[verdict][generated prompt][source: fullstory.com]
Can I vibecode FullStory?
// the value is the network, the data or the infrastructure
A consolation build is possible, but the paid product's decisive value sits outside a solo rebuild. For FullStory, collect explicit product events and targeted debug snapshots with strong privacy controls. The hard boundary is high-fidelity replay, privacy redaction, indexing, search, storage, and compliance, plus data pipeline reliability and analytical depth.
confidence: high
what it is: Collect explicit product events and targeted debug snapshots with strong privacy controls
Buildability index · an editorial game
- Price on request weight: zero
- Time closest consolation build: one sitting weight: minus 1
- Category analytics no weight
- Moat infrastructure scale · execution quality weight: minus 3
- Confidence high weight: plus 1
- What you lose 5 items weight: minus 2
- Site fullstory.com (si apre in una nuova scheda) no weight
It is not close. The prompt below rebuilds a piece, not the product.
Gioco editoriale: il verdetto dice se un agente può, l’indice se conviene.
What you build
Collect explicit first-party product events and targeted debug snapshots with strong privacy controls, answer a small set of product questions, and retain raw data under the owner's control.
what you need
- Docker
- ClickHouse
- PostgreSQL
- public HTTPS collector endpoint
- site script access
Editorial comparison targets the Business plan and a single-product first-party analytics DIY substitute. Recheck price before merge.
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.
Build a closest honest personal substitute for FullStory in an empty repository.
Use Next.js 15, TypeScript, ClickHouse, PostgreSQL, and Docker Compose; do not offer alternative stacks.
The core loop is: collect explicit first-party product events and targeted debug snapshots with strong privacy controls, answer a small set of product questions, and retain raw data under the owner's control.
Make the first run work locally with one documented command.
Store all user data locally by default and make export straightforward.
Put secrets in .env, ship .env.example, and never commit credentials.
Ship a lightweight browser SDK for page views and explicit custom events.
Create projects, API keys, environments, event names, and a documented event schema.
Ingest idempotently, filter obvious bots, truncate IP data, and avoid fingerprinting.
Build dashboards for visitors, sessions, funnels, retention, sources, pages, and events.
Expose filters by date, environment, device, country, referrer, and selected properties.
Add retention controls, raw-event export, deletion, health checks, and backup instructions.
Include clear empty, loading, success, and recoverable error states.
Add input validation, safe filenames, and graceful handling of unavailable APIs.
Write focused tests for the core transformation and one end-to-end happy path.
Create a README with setup, architecture, permissions, data location, and backup steps.
Do not add accounts, billing, telemetry, analytics, or a hosted control plane.
Do not claim to reproduce proprietary data, network liquidity, regulated access, or frontier infrastructure.
Deliberately leave out cross-site identity graphs.
Deliberately leave out session replay and automatic DOM capture.
Deliberately leave out warehouse-scale reverse ETL and enterprise governance.
Finish by running the tests and listing the exact commands used.Prompt generated from the data on this page, not reviewed by hand yet. In English on purpose — it is the language coding agents work best in.
What you lose
- high-fidelity replay, privacy redaction, indexing, search, storage, and compliance
- identity stitching
- session replay
- warehouse connectors
- high-volume global ingestion and support
Why people still pay
People still pay for FullStory because teams pay because analytics must keep collecting and remain trustworthy while the product changes underneath it. The recurring cost buys event schemas, bot filtering, identity, late data, retention, query cost, privacy, backups, and always-on ingestion, not just the visible interface.
moat: Infrastructure scale Execution quality what a moat is
data pipeline reliability and analytical depth
Free alternatives
Not in the mood to build it? These already exist, they are free or open source, and we checked them one by one.
Who has already built it
Starting from here is still vibecoding: the prompt is for when you want it exactly your way.
- Umami (opens in a new tab) — Popular open-source privacy-focused web analytics platform.
Do you agree?
The vote balance
Ancora nessun voto: il tuo è il primo.
Nessun voto ancora — il primo pesa.
