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[verdict][curated prompt][source: salestouch.io]

Can I vibecode SalesTouch?

// the value is the network, the data or the infrastructure

The local CRM and AI drafting layer are straightforward, but SalesTouch's core value is reliable access to LinkedIn's private network: authenticated sessions, live data extraction, residential IP routing, human-paced queues, limits, cooldowns, reconnection, and ongoing adaptation to platform changes. A one-shot clone either stops at manual copy and paste or becomes brittle automation that can put the LinkedIn account at risk.

confidence: high

what it is: LinkedIn MCP for AI agents to research prospects and run outreach workflows

Buildability index · an editorial game

  • Price 49 $/month weight: plus 3
  • Time one sitting for a manual cockpit; not realistically replaceable for live LinkedIn execution weight: minus 3
  • Category automation no weight
  • Moat integrations · infrastructure scale weight: minus 3
  • Confidence high weight: plus 1
  • What you lose 5 items weight: minus 2
  • Site salestouch.io (si apre in una nuova scheda) no weight
Indice: minus 4. think twice

The moat outweighs the price: rebuilding this is a project, not an evening.

Gioco editoriale: il verdetto dice se un agente può, l’indice se conviene.

What you build

Import or paste prospects, score them from user-supplied context, draft personalized outreach with an LLM, and track manual follow-ups in a local pipeline.

what you need

  • OpenAI API key
  • LinkedIn account
  • manual profile and conversation input

Submitted by the maker and judged against the same rubric as every other app.

The prompt

The verdict is NOT REALLY, and the prompt stays anyway: it does not replace the app, it rebuilds the part that really is code. The rest is the moat.

One-shot prompt EN 
Build me a local LinkedIn outreach cockpit inspired by SalesTouch. Requirements:

- Node 22 + Express + better-sqlite3; one localhost web app with no accounts.
- Import prospects from CSV with name, company, role, LinkedIn URL, source,
  notes, and last-contact date; validate and deduplicate by LinkedIn URL.
- Let me paste profile, company, post, and conversation text into each record.
  Never crawl LinkedIn or read browser cookies.
- Store my offer and ICP rules in config.json. Use the OpenAI API to return a
  fit score, evidence, a personalized angle, a connection note under 300
  characters, a first DM, and one follow-up. Put OPENAI_API_KEY in .env.
- A kanban pipeline: new, researched, ready, contacted, replied, won, lost.
- A Today queue showing due follow-ups and a configurable manual daily limit.
- Each action opens the LinkedIn profile in a new tab and has copy buttons for
  the approved text. It must never click, send, invite, comment, or publish.
- Let me paste a new reply, show the complete conversation history, and draft
  a suggested response for approval.
- Log every status change and copied draft in SQLite; export prospects and
  activity as CSV. Never pretend a copied message was sent.
- Keep all data local. No cloud database, telemetry, background workers, or
  multi-user features.
- Explicitly out of scope: LinkedIn login or cookies, scraping, Sales Navigator
  automation, residential proxies, auto-sending, engagement, publishing,
  multi-account orchestration, and claims that this is account-safe automation.
- README: setup, CSV format, backup path, and an honest explanation that the
  tool replaces planning and drafting only, not SalesTouch's LinkedIn execution.

Curated prompt: written and reviewed by hand for this app. In English on purpose — it is the language coding agents work best in.

What you lose

  • live LinkedIn and Sales Navigator searches and audience extraction
  • authenticated messages, invitations, engagement, and publishing
  • residential IP routing and resilient LinkedIn sessions
  • human-paced queues, limits, cooldowns, and account safety controls
  • multi-account orchestration, activity logs, and analytics

Why people still pay

They pay for the execution layer, not the dashboard. SalesTouch keeps authenticated LinkedIn sessions alive, turns private network data into agent tools, schedules actions within safety rules, and absorbs the maintenance when LinkedIn changes behavior. Rebuilding the screens is easy; operating the connection reliably without endangering an account is the product.

moat: Integrations Infrastructure scale what a moat is

LinkedIn access infrastructure + account safety

Do you agree?

The vote balance

Ancora nessun voto: il tuo è il primo.

Nessun voto ancora — il primo pesa.

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