlite3 for storage, imapflow for reading mail, nodemailer for sending, and one OpenAI-compatible chat completions endpoint for the AI. No React, no Next, no Docker, no cloud services, no telemetry, no user accounts. This runs on localhost for exactly one person. Secrets in .env, read with a tiny loader, and ship a .env.example with: IMAP_HOST, IMAP_PORT, IMAP_USER, IMAP_PASS, SMTP_HOST, SMTP_PORT, LLM_BASE_URL, LLM_API_KEY, LLM_MODEL. Never log credentials or full message bodies. What is in scope: - A sync job that connects over IMAP, fetches messages from INBOX since a stored high water mark, and stores id, thread key, from, to, subject, date, plain text body and raw headers in SQLite. Dedupe on Message-ID. Make sync idempotent and resumable. - Strip HTML to text and truncate long bodies before sending anything to the model. - For each new thread: one LLM call returning strict JSON with category (one of urgent, needs-reply, fyi, newsletter, junk), a two sentence summary, and a suggested reply draft when category is needs-reply or urgent. Validate the JSON with zod and retry once on parse failure. - Cache results keyed by thread and message count so restarts do not re-bill you. - A web UI at / with a triage queue grouped by category, thread detail view, and an editable draft box with Approve and Send, Skip, and Mark Junk. Nothing is ever sent without an explicit click. - Sending via SMTP with correct In-Reply-To and References headers so replies thread properly. - A rules table for cheap deterministic overrides by sender or subject substring, applied before any LLM call. - npm run sync, npm run dev, and a --dry-run flag that classifies without sending. Explicitly out of scope: OAuth flows, mobile app, push notifications, multi-account support, calendar, attachments beyond recording filenames, search beyond a SQL LIKE query. Write a README with setup steps, an honest limitations section that says polling is not push and that message text leaves the machine for the model, and a cost note estimating tokens per hundred emails. Include a fixture-based test for the classifier JSON parser that does not hit the network. ## Required capabilities - An email account with IMAP/SMTP access and an app password, or patience for OAuth - An LLM API key, and acceptance that your mail text goes to that provider - A machine or small VPS that stays awake to poll - Basic comfort debugging MIME, threading and character encodings ## 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 Mailient. 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 ===== # Mailient indie build ## Goal Build the smallest trustworthy replacement for the core Mailient workflow for one developer or a tiny team. ## Scope Polls your IMAP inbox, classifies and summarizes each thread with an LLM, and parks suggested replies in a local review queue you approve before sending. ## 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: - A mobile app and real push notifications, which is where most email actually gets read - Managed OAuth with Google and Microsoft, including the review process and token refresh pain - Someone else absorbing provider API changes, rate limits and broken threading - Polish: keyboard shortcuts, fast search, snooze, undo send, offline behavior - Any sending reputation work if the product handles outbound at scale If those capabilities are essential, use Mailient 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 AI email triage tool called Inbox Warden in this empty folder. Stack, no substitutions: TypeScript on Node 20, Fastify for the server, server-rendered HTML with htmx for the UI, better-sqlite3 for storage, imapflow for reading mail, nodemailer for sending, and one OpenAI-compatible chat completions endpoint for the AI. No React, no Next, no Docker, no cloud services, no telemetry, no user accounts. This runs on localhost for exactly one person. Secrets in .env, read with a tiny loader, and ship a .env.example with: IMAP_HOST, IMAP_PORT, IMAP_USER, IMAP_PASS, SMTP_HOST, SMTP_PORT, LLM_BASE_URL, LLM_API_KEY, LLM_MODEL. Never log credentials or full message bodies. What is in scope: - A sync job that connects over IMAP, fetches messages from INBOX since a stored high water mark, and stores id, thread key, from, to, subject, date, plain text body and raw headers in SQLite. Dedupe on Message-ID. Make sync idempotent and resumable. - Strip HTML to text and truncate long bodies before sending anything to the model. - For each new thread: one LLM call returning strict JSON with category (one of urgent, needs-reply, fyi, newsletter, junk), a two sentence summary, and a suggested reply draft when category is needs-reply or urgent. Validate the JSON with zod and retry once on parse failure. - Cache results keyed by thread and message count so restarts do not re-bill you. - A web UI at / with a triage queue grouped by category, thread detail view, and an editable draft box with Approve and Send, Skip, and Mark Junk. Nothing is ever sent without an explicit click. - Sending via SMTP with correct In-Reply-To and References headers so replies thread properly. - A rules table for cheap deterministic overrides by sender or subject substring, applied before any LLM call. - npm run sync, npm run dev, and a --dry-run flag that classifies without sending. Explicitly out of scope: OAuth flows, mobile app, push notifications, multi-account support, calendar, attachments beyond recording filenames, search beyond a SQL LIKE query. Write a README with setup steps, an honest limitations section that says polling is not push and that message text leaves the machine for the model, and a cost note estimating tokens per hundred emails. Include a fixture-based test for the classifier JSON parser that does not hit the network. ## Required capabilities - An email account with IMAP/SMTP access and an app password, or patience for OAuth - An LLM API key, and acceptance that your mail text goes to that provider - A machine or small VPS that stays awake to poll - Basic comfort debugging MIME, threading and character encodings ## 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 Mailient. 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 ===== # Mailient product brief ## Problem The core trick here, pull mail, classify it, summarize threads, draft replies, is genuinely a weekend of work now that an LLM does the hard part. An agent can wire IMAP plus SQLite plus a cheap web UI and have working triage before dinner. The gaps are all the unglamorous parts: Gmail and Outlook OAuth, push sync instead of polling, threading edge cases, and the fact that you will read this thing on a phone and your build has no app. Nothing here is protected by data or network, so a personal version keeps most of the value if you accept that you are now the ops team for your own mail pipeline. Product details and pricing are thin from the outside, so treat the specifics as unverified. ## Product outcome Polls your IMAP inbox, classifies and summarizes each thread with an LLM, and parks suggested replies in a local review queue you approve before sending. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - An email account with IMAP/SMTP access and an app password, or patience for OAuth - An LLM API key, and acceptance that your mail text goes to that provider - A machine or small VPS that stays awake to poll - Basic comfort debugging MIME, threading and character encodings ## Explicit non-goals for v1 - A mobile app and real push notifications, which is where most email actually gets read - Managed OAuth with Google and Microsoft, including the review process and token refresh pain - Someone else absorbing provider API changes, rate limits and broken threading - Polish: keyboard shortcuts, fast search, snooze, undo send, offline behavior - Any sending reputation work if the product handles outbound at scale ## 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 AI email triage tool called Inbox Warden in this empty folder. Stack, no substitutions: TypeScript on Node 20, Fastify for the server, server-rendered HTML with htmx for the UI, better-sqlite3 for storage, imapflow for reading mail, nodemailer for sending, and one OpenAI-compatible chat completions endpoint for the AI. No React, no Next, no Docker, no cloud services, no telemetry, no user accounts. This runs on localhost for exactly one person. Secrets in .env, read with a tiny loader, and ship a .env.example with: IMAP_HOST, IMAP_PORT, IMAP_USER, IMAP_PASS, SMTP_HOST, SMTP_PORT, LLM_BASE_URL, LLM_API_KEY, LLM_MODEL. Never log credentials or full message bodies. What is in scope: - A sync job that connects over IMAP, fetches messages from INBOX since a stored high water mark, and stores id, thread key, from, to, subject, date, plain text body and raw headers in SQLite. Dedupe on Message-ID. Make sync idempotent and resumable. - Strip HTML to text and truncate long bodies before sending anything to the model. - For each new thread: one LLM call returning strict JSON with category (one of urgent, needs-reply, fyi, newsletter, junk), a two sentence summary, and a suggested reply draft when category is needs-reply or urgent. Validate the JSON with zod and retry once on parse failure. - Cache results keyed by thread and message count so restarts do not re-bill you. - A web UI at / with a triage queue grouped by category, thread detail view, and an editable draft box with Approve and Send, Skip, and Mark Junk. Nothing is ever sent without an explicit click. - Sending via SMTP with correct In-Reply-To and References headers so replies thread properly. - A rules table for cheap deterministic overrides by sender or subject substring, applied before any LLM call. - npm run sync, npm run dev, and a --dry-run flag that classifies without sending. Explicitly out of scope: OAuth flows, mobile app, push notifications, multi-account support, calendar, attachments beyond recording filenames, search beyond a SQL LIKE query. Write a README with setup steps, an honest limitations section that says polling is not push and that message text leaves the machine for the model, and a cost note estimating tokens per hundred emails. Include a fixture-based test for the classifier JSON parser that does not hit the network. ## 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 Mailient capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
README.md
# Mailient indie build ## Goal Build the smallest trustworthy replacement for the core Mailient workflow for one developer or a tiny team. ## Scope Polls your IMAP inbox, classifies and summarizes each thread with an LLM, and parks suggested replies in a local review queue you approve before sending. ## 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: - A mobile app and real push notifications, which is where most email actually gets read - Managed OAuth with Google and Microsoft, including the review process and token refresh pain - Someone else absorbing provider API changes, rate limits and broken threading - Polish: keyboard shortcuts, fast search, snooze, undo send, offline behavior - Any sending reputation work if the product handles outbound at scale If those capabilities are essential, use Mailient 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 AI email triage tool called Inbox Warden in this empty folder. Stack, no substitutions: TypeScript on Node 20, Fastify for the server, server-rendered HTML with htmx for the UI, better-sqlite3 for storage, imapflow for reading mail, nodemailer for sending, and one OpenAI-compatible chat completions endpoint for the AI. No React, no Next, no Docker, no cloud services, no telemetry, no user accounts. This runs on localhost for exactly one person. Secrets in .env, read with a tiny loader, and ship a .env.example with: IMAP_HOST, IMAP_PORT, IMAP_USER, IMAP_PASS, SMTP_HOST, SMTP_PORT, LLM_BASE_URL, LLM_API_KEY, LLM_MODEL. Never log credentials or full message bodies. What is in scope: - A sync job that connects over IMAP, fetches messages from INBOX since a stored high water mark, and stores id, thread key, from, to, subject, date, plain text body and raw headers in SQLite. Dedupe on Message-ID. Make sync idempotent and resumable. - Strip HTML to text and truncate long bodies before sending anything to the model. - For each new thread: one LLM call returning strict JSON with category (one of urgent, needs-reply, fyi, newsletter, junk), a two sentence summary, and a suggested reply draft when category is needs-reply or urgent. Validate the JSON with zod and retry once on parse failure. - Cache results keyed by thread and message count so restarts do not re-bill you. - A web UI at / with a triage queue grouped by category, thread detail view, and an editable draft box with Approve and Send, Skip, and Mark Junk. Nothing is ever sent without an explicit click. - Sending via SMTP with correct In-Reply-To and References headers so replies thread properly. - A rules table for cheap deterministic overrides by sender or subject substring, applied before any LLM call. - npm run sync, npm run dev, and a --dry-run flag that classifies without sending. Explicitly out of scope: OAuth flows, mobile app, push notifications, multi-account support, calendar, attachments beyond recording filenames, search beyond a SQL LIKE query. Write a README with setup steps, an honest limitations section that says polling is not push and that message text leaves the machine for the model, and a cost note estimating tokens per hundred emails. Include a fixture-based test for the classifier JSON parser that does not hit the network. ## Required capabilities - An email account with IMAP/SMTP access and an app password, or patience for OAuth - An LLM API key, and acceptance that your mail text goes to that provider - A machine or small VPS that stays awake to poll - Basic comfort debugging MIME, threading and character encodings ## 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
# Mailient product brief ## Problem The core trick here, pull mail, classify it, summarize threads, draft replies, is genuinely a weekend of work now that an LLM does the hard part. An agent can wire IMAP plus SQLite plus a cheap web UI and have working triage before dinner. The gaps are all the unglamorous parts: Gmail and Outlook OAuth, push sync instead of polling, threading edge cases, and the fact that you will read this thing on a phone and your build has no app. Nothing here is protected by data or network, so a personal version keeps most of the value if you accept that you are now the ops team for your own mail pipeline. Product details and pricing are thin from the outside, so treat the specifics as unverified. ## Product outcome Polls your IMAP inbox, classifies and summarizes each thread with an LLM, and parks suggested replies in a local review queue you approve before sending. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - An email account with IMAP/SMTP access and an app password, or patience for OAuth - An LLM API key, and acceptance that your mail text goes to that provider - A machine or small VPS that stays awake to poll - Basic comfort debugging MIME, threading and character encodings ## Explicit non-goals for v1 - A mobile app and real push notifications, which is where most email actually gets read - Managed OAuth with Google and Microsoft, including the review process and token refresh pain - Someone else absorbing provider API changes, rate limits and broken threading - Polish: keyboard shortcuts, fast search, snooze, undo send, offline behavior - Any sending reputation work if the product handles outbound at scale ## 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 AI email triage tool called Inbox Warden in this empty folder. Stack, no substitutions: TypeScript on Node 20, Fastify for the server, server-rendered HTML with htmx for the UI, better-sqlite3 for storage, imapflow for reading mail, nodemailer for sending, and one OpenAI-compatible chat completions endpoint for the AI. No React, no Next, no Docker, no cloud services, no telemetry, no user accounts. This runs on localhost for exactly one person. Secrets in .env, read with a tiny loader, and ship a .env.example with: IMAP_HOST, IMAP_PORT, IMAP_USER, IMAP_PASS, SMTP_HOST, SMTP_PORT, LLM_BASE_URL, LLM_API_KEY, LLM_MODEL. Never log credentials or full message bodies. What is in scope: - A sync job that connects over IMAP, fetches messages from INBOX since a stored high water mark, and stores id, thread key, from, to, subject, date, plain text body and raw headers in SQLite. Dedupe on Message-ID. Make sync idempotent and resumable. - Strip HTML to text and truncate long bodies before sending anything to the model. - For each new thread: one LLM call returning strict JSON with category (one of urgent, needs-reply, fyi, newsletter, junk), a two sentence summary, and a suggested reply draft when category is needs-reply or urgent. Validate the JSON with zod and retry once on parse failure. - Cache results keyed by thread and message count so restarts do not re-bill you. - A web UI at / with a triage queue grouped by category, thread detail view, and an editable draft box with Approve and Send, Skip, and Mark Junk. Nothing is ever sent without an explicit click. - Sending via SMTP with correct In-Reply-To and References headers so replies thread properly. - A rules table for cheap deterministic overrides by sender or subject substring, applied before any LLM call. - npm run sync, npm run dev, and a --dry-run flag that classifies without sending. Explicitly out of scope: OAuth flows, mobile app, push notifications, multi-account support, calendar, attachments beyond recording filenames, search beyond a SQL LIKE query. Write a README with setup steps, an honest limitations section that says polling is not push and that message text leaves the machine for the model, and a cost note estimating tokens per hundred emails. Include a fixture-based test for the classifier JSON parser that does not hit the network. ## 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 Mailient 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 email is the one app that has to work at 7am on a phone with two bars of signal, and a self-hosted poller on a home server does not clear that bar. People pay to skip OAuth verification, token refresh, IMAP quirks and the slow realization that their triage cron died four days ago and they missed an invoice. The AI part is commodity; the boring reliability around it is what the subscription actually buys.
xA mobile app and real push notifications, which is where most email actually gets read
xManaged OAuth with Google and Microsoft, including the review process and token refresh pain
xSomeone else absorbing provider API changes, rate limits and broken threading
xPolish: keyboard shortcuts, fast search, snooze, undo send, offline behavior
xAny sending reputation work if the product handles outbound at scale
Nothing worth pointing at. That's why the prompt exists.
share on X ↗"I just replaced Mailient ($29/mo) with one prompt"
Vibecode Mailient
Kinda. The core of Mailient is buildable in a weekend with the prompt on this page, but there are real gaps: A mobile app and real push notifications, which is where most email actually gets read, Managed OAuth with Google and Microsoft, including the review process and token refresh pain. Read the honest list above before committing.
How much does Mailient cost?
Mailient costs about $29/month (Monthly, checked 2026-08-18), which is $348 per year.
What do I lose by replacing Mailient?
Honestly: A mobile app and real push notifications, which is where most email actually gets read; Managed OAuth with Google and Microsoft, including the review process and token refresh pain; Someone else absorbing provider API changes, rate limits and broken threading; Polish: keyboard shortcuts, fast search, snooze, undo send, offline behavior; Any sending reputation work if the product handles outbound at scale. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to Mailient?
No mature open-source alternative worth pointing at, which is exactly why the one-shot prompt on this page exists.