How I Use AI Tools as a Web3 Developer

It’s been about a year since I started integrating AI tools seriously into my development workflow. I resisted for longer than I should have — partly scepticism, partly the classic developer ego thing of “I should be able to figure this out myself”. Eventually I caved, and I have thoughts.

What Actually Helps

Boilerplate and scaffolding. Asking an AI to generate a basic ERC-721 contract or a standard API handler is genuinely useful. Not because I can’t write it, but because starting from a skeleton and modifying it is faster than starting from a blank file every time. The generated code is usually sensible enough to be a good starting point.

Explaining unfamiliar code. I work with a fair bit of code I didn’t write — open source contracts, legacy services, other people’s ABIs. Pasting a function and asking “what does this do and what should I watch out for?” saves a lot of time jumping between documentation tabs.

Writing tests. I dislike writing tests for obvious-behaviour functions. AI is surprisingly good at generating unit test cases, including edge cases I might have glossed over. I still review everything but the coverage improves noticeably.

What Doesn’t Work Well

Anything bleeding-edge or niche. If you’re working with a protocol that launched six months ago, or a new L2 with limited public documentation, the AI will confidently give you outdated or hallucinated information. This is dangerous in Web3 where a wrong address or incorrect contract ABI loses real money. I always cross-reference with official docs for anything chain-specific.

Auditing smart contracts. I have seen developers paste their Solidity into an AI and treat the response as a security review. Please don’t do this. AI can catch obvious patterns but it misses subtle re-entrancy issues, business logic bugs, and protocol-specific edge cases. Use proper auditing tools and if it’s going to hold real value — get an actual audit.

Architecture decisions. Great for tactics, not great for strategy. Asking “how do I implement this function” works. Asking “how should I structure this entire system” tends to produce generic advice that doesn’t account for your specific constraints.

My Current Stack

I mostly use Claude for code explanations and Go/Solidity generation, and GitHub Copilot for autocomplete while I’m typing. They serve different purposes and work well together. I turn Copilot off sometimes when I’m in “deep thinking” mode because the autocomplete starts to feel like it’s steering my thoughts rather than following them.

The Bigger Picture

I think the honest answer is: AI tools make the boring parts of development faster, which frees up time for the parts that actually require thinking. For Web3 specifically, the “require thinking” parts are non-trivial — the security surface is large and the cost of mistakes is high. So my approach is to use AI for speed on the low-risk stuff, and stay cautious on anything that touches user funds or sensitive logic.

It’s a tool. A pretty useful one. But it’s not a replacement for understanding what you’re building.

Why I Reach for Go When Building Web3 Backends

I have been writing Go professionally for over a year now, mainly for the backend of Web3 products. Before that I was mostly JavaScript and Python. I want to write down why Go has become my default choice for anything backend in the Web3 space, because I wish someone had told me this earlier.

The Concurrency Thing is Real

When you’re building something that listens to blockchain events — indexing transactions, watching contract events, syncing state — you need concurrency that doesn’t make you want to cry. Go’s goroutines are genuinely easy to use compared to JavaScript’s async/await chains or Python’s asyncio.

A simple example: listening to multiple smart contract events simultaneously and writing them to a database. In Go this is a handful of goroutines and a few channels. Clean and readable.

go-ethereum is Excellent

The go-ethereum library (geth) is the reference Ethereum client and it’s written in Go. Using it from Go feels native in a way that doesn’t quite translate to other languages. You can subscribe to events, call contract functions, sign and send transactions — all with proper types, none of the any and casting chaos I used to deal with in TypeScript.

client, err := ethclient.Dial("wss://mainnet.infura.io/ws/v3/YOUR_KEY")
if err != nil {
    log.Fatal(err)
}

query := ethereum.FilterQuery{
    Addresses: []common.Address{contractAddress},
}

logs := make(chan types.Log)
sub, err := client.SubscribeFilterLogs(context.Background(), query, logs)

That’s it. No callback hell. Errors are explicit. I know exactly what’s happening.

Performance Matters at Scale

On a busy chain like Polygon or during a token launch, your backend might be processing hundreds of events per second. Go’s performance here is just in a different league from Python. I noticed this the first time we had a high-traffic period at work — the Go service barely moved on CPU, while the old Python service we had experimented with earlier would have been struggling.

The Learning Curve is Honest

Go is opinionated and the error handling is verbose. Writing if err != nil fifty times per file feels tedious at first. But this explicitness saved me multiple times when I was new to the codebase — every failure path is explicit, not hidden behind an exception that might bubble up in a weird way.

If you are coming from JavaScript, the static typing will also feel restrictive initially. Give it two weeks. You’ll miss it in every other language after that.

What I’m Building With It Now

Currently using Go to build a token-gating API — it checks NFT ownership and issues signed session tokens for gated content access. Go’s standard library handles the crypto primitives really well, and the binary compiles to a single self-contained executable which makes deployment painless.

If you are building anything in the Web3 backend space and haven’t tried Go, I’d really recommend it. The ecosystem is mature and the language is genuinely a pleasure once it clicks.