Smith›Guides
Playbooks, Not a Blog
Rescue playbooks for what AI tools get wrong — auth, payments, security, deployment. Plus practical guides on writing job posts and proposals that actually work.
12 guides
If you're getting generic proposals, low-quality applicants, or nothing at all, the problem is almost always the job post — here's exactly what to fix.
Moving a conversation to WhatsApp or email 'just to be faster' feels harmless — until something goes wrong and there's no record of what was actually agreed.
How Smith's payment flow is actually structured — funding, submission, review, and payout — and how to use milestones so a disagreement doesn't turn into a loss for either side.
Clients now see dozens of AI-templated proposals per job and filter them in seconds. Here's exactly what makes yours the one that gets read.
With dozens of AI-templated proposals landing in every job, most clients pattern-match and skim. Here's how to actually tell the strong ones apart from the noise.
Every bad-client horror story has a warning sign that was visible before the proposal was even sent. Here's what to check before you apply, not after.
Vague pushback teaches a client that scope expansion is free. Here's the exact script freelancers actually use to handle it — without souring the relationship.
A normal freelance brief has predictable scope. An AI-generated codebase doesn't — and 'just fix it' is exactly the job post that turns a small fix into a full rebuild nobody agreed to.
The 9 security holes that appear in almost every AI-generated app before a Smith reviews it — and exactly how to close each one.
OAuth loops, sessions not persisting, and JWT errors — a complete step-by-step rescue for the most common Supabase auth failures in Bolt-generated apps.
Replit is great for building. It's not a production host. Here's how to migrate your Replit app to a real deployment without losing your data or breaking your users.
Webhooks work in the Stripe dashboard test but never hit your app. Here's why, and how to fix signature verification, endpoint registration, and the silent failure patterns AI-generated code creates.
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