Post-Launch: What Happens After We Ship Your Product

The product is live. Users are signing up. You are celebrating. And then quietly, in the back of your mind, a thought starts forming: what if something breaks?

This is the part of software development that nobody talks about enough. The launch is not the finish line. It is the starting line. What happens in the weeks and months after launch determines whether your product thrives or slowly degrades.

We have shipped over a dozen products, and every single one needed attention after launch. Not because the code was bad — because real users do things you cannot fully predict. They use browsers you did not test. They enter data in formats you did not expect. They find workflows that expose edge cases your test suite missed. This is normal. What matters is how you handle it.

The 30-Day Warranty Period

Every project we deliver comes with a 30-day warranty period at no additional cost. During these 30 days, we fix any bugs that are attributable to our work. No invoices, no scope discussions, no friction.

What counts as a warranty bug:

• Something that worked during testing but breaks in production
• An edge case in the code we wrote that causes errors
• A deployment or infrastructure issue with the setup we configured
• A regression introduced by our code

What does not count:

• New feature requests (even small ones)
• Bugs in third-party services or APIs we integrated with
• Issues caused by changes made by your team after handoff
• Performance issues caused by usage patterns dramatically beyond what was scoped (e.g., a system scoped for 1,000 users handling 100,000)

The line between “bug” and “feature request” can get blurry. Our default is to err on the side of generosity. If there is a legitimate argument that something should work a certain way based on the original spec, we will fix it under warranty.

During the warranty period, our response times are:

Severity Levels:
- Critical (product is down / data loss risk): Response within 2 hours
- High (major feature broken, no workaround): Response within 8 hours
- Medium (feature broken, workaround exists): Response within 24 hours
- Low (cosmetic / minor UX issue): Response within 48 hours

Response time means we have acknowledged the issue, assessed it, and communicated a plan — not necessarily that the fix is deployed. Critical issues get hotfixed immediately. Lower-severity issues get batched into a weekly patch release.

Monitoring Setup Before Launch

We do not launch and hope for the best. Before any product goes live, we set up monitoring so we know when something breaks — ideally before you or your users notice.

Our standard monitoring stack includes:

Error tracking. We integrate an error tracking service (typically Sentry) into every production deployment. Unhandled exceptions, failed API calls, and client-side errors get captured with full context — stack trace, user session data, browser info, request payload. When we launched MindHyv, error tracking caught a Safari-specific rendering issue within the first hour that affected about 8% of users. We had a fix deployed before any user reported it.

Uptime monitoring. We set up synthetic checks that ping your critical endpoints every few minutes. If your API goes down or response times spike above a threshold, we get alerted immediately.

Database monitoring. For Supabase-backed projects (which is most of what we build), we monitor query performance, connection pool usage, and storage growth. Slow queries get caught early before they become user-facing performance problems.

Log aggregation. Structured logging throughout the application, with logs shipped to a centralized service. When something goes wrong, we can trace a request through the entire system in minutes instead of hours.

Here is an example of how we structure application logging in our SvelteKit projects:

// src/lib/server/logger.ts
import { env } from '$env/dynamic/private';

type LogLevel = 'info' | 'warn' | 'error';

interface LogEntry {
  level: LogLevel;
  message: string;
  context?: Record<string, unknown>;
  timestamp: string;
  requestId?: string;
}

export function createLogger(requestId?: string) {
  function log(level: LogLevel, message: string, context?: Record<string, unknown>) {
    const entry: LogEntry = {
      level,
      message,
      context,
      timestamp: new Date().toISOString(),
      requestId,
    };

    // Structured JSON logging for production
    if (env.NODE_ENV === 'production') {
      console[level](JSON.stringify(entry));
    } else {
      console[level](`[${level.toUpperCase()}] ${message}`, context ?? '');
    }
  }

  return {
    info: (msg: string, ctx?: Record<string, unknown>) => log('info', msg, ctx),
    warn: (msg: string, ctx?: Record<string, unknown>) => log('warn', msg, ctx),
    error: (msg: string, ctx?: Record<string, unknown>) => log('error', msg, ctx),
  };
}

// Usage in a SvelteKit server route
import { createLogger } from '$lib/server/logger';

export async function POST({ request, locals }) {
  const logger = createLogger(locals.requestId);

  try {
    const body = await request.json();
    logger.info('Processing payment', { userId: locals.userId, amount: body.amount });

    const result = await processPayment(body);
    logger.info('Payment successful', { paymentId: result.id });

    return json(result);
  } catch (err) {
    logger.error('Payment failed', {
      userId: locals.userId,
      error: err instanceof Error ? err.message : 'Unknown error',
    });
    throw error(500, 'Payment processing failed');
  }
}

This structured approach means that when a user reports “my payment did not go through,” we can search logs by their user ID and see exactly what happened, with full context, in seconds.

The Bug Triage Process

Not all bugs are created equal, and not all bugs need to be fixed immediately. We follow a straightforward triage process that prioritizes based on user impact.

When a bug is reported — whether by monitoring, by you, or by your users — it goes through this flow:

1. Reproduce and confirm. Before we do anything, we confirm the bug exists and is reproducible. A surprising number of reported “bugs” turn out to be user confusion, one-time network blips, or already-resolved issues. We do not waste time fixing things that are not broken.

2. Assess severity. Using the severity levels above (critical, high, medium, low), we classify the bug based on how many users are affected and how badly their experience is degraded.

3. Identify root cause. Before writing a fix, we understand why the bug happened. A quick fix that addresses the symptom but not the cause will just break again later. When we found a data consistency issue in Trackelio’s voting system, the temptation was to write a migration script to fix the affected data. But the root cause was a race condition in the vote counting logic — fixing only the data would have left the race condition in place.

4. Fix, test, deploy. The fix is written, tested against the reproduction case, reviewed by a second engineer, and deployed. For critical bugs, this entire cycle can happen in under an hour. For lower-severity issues, fixes are batched and deployed together.

5. Post-mortem for critical issues. If something critical happened — downtime, data loss, security issue — we write a brief post-mortem. What happened, why, what we did to fix it, and what we are doing to prevent it from happening again. You get a copy. Transparency is non-negotiable.

Ongoing Maintenance Plans

After the 30-day warranty period, most of our clients transition to a maintenance plan. This is not optional in the sense that your product needs ongoing care — it is optional in the sense that you can choose to handle it yourself or hire someone else. But we strongly recommend continuing with us because we already know the codebase intimately.

Our maintenance plans come in three tiers:

Essential (10 hours/month): Bug fixes, security patches, dependency updates, and monitoring. This is the minimum to keep a production product healthy. Good for products with stable feature sets and modest traffic.

Growth (20-40 hours/month): Everything in Essential plus minor feature development, performance optimization, and user feedback-driven improvements. Good for products that are actively growing and iterating.

Scale (40+ hours/month): Full ongoing development. At this point, we are effectively your development team. Good for products in active growth mode that need continuous feature development. This is how our engagement with MindHyv works — the product is always evolving based on user needs.

We describe our pricing approach in more detail in Why We Do Not Do Fixed-Price Contracts.

What Ongoing Maintenance Actually Looks Like

Here is a real example of what a typical month looks like on our Growth plan for a SaaS product:

Month Summary — February 2026
================================
Total hours: 28

Bug fixes (6 hours):
- Fixed timezone rendering in dashboard charts (2h)
- Resolved email delivery failures for Yahoo addresses (1.5h)
- Fixed pagination bug on mobile search results (1h)
- Patched CSV export dropping special characters (1.5h)

Security & dependencies (4 hours):
- Updated Svelte to 5.x patch release (1h)
- Rotated API keys per quarterly schedule (0.5h)
- Applied Supabase security advisory patch (1h)
- Reviewed and updated npm dependencies (1.5h)

Feature work (14 hours):
- Added bulk export for user reports (6h)
- Implemented webhook retry logic with exponential backoff (5h)
- Added filter presets to analytics dashboard (3h)

Performance (4 hours):
- Optimized slow query on user search (2h)
- Added image lazy loading to feed pages (1h)
- Configured CDN caching for static assets (1h)

Notice how bug fixes are a relatively small portion. The bulk of maintenance time goes toward making the product better — new features, performance improvements, and keeping the stack up to date. This is healthy maintenance. If bug fixes are consuming more than 30% of your maintenance budget consistently, something is wrong with the underlying code quality.

Dependency Updates Are Not Optional

Keeping dependencies up to date is one of the most overlooked aspects of maintenance. We run dependency audits monthly — npm audit for vulnerabilities, npm outdated for stale packages. Letting dependencies rot leads to a compounding problem. Skip updates for six months and you face dozens of breaking changes simultaneously. Update monthly and each change is small and manageable.

We inherited a project once where dependencies had not been updated in over a year. Three npm packages had known critical vulnerabilities. Upgrading everything took nearly two weeks — time and money that regular maintenance would have prevented.

The Handoff Option

Sometimes clients have their own development team and just need us to build the initial product. That is fine. We do thorough handoffs.

A handoff includes:

• Complete codebase documentation (README, architecture decisions, environment setup)
• Database schema documentation with entity-relationship diagrams
• Deployment runbook (how to deploy, roll back, and manage infrastructure)
• A recorded walkthrough of the codebase with one of our engineers
• Transfer of all credentials, API keys, and service accounts
• Two weeks of overlap where your team can ask questions

We want the handoff to succeed even if we never hear from you again. A product that dies because the original developers left and nobody could figure out the code is a failure for everyone.

Do Not Be Afraid of Post-Launch

The worst thing you can do is treat launch as the end. The products that succeed are the ones that keep improving based on real user feedback and real production data.

We build our projects with post-launch in mind from day one. Clean code so it is easy to change. Good test coverage so changes are safe. Monitoring so issues surface quickly. Documentation so anyone can understand the system. These are not extras — they are requirements for a product that will survive contact with the real world.

If you are planning a product launch and want a team that sticks around after the confetti settles, reach out at [email protected].