Comparison
You got to 70% with an AI coding tool. Here is what the last 30% actually costs.
Lovable, v0, Bolt, Base44 and Cursor are genuinely good at the first two weeks. This is an honest account of where they stop, and what to do when you are already past that line.
Short version
The answer, before the argument
AI coding tools will get a working prototype in front of customers faster than any agency, including us, and for a fraction of the price. Use them for that.
They stall at the seams — permissions, migrations, error states, anything requiring a consistent decision across many files — and the stall arrives suddenly, usually the week you start onboarding real users.
At a glance
Side by side
| Dimension | AI coding tools | Engisols |
|---|---|---|
| Speed to first demo | Hours | Two to three weeks |
| Cost to prototype | Effectively nothing | $18K and up |
| Cost to production | Unbounded, and invisible up front | Fixed and quoted |
| Handles auth and permissions | Partially, inconsistently | Yes |
| Handles data migrations | No | Yes |
| Someone accountable at 3am | No | Yes |
| Best for | Proving the idea | Shipping the thing |
In detail
Why each of those is true
Speed
Not a contest. A competent founder with Lovable will have something clickable this afternoon, and we will not. If you are still testing whether anyone wants this, that speed is worth more than everything below.
The 70% wall
The pattern is consistent enough to predict. The happy path is complete and the seams are not: a permission that is checked in three places and missed in the fourth, a schema change with no migration path, an error state that renders a blank screen. Each is small. Together they are the difference between a demo and a product.
Cost
The prototype is nearly free and the last 30% is not, which is what makes the total so hard to see in advance. The honest comparison is not tool-versus-agency, it is prototype-plus-rescue versus build. If the idea is unproven, the first path is still cheaper.
Code you can hand over
Generated code is often readable and rarely coherent — patterns vary between files because each was generated in a different context. A new engineer can read any single file and still take three weeks to understand the system, and that cost lands on whoever you hire next.
Accountability
When the tool produces something subtly wrong, there is nobody to ask. That is fine at prototype stage and stops being fine the day you have customers with data in it.
The honest part
When AI coding tools is the better answer
Written without hedging. If one of these describes you, take it — the referral is worth more to us than a bad fit.
Choose AI coding tools
- You are testing whether anyone wants this at all. Do not hire us to find that out.
- The audience is small and known, and a rough edge costs you a conversation rather than a customer.
- It is an internal tool for a handful of colleagues who will tolerate friction.
- You have more time than money and are willing to learn the tool properly.
Choose Engisols
- Real customers have data in it and losing it is a real event.
- You have hit the wall — auth, migrations, permissions, silent failures — and each fix is breaking something else.
- You are raising, and due diligence is going to read this codebase.
- You need a date you can commit to publicly.
- Somebody has to be accountable for it working at 3am.
FAQ
Questions people actually ask
Can you just fix what the tool built, or does it need starting again?
Usually fix. The honest split across the rescues we have run is roughly half repair, a third partial rebuild of specific subsystems, and the rest a genuine restart — and the restarts are nearly always projects that outgrew their original data model rather than projects that used AI badly.
Is AI-generated code worse than human code?
Not line by line, and that is what makes it deceptive. It is locally reasonable and globally inconsistent, because each file was generated without the others in view. The defects cluster at the boundaries rather than inside functions.
Do you use AI tools yourselves?
Yes, daily, with a senior engineer reading every line before it lands. The difference is not the tool, it is whether someone is accountable for the shape of the whole system.
How do we know which side of the line we are on?
The clearest signal is whether fixes are creating new breakage. Isolated bugs mean the architecture is holding. If every repair moves the problem somewhere else, the seams have gone, and that is what the Build Audit measures.