TypeScript SaaS Maintenance and Reliability

I fix and stabilize existing TypeScript web applications.

Next.js, React, Node.js, Supabase, and PostgreSQL—authentication, permissions and RLS, APIs, data bugs, deployments, regressions, and release hardening.

The application already exists. I inspect the code and production behavior, reproduce the failure, make the smallest safe change, and document the evidence. I do not sell a rewrite by default.

Start with one scoped issue Review engineering proof

Problems I work on

Maintenance scoped around observable failures.

Auth, access, and data boundaries

Sessions that disappear, redirect loops, incorrect authorization, users seeing the wrong data, tenant isolation gaps, and Supabase RLS behavior.

Evidence: Next: PostgreSQL RLS, private and public data boundaries, and transactional commands.

API, database, and application bugs

Broken endpoints, incorrect query results, duplicate requests, stale data, forms, filters, React state races, and Node.js backend failures.

Evidence: Reticle and Apache Maka: behavioral fixes in unfamiliar TypeScript repositories.

Deployment and release stability

Vercel or build failures, environment and CORS problems, CI failures, flaky tests, and missing Playwright or Vitest regression coverage.

Evidence: BlueHex and Apache Fineract: browser coverage and test modernization accepted upstream.

AI-built application stabilization

Applications created or accelerated with Lovable, Bolt, Replit, v0, Base44, Claude, Codex, or similar tools that now fail under real workflows.

Evidence: Independent verification of the repository, runtime behavior, permissions, data boundaries, and release checks.

A bounded engagement

From symptom to a reviewed, testable change.

01Send the symptoms, issue, logs, screenshots, or repository context.
02I reproduce the behavior, identify the root cause, and define a bounded scope.
03After we agree on scope, I implement the focused change on a branch.
04I validate the behavior and add regression coverage when it reduces repeat risk.
05You receive a clean pull request and a concise explanation of the cause, fix, and evidence.

AI-built application rescue

Rapid development still needs independent verification.

If an AI-built prototype works most of the time but fails under real users, I inspect the actual repository and runtime behavior. I check auth and data boundaries, reproduce the real failure mode, and stabilize the application without replacing working parts.

The value is engineering ownership: understanding the system, reviewing the diff, validating assumptions, and leaving regression evidence another developer can maintain.

Existing codebase · Focused scope · Clear evidence

Start with the issue that is blocking you.

Describe the issue Review my code