# Build brief — a focused alternative to Soccial AI > **Verdict:** Partly, if you narrow it · **Buildability:** 49/100 · **Category:** Social Media > **Source:** https://www.canitbevibecoded.com/soccial-ai > Independent editorial assessment from Can It Be Vibe Coded? Not affiliated with, endorsed by, or derived from Soccial AI. Verify current pricing and capabilities before acting. ## Context **Soccial AI** — AI Instagram DM and comment automation with a CRM that turns followers into customers you own. It currently costs $139/mo. The code is the easy part; Meta is the hard part. The core loop, an LLM that auto-replies to your Instagram DMs, is a small webhook server any coding agent writes with a focused implementation. But it only runs against a Meta developer app: you need an Instagram professional account, a public HTTPS endpoint that is up 24/7 (DMs arrive while your laptop is closed), webhook signature verification, and token refresh. And your app stays in development mode, which is fine for your own account but serving anyone else means Meta App Review plus business verification. What the subscription actually sells is connector upkeep across Instagram, Facebook, Shopify and GoHighLevel, hosted always-on webhooks, and a CRM wrapped around the conversations. This brief describes a focused, single-operator replacement for the part of Soccial AI that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest. ## What you are building A small webhook server that receives your Instagram DMs and auto-replies through an LLM using your own system prompt. - Draft, queue, and track content for the few networks you actually use. - A responsive interface with real empty, loading, success, and error states. ## Requirements ### Functional - Meta developer app (free) + Instagram professional account. - Always-on public HTTPS endpoint (Cloudflare Tunnel on a Pi, or a $5 VPS). ### Data and integrations - Anthropic or OpenAI API key. Each of these needs a real account, credential, or quota. Set them up before writing feature code. ### Non-functional - Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support. - Security: server-side secrets, validated input, and no credentials in the client bundle. - Reliability: retries with backoff on external calls, and a clear failure state when a provider is down. - Portability: the operator can export their data and leave without losing it. ## Implementation brief Build a self-hosted Instagram DM auto-responder for my own Instagram professional account, in this empty folder. Stack: Node 22 + Hono + better-sqlite3 + the Anthropic SDK (claude-sonnet-5). One small server, no frontend. Secrets in .env: IG_ACCESS_TOKEN, IG_ACCOUNT_ID, META_APP_SECRET, META_VERIFY_TOKEN, ANTHROPIC_API_KEY. Endpoints: - GET /webhook: Meta's hub.challenge verification handshake. - POST /webhook: verify X-Hub-Signature-256 with META_APP_SECRET, ACK 200 immediately, process async. On each incoming DM: skip echoes of my own outbound messages (is_echo); dedupe by message id in SQLite; load the last 10 messages of that conversation from SQLite as context; generate a reply with Claude using the editable system prompt in persona.md; send it via POST https://graph.instagram.com/v23.0/me/messages with recipient.id set to the sender's IGSID; log both sides to SQLite. Guardrails: never reply twice to the same message id; hard cap of one auto-reply per user per two minutes; if the model's reply contains the token HUMAN, send nothing and log it for me instead. Write a README that walks through the Meta side, which is the actual hard part: create a Meta app, add the Instagram API with Instagram Login, generate a long-lived access token for my account, subscribe the app to the messages webhook field, and expose this server with a Cloudflare Tunnel. Note plainly that in development mode this works only for my own account, and that is the point. Deliberately out of scope: comment automation, multiple accounts, any CRM, Shopify or calendar integrations, and Meta App Review. ## Delivery standard - Inspect the repository first, then write a short implementation plan before writing code. - Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data. - Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations. - Include responsive layouts plus genuine empty, loading, success, validation, and failure states. - Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data. - Add structured logs around every external call and return actionable errors without leaking sensitive details. - Write unit tests for the core logic and one automated test of the main user journey. - Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations. ## Acceptance criteria - [ ] A clean install starts the app using only the README and .env.example. - [ ] The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable. - [ ] Invalid input, missing configuration, provider failure, and an empty database each have a usable state. - [ ] The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control. - [ ] Tests, type checking, linting, and a production build all pass with no ignored failures. - [ ] No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified. ## Non-goals Do not build these, and do not claim to have replaced them: - Anyone-but-you: without Meta App Review your app only serves accounts you add as testers. - Shopify and GoHighLevel context behind replies, and the CRM around the conversations. - Comment-to-DM automations, scheduled follow-ups, and human-approval gates on AI writes. - Someone else babysitting webhook uptime, token refresh, and Meta API deprecations. ## What you still own after launch - Secure credentials, rotate secrets, and handle provider rate limits. - Run migrations, backups, restores, and dependency updates. - Test the critical journey after every model, API, or hosting change. - Monitor failures and fix the edge cases a first prompt will miss. - Maintain every third-party integration as APIs and OAuth rules change. ## Risk **Operational risk.** The code is achievable; dependable data, integrations, and ongoing operations are the real cost. Editorial confidence in this assessment: high. No reviewed project implementation is linked yet. ## Prior art Working open-source software you can read, fork, or borrow from before starting: - [Chatwoot](https://github.com/chatwoot/chatwoot) — open-source support inbox with an official Instagram DM channel, bring-your-own Meta app --- Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/soccial-ai