Forem: Diana Levytska

Stop copying AI-generated Solidity into empty folders — Kode Sherpa builds the whole project

Diana Levytska — Tue, 07 Apr 2026 09:40:33 +0000

Most AI tools give you a contract. Then leave you alone with a blank project, untested logic, and no deployment setup.

Kode Sherpa works differently.

Before writing a single line of Solidity, it asks the right questions — gathering your requirements, clarifying edge cases, and scoping what actually needs to be built. No generic output from a vague prompt.

Then it generates a complete project: contracts, tests, deployment scripts, and a navigable structure you can work inside — not just a code snippet to copy elsewhere.

What's inside:

Sherpa Studio — an IDE-like environment to manage your entire smart contract project in one place.

Templates — real-world starting points for common blockchain use cases. Skip the blank page, start from something solid.

Spec-first generation — Kode Sherpa asks before it builds. Because the quality of the output starts with the quality of the input.

Whether you're shipping your first Solidity contract or managing a more complex project, the goal is the same: less friction between idea and deployment.

Try Kode Sherpa →

Have questions or feedback? Drop them in the comments — we read everything.

Why generating a smart contract is not the hard part anymore

Diana Levytska — Tue, 07 Apr 2026 09:35:28 +0000

Ask any AI tool to generate a Solidity smart contract today and you'll have something usable in seconds. ERC-20, staking logic, a marketplace contract — doesn't matter. Type a prompt, get code, move on.

For a moment, it feels like the problem is solved.

It isn't.

After spending serious time in this space, one thing becomes obvious: generating the contract is the easy part now. The hard part starts immediately after, and most tools just leave you there.

The illusion of "done"

There's a quiet lie baked into most AI coding tools: once the contract is generated, you're mostly finished.

In reality, a smart contract is not useful because it exists as a code snippet. It becomes useful when it's part of a project you can actually work on — test, review, iterate, and deploy.

The moment you generate that contract, the real questions start:

Where does this file belong in the project?
What else needs to exist around it?
How should the test suite be structured?
What happens when the first generated test fails?
How do you prepare deployment?
How do you make changes without breaking everything?

This is where most "AI-assisted" workflows fall apart. They're good at producing code. They're much weaker at supporting what happens next.

Where the friction actually lives

Smart contract development isn't a single step. It's a sequence of tightly connected steps:

idea → requirements → contract → project structure → tests → deployment → iteration

Break any one of these links, and the whole thing gets fragile. Here's where it typically breaks.

1. Code without structure

Most tools generate isolated code blocks. Fine for a demo, useless for a real development process. Developers need a full context: contracts, tests, configuration files, deployment scripts, a folder structure they can navigate. Without that, generated code is just another artifact you still have to manually organize before work can actually continue.

2. Tests are where things crack

Generating a contract is easy compared to generating useful tests. Tests are where you find out whether the logic is actually coherent — whether your assumptions hold, whether edge cases are covered. This is usually where AI-generated workflows start breaking:

incomplete test coverage
brittle assertions
mismatched expectations
errors from small structural inconsistencies

The promise of "faster development" quietly turns into hours of manual debugging.

3. Deployment as an afterthought

Even when the contract looks good and tests are partially passing, deployment is still left to you. That's another gap the tool didn't close. You're faster on one part of the workflow and still on your own for the rest.

4. Iteration becomes risky

Once v1 exists, you need to refine it. Update features, fix issues, regenerate tests — without breaking the project. This is where structure matters most, and where its absence hurts most. Every iteration becomes riskier and slower when files, dependencies, and conventions aren't handled properly.

What we built Kode Sherpa to do differently

Kode Sherpa started from a simple premise: AI shouldn't just generate smart contracts. It should help developers build complete smart contract projects.

That's a different scope entirely.

The first thing that sets Kode Sherpa apart happens before a single line of code is written. Instead of taking a vague prompt and generating something generic, Kode Sherpa asks questions first. It proactively gathers requirements, clarifies edge cases, and builds a structured understanding of what you're actually trying to build. Poor input leads to poor output — so we deal with it upfront.

Then the workflow continues from there.

Sherpa Studio

Sherpa Studio is the IDE-like environment we built to solve the "AI gives me code but I still have to build the project myself" problem.
Instead of receiving a single code output and copying it somewhere else, you work inside a complete project structure. Navigate files, manage folders, keep everything in one place. It's the difference between getting a contract and getting a project.

Templates

The blank page is expensive. Even when you know what you want to build, starting from nothing takes time.

Templates give you a concrete starting point based on real use cases and common blockchain patterns. Not a generic prompt — an actual project baseline you can adapt. Less setup, faster start, more realistic foundation.

Tests, deployment, and safe iteration

Test generation is part of the flow, not an afterthought. And when the contract is ready, Kode Sherpa generates a deployment script and a README directly inside the project — because "here's your contract" and "here's how to actually ship it" are two very different things.

Features like locked files and structured project handling exist for one reason: to keep the environment stable while you keep iterating. Because fragile workflows don't scale.

Why this matters specifically for web3

Every space has tools that generate code. That alone stopped being impressive a while ago.

What matters now is whether those tools can support the full development process — especially in a domain where the stakes are higher.

Smart contracts aren't casual scripts. They interact with real assets, enforce permissions, and execute irreversible logic on-chain. The code quality matters, yes. But so does the workflow around it: how you structure it, test it, deploy it, and update it safely.

If AI is going to be genuinely useful in web3 development, it has to go further than generation. It has to support structure, testing, deployment, and controlled iteration.

Where we stand

The bottleneck in smart contract development has shifted. It's no longer "how do I write this contract?" — AI solved that part.

The real questions now are:

How do I turn this into a usable project?
How do I test it properly?
How do I deploy it without ambiguity?
How do I keep iterating without breaking things?

That's the gap Kode Sherpa is built to close.

We're still early, and there's a lot ahead. But the direction is clear: not just code generation, but guided project development — from the first requirement to a contract that's actually ready to ship.

Built this in Kode Sherpa? Running into workflow pain we haven't addressed yet? Let us know in the comments.

Great breakdown from one of our builders on smart contract testing with AI 👏 Super valuable to see real challenges and not just ideal scenarios.

Diana Levytska — Fri, 03 Apr 2026 13:39:37 +0000

Syed Ghufran Hassan

Apr 3

Investigation of the failing tests with Kode Sherpa

#kodesherpa #patterns #solidity

Comments 2

3 min read

AI didn’t replace smart contract developers. It just moved the bottleneck.

Diana Levytska — Fri, 03 Apr 2026 13:32:40 +0000

For the past year, everyone’s been talking about how AI can generate smart contracts.

And yes — it can.

You can prompt your way into a Solidity contract in seconds.

But after working on this space for a while, I’ve realized something:

👉 generating code was never the real bottleneck.

The real bottleneck starts after the code is generated.

Things like:

structuring the project properly
writing and running tests
managing dependencies
handling deployment
making safe iterations

AI helps you get started faster.
But it doesn’t remove the complexity of building something real.

🧠 Where things break

I’ve seen this pattern a lot:

You generate a contract → it looks fine
Then you try to actually use it → everything gets messy

tests are missing or incomplete
deployment is unclear
small changes break things
no real structure to build on

And suddenly you’re back to doing everything manually.

⚡ So what changes?

Instead of asking:

“Can AI generate this contract?”

Maybe the better question is:

“Can AI help me manage the entire development workflow?”

From idea → contract → tests → deployment → iteration

👀 Open question

Curious how others are experiencing this:

Are you actually using AI in your smart contract workflow?
Where does it help the most?
Where does it completely fall apart?

Most AI tools generate code. We tried something different: what if AI helped you manage the entire smart contract project instead? Curious if this makes sense 👇

Diana Levytska — Fri, 03 Apr 2026 13:23:44 +0000

Diana Levytska for Kode Sherpa

Apr 3

We turned our AI smart contract generator into an IDE

Comments

1 min read

We turned our AI smart contract generator into an IDE

Diana Levytska — Fri, 03 Apr 2026 13:22:33 +0000

When we started building Kode Sherpa, the goal was simple:
help developers generate smart contracts faster.

But pretty quickly we hit a limit.

Generating code is not the hard part anymore.
The hard part is everything around it:

structuring the project
writing and running tests
handling deployment
iterating safely

So we started asking a different question:

👉 What if AI didn’t just generate code, but helped you manage the entire project?

That’s what led us to build Sherpa Studio.

Instead of just outputting Solidity, you now work inside a structured environment:

contracts, tests, config
file management
deployment scripts generated automatically

We also introduced templates you can explore even without signing up — just to make the entry barrier lower.

Still early, still a lot to improve.

Curious to hear from other devs:
does this direction make sense, or is it overengineering?