Turn an existing app into software customers can depend on.
I harden inherited and AI-assisted applications across authentication, data boundaries, backend reliability, deployment, monitoring, recovery, and production operations.
For software with users, revenue, funding, or a committed launchSoftware that already matters to someone
This engagement exists for products with real users, revenue, meaningful internal operations, funding, or a committed customer launch. It is not a cheap rescue service for idea-stage prototypes — production hardening is senior engineering work on a system whose failures now have consequences.
- Authentication, session handling, and account/tenant separation
- Data boundaries, permissions, and multi-tenant isolation
- Backend reliability: error handling, retries, background jobs, and queues
- Database integrity, migrations, backups, and restore tests
- Deployment, environments, secrets, and rollback
- Logging, monitoring, and alerting that distinguishes real failures from noise
- Tests around the workflows the business actually depends on
Is this the right engagement?
An honest self-check. If the project is below this bar, the fit call will say so quickly.
Good fit
- Software with real users, revenue, funding, meaningful internal operations, or a committed customer launch.
- An inherited codebase whose original team, agency, or contractor is gone.
- An AI-assisted or rapidly built app that now needs dependable authentication, data boundaries, and operations.
- A named reliability, security, or launch-readiness problem with a decision-maker who can grant access.
Not a fit
- Idea-only projects with no users, budget, or committed launch.
- A prototype rescue priced on the assumption that repair costs as little as generation did.
- Equity-only or unpaid engagements.
- A request to guess at production behavior from screenshots, with no repository or system access.
If the shape of the problem is different
Nothing built yet, but a defined scope?
A funded, bounded greenfield build is a different engagement with a written scope and fixed price.
See defined product builds →Payments or financial data failing?
Stripe, QuickBooks/ERP, webhook, sync, and reconciliation failures are the primary offer, with their own diagnostic path.
See payment & financial integration repair →Common questions
Do you work with AI-generated codebases?
Yes. The relevant question is not how the first draft was produced but whether the behavior, data boundaries, failure modes, deployment, and recovery are dependable. I assess what can safely be kept and what must change for real users.
We inherited a codebase and the original developers are gone. Where do you start?
With a map: what runs where, what the data model actually is, which workflows matter commercially, and what the riskiest gaps are. Then hardening proceeds in bounded, prioritized steps rather than an open-ended rewrite.
Is this a rewrite?
Usually not. The default is to harden the existing system — production readiness is mostly about authentication, data correctness, reliability, deployment, and observability, not about replacing working code. A rewrite is only proposed when the evidence supports it.
What does “production ready” mean here?
Agreed in writing per engagement: which workflows must work, how failures surface, what is backed up and restorable, how deploys and rollbacks happen, and what the team can observe after handover. Not a generic checklist.
What if the real problem is a payment or accounting integration?
Then start with the primary offer instead — payment and financial integration repair is its own engagement with its own diagnostic path.
Tell me what exists, who depends on it, and what must become dependable
Bring the product, its current state, and the deadline. I will tell you whether production hardening fits and what the first bounded step would be.