Hardhat vs Foundry 2025 — if I’m targeting Singapore roles, which one should I go deep on first?

I onboard juniors pretty regularly, and what actually matters on Day 1 is confidence in a single workflow, not equal knowledge of both. When someone joins our team, they rarely touch deployment scripts immediately — they start by extending tests, debugging traces, and writing small property checks. 

For this, Foundry tends to give juniors quicker wins because the feedback loop is extremely fast, traces are cleaner, and the cheatcodes help them reason about state transitions.

That said, most production stacks still use Hardhat for at least some part of the lifecycle — especially TypeScript scripts, verification, or mainnet forking with specific plugins. The candidates who perform best in interviews usually pick one tool and go deep enough to build tests beyond the basics: fuzzing inputs, asserting reverts properly, and isolating edge cases. Depth signals readiness. Breadth can come later on the job.

If you want to feel prepared for assessments, start with Foundry tests and keep one real Hardhat deployment script ready.

From an audit perspective, Foundry has become almost standard for serious testing work. When teams send us codebases, a lot now include at least partial Foundry suites because fuzzing, invariant testing, and differential tests are easier to express. If you plan to work in environments where audits or security reviews matter, Foundry skill shows up immediately — especially your comfort with interpreting traces, gas snapshots, and state-transition edge cases.

However, juniors often underestimate how useful Hardhat scripting is during early job tasks. When protocols ask us to reproduce bugs, deploy PoCs, or run mainnet-fork simulations, we often rely on Hardhat’s plugin ecosystem. So the balance that works in practice is Foundry for testing depth and many assessments, and Hardhat for tooling interoperability and scripting in real teams.

You won’t fail interviews for not knowing both, but being weak at testing depth does show. Start with Foundry, then add minimal Hardhat fluency.

What I actually evaluate during junior interviews is not the tool choice but whether you understand why tests are structured the way they are. Candidates who rely too much on templates — Hardhat or Foundry — struggle when we change constraints in the problem. The strongest juniors demonstrate three things: ability to justify test cases, ability to debug revert reasons cleanly, and ability to modify or extend someone else’s test suite.

Foundry helps because most assessments today revolve around writing or improving tests, not building full dApps. But I’ve hired strong juniors who only knew Hardhat deeply — as long as they wrote clean tests, used mock contracts properly, and understood coverage gaps.

If I were in your position, I’d master Foundry test-writing for interviews and learn Hardhat’s basics for real-world tasks. Showing depth in one signals readiness; showing confusion across both signals worry.

I switched from Node.js backend to Solidity last year, and what helped me most was picking one workflow and repeating it until muscle memory formed. I chose Hardhat first because I understood TS scripts better, but I moved to Foundry right before interviews — and that’s what made the difference. Fuzzing plus fast test cycles helped me catch mistakes earlier.

You don’t need mastery of both; you need mastery of debugging patterns.

Across AOB discussions on web3 interview prep, the pattern is clear: juniors who go deep into one tool and pair it with strong fundamentals perform much better in early smart contract interviews than those who try to “half-learn” everything. In practice, what recruiters look for in crypto jobs isn’t the tool name — it’s whether you can extend tests, interpret traces, and explain failures without guesswork.

If you’re planning your next 4–6 weeks, start with our Smart Contract Fundamentals Hub — it maps the core concepts you’ll keep testing with Hardhat or Foundry: 

https://artofblockchain.club/discussion/smart-contract-fundamentals-hub

Then read how other engineers approach real-world failures here: https://artofblockchain.club/discussion/debugging-smart-contracts-is-tough-how-do-you-make-it-easier

And if you’re leaning Hardhat-first, this thread on Hardhat debugging mistakes juniors repeat will show you exactly what interviewers and seniors notice in logs, state assumptions, and flaky tests:

https://artofblockchain.club/discussion/need-help-hardhat-debugging-mistakes-juniors-repeat-logs-vs-state-assumptions

A simple way to decide: think of your first 2 weeks on the job. If you expect to spend most time in tests plus debugging failures, Foundry gives you immediate leverage. If you expect deployments plus scripts plus integrations (contracts with frontend/backend), Hardhat skills show up earlier.

If you want a “no-regret” plan for the next 4–6 weeks, do Foundry for tests (unit plus one invariant plus one fork test), and do one Hardhat script end-to-end (deploy, verify, interact). That combo matches real work without becoming “two tools half learnt.”

Adding one more angle to @Aditi’s “Day-1 confidence” point, because this is where a lot of people silently lose points in Singapore loops: it’s not the tool choice, it’s whether the workflow looks repeatable and explainable. A couple of recent take-homes I saw basically tested “can this person join our repo and become useful without handholding?”—meaning: run tests cleanly, locate the failing case fast, explain the failure path, then ship a small fix without breaking everything else.

What helped me (and what I now recommend) is keeping a tiny “handover” note in the repo: one short README that lists the exact commands to run tests and a fork scenario, one sentence on what the key invariant/assumption is, and a quick note on how to reproduce the failure if a test flakes. That makes the submission feel like real team work rather than a one-off assignment.

Curious: in the Singapore take-homes people are seeing right now, are they more “extend/improve the test suite” or more “write a script + deploy/verify + show a repro on a fork”?

This thread is still useful for beginners, but in real Solidity interviews the stronger signal usually goes beyond Hardhat vs Foundry and moves into what your tests actually prove. The gap is often not tool choice — it’s whether you can explain failure modes, edge cases, and why your test setup reflects real smart contract risk.

If you’re preparing for interviews, these two newer discussions add a deeper layer to this exact topic:

US remote Solidity take-home assignments (gas optimization vs clean code)

(https://artofblockchain.club/discussion/us-remote-solidity-take-home-assignment-gas-optimization-vs-clean-code-do#SGEDDGL9) and

How to explain external call risks in Solidity interviews

(https://artofblockchain.club/discussion/best-way-to-answer-risks-of-external-calls-in-solidity-developer-interviews#00006H6A).

For people who recently interviewed: what got more weight in practice — clean unit tests, fuzz/invariant thinking, or a working end-to-end workflow?