Sid Probstein

Every week someone tells me they vibe-coded their app over the weekend and don't need developers anymore. Before it touches a paying customer, make sure it includes: > a schema someone designed, instead of one the AI improvised table by table > login that still works when someone puts a plus sign in their email > password reset links that expire and work once > MFA, plus a recovery path for the user who lost their phone > sessions that time out, and a way to kill every session for one user > SSO for the enterprise customer who won't sign without it > SAML, because that customer's IT team doesn't do magic links > SCIM, so a fired employee loses access the moment IT offboards them > roles and permissions deeper than "admin" and "everyone else" > checks that stop user A from reading user B's data by changing one number in the URL > tenant isolation, so one customer's bug never shows another customer's records > an admin "log in as this user" button for support, with an audit trail on every use > rate limits on login, so nobody can guess passwords at scale > lockouts that stop attackers without locking out your CFO the night before the board meeting > database migrations that run forward and roll back > migrations that don't lock the main table at 2pm on a Tuesday > indexes, because the query that was instant on 50 test rows times out on 5 million real ones > connection pooling, so a traffic spike doesn't exhaust the database > backups every night > a restore from those backups, tested, because a backup you've never restored is a hope > point-in-time recovery for the day someone runs a delete without a where clause > soft deletes, so "I deleted it by accident" is a support ticket and not an incident > validation on the server, not just in the form > timezones stored right, so the 9am reminder doesn't fire at 4am > the customer with an apostrophe in their last name > emoji, accents and right-to-left text in every field > money stored as integers, because 0.1 + 0.2 doesn't equal 0.3 in floating point > currency, rounding and tax rules for every country you sell into > a data model that survives your second customer asking for "one small change" > idempotency keys, so a retried payment doesn't charge the card twice > deduplication for the user who clicks submit four times > pagination that still works on page 400 > exports, because sooner or later every customer wants their data in a spreadsheet > imports that survive the CSV someone saved in 2009 > retention rules, and code that deletes what your contract says you'll delete > secrets out of the code, out of the repo and out of the AI chat history > rotating every key the AI pasted into a config file last month > confirming every package the AI installed exists and is the one you meant > dependency scanning, because the AI pulled in libraries nobody reviewed > input sanitization everywhere a user can type > protection against SQL injection, XSS, CSRF and the rest of the OWASP list > file uploads that get scanned, size-limited and stored where they can't execute > CORS rules that aren't "allow everything" > security headers on every response > encryption at rest and in transit > least-privilege access for everyone, including the AI agent holding production credentials > logs that record who did what, without recording passwords, tokens or card numbers > a penetration test before your enterprise customer's security team runs their own > answers to the security questionnaire every enterprise buyer sends, with evidence behind each one > a disclosure process for the day a stranger emails you a vulnerability > a plan for the day a laptop with production access gets stolen > SOC 2, which means policies, evidence and an auditor, not a checkbox > HIPAA, the moment a single patient record touches your system > a BAA with every vendor that touches that data, including your AI model provider > audit trails that show who viewed a record, not just who changed it > PCI scope, and card numbers kept out of your database > GDPR deletion requests that reach every table, backup and log > data residency for the customer whose contract says EU only > quarterly access reviews someone signs off on > dev, staging and production environments that match each other > infrastructure written as code, so the setup lives somewhere other than one person's memory > a deploy pipeline that runs the tests before anything reaches customers > one-click rollbacks, because Friday deploys happen > zero-downtime deploys, because your customers don't have maintenance windows > feature flags, so you can ship the code without shipping the feature > autoscaling for the Monday morning spike > a CDN, so the app loads fast in Singapore too > DNS, SSL certificates, and renewals that don't expire on a Sunday > background job queues, so slow work doesn't freeze the page > retries with backoff, so one flaky API call doesn't become a lost order > a dead-letter queue for the jobs that fail every retry > cron jobs that don't run twice the day you add a second server > caching, and clearing that cache when the data changes > SPF, DKIM and DMARC, so your password resets don't land in spam > bounce and complaint handling on every transactional email > storage rules, so you stop paying to keep 2021's temp files > cost alerts, so a runaway agent loop shows up the same day and not on the invoice (we learned this one for $1,382.59) > a disaster recovery plan, written down and tested once a year > a second region, if your contract promises uptime one region can't deliver > structured logs you can search at 3am > error tracking that groups the same bug instead of sending you 4,000 emails > uptime checks from outside your own network > alerts that page a human, tuned until they stop paging for nothing > dashboards for latency, error rate and throughput > tracing for one slow request across every service it touches > an on-call rotation, and a person who picks up > runbooks, so the engineer on call knows what "queue depth critical" means > postmortems that change something > a status page customers check before they email you > unit tests written by someone who knows what the logic should do > integration tests for every third-party API you depend on > end-to-end tests for signup, checkout and the other flows that make you money > load testing before the launch email goes out > test data that looks like production without being production data > regression tests, so fixing bug 41 doesn't bring back bug 12 > testing on the five-year-old laptop your biggest customer's ops team still uses > accessibility compliance, because the enterprise contract requires it > subscriptions, upgrades, downgrades and proration > failed-payment retries and dunning emails > invoices with the customer's PO number on them, because procurement won't pay without it > sales tax and VAT > refunds, credits and partial refunds > usage metering that matches what you bill, to the cent > annual contracts with custom terms your billing logic never planned for > revenue reports your finance team can reconcile > webhooks that verify signatures > webhooks that retry, with a log of every failed delivery > a versioned API, so you can change it without breaking your customers' integrations > API keys customers can create and revoke > API rate limits that protect you without blocking real integrations > a plan for the day a third-party API changes its response format without telling you > OAuth token refresh, because tokens expire at the worst possible moment > a sandbox where customers can test their integration > protection against prompt injection in every field that reaches the model > customer and patient data kept out of prompts that leave your network > a model spend cap per customer, so one heavy user can't run up your bill > evals, so you find out when a model update makes your answers worse > a fallback for the afternoon your model provider goes down > a migration plan for the day your model gets deprecated > prompt and output logs for debugging, minus whatever you're not allowed to keep > a human approval step for anything the AI does that can't be undone > pages that load on hotel wifi > empty states, loading states and error states on every screen > error messages a customer can act on, instead of "something went wrong" > forms that keep what people typed when one field fails validation > emails that render in every mail client your customers use > notifications people can turn off > undo > keyboard navigation and screen reader support > translations, with dates and numbers formatted for each locale > a back button that does what people expect > code a human can read > code review on every change > a branching strategy, so two people can work without overwriting each other > monthly dependency upgrades, so you're never two major versions behind > framework upgrades before the old version stops getting security patches > deleting the dead code the AI left behind from its first three attempts > splitting up the 2,000-line file the AI kept appending to > architecture decisions written down, with the reasons > a README that gets a new engineer running locally in under an hour > documentation for whoever inherits this > an admin panel for your ops team > support tooling, so customer success can answer questions without pinging engineering > a changelog customers can read > terms and a privacy policy that match what the code does > every account, domain and repo in the company's name, not the name of whoever built the prototype > a bus factor higher than one Oh, and besides keeping all of this working every day, forever… your vibe-coded app will still need people who know what they're doing: > reading every line the AI wrote before it ships (a senior engineer) > designing the data model before your second customer breaks it (a backend engineer) > explaining why the AI's fix for one bug created two new ones (a senior engineer, again) > deploys, rollbacks, servers and the cloud bill (a DevOps engineer) > answering the page at 3am when payments stop (whoever's on call) > patching the framework the week a vulnerability goes public (security) > walking an auditor through how patient data moves (security and compliance) > testing what the AI says it tested (QA) > running a migration on a live database without losing a row (a backend engineer) > saying no to the feature that breaks three others (a tech lead) > turning "works on my laptop" into "works for every customer at once" (an architect) > debugging the code when the AI that wrote it can't (a senior engineer) > remembering why it's built this way, a year from now (someone who was there) …wishing them the best 🫡