I had Qwen build a Qwen-powered app — and sat in the reviewer's chair

A developer built QuotePilot, an AI-powered app that automates cross-border B2B price quotes, using Qwen models for both runtime and development. The entire app was written by Qwen models for under $1 in API costs, with the developer reviewing and accepting or rejecting each piece of code. The project highlights the effectiveness of precise interface descriptions for code generation and the importance of human oversight in AI-assisted development.

Most hackathon posts are about what the AI does . This one is also about who wrote it . QuotePilot — an autopilot that turns a cross-border B2B inquiry email into an approved, bilingual EN/中文 price quote — is powered by Qwen at runtime. But the app itself was also largely written by Qwen models, dispatched through a tiny harness while I sat in the reviewer's chair and accepted or rejected each piece. Total model spend for the whole build: under $1 of the $40 hackathon credit. Here's what that actually felt like, where it was magic, and where I had to keep both hands on the wheel. judge / qwen2026 A US software company selling into China answers every inquiry email by hand: read the ask often in Chinese , look up pricing, apply volume discounts, convert USD⇄CNY at today's rate, and draft a bilingual quote with the right cross-border legal and tax terms HKIAC arbitration, Chinese text controlling, "we can't issue a fapiao" note . It's 1–2 hours per inquiry, and the mistakes — a wrong rate, a missing tax clause — are the expensive kind. That's a real workflow with a real brake pedal built in: someone always reviews the quote before it goes out. So the design wrote itself — an agent that does the whole run in under a minute and pauses for exactly one human decision. QuotePilot runs a six-stage pipeline — intake → live FX → pricing → rule risk → AI risk sweep → bilingual drafting — then stops at a human gate. Three Qwen models split the work: | Role | Model | |---|---| | Planner / bilingual drafting | qwen-max | | Extraction + risk-sweep workers | qwen-flash | | Strict structured output catalog mapping | qwen3-coder-plus | The single most important line I drew: the LLM never does arithmetic and never writes legal terms. Every price is Python Decimal , computed in code. Every The model maps "we want CitizenReady for 150 seats" → SKU CR-ENT. The code does the money — always. net = unit price qty 100 - discount pct / 100 .quantize CENT, ROUND HALF UP I built a ~150-line dispatcher scripts/qwen dev.py : hand it a task spec, it sends the spec to a chosen Qwen model, parses the returned files into a staging area, and appends token usage to a ledger. Nothing lands in the repo until I review it. Over the build, Qwen wrote the FastAPI backend, the approval dashboard, the settings UI, the runs index, and more — fourteen dispatches, $0.81 total , a few cents each. Even the demo video's voiceover is Qwen qwen3-tts-flash . The pattern that emerged: describe the interfaces precisely, and a code model fills them in impressively well. When my task spec pinned down exact function qwen3-coder-plus produced code Alibaba Cloud's fcapp.run domain force-downloads HTML. My first deploy curl but the browser downloaded the page instead of rendering it — Content-Disposition: attachment and forbids 3xx fetch doesn't care about the download header, and now the custom.debian10 ships Python 3.7, not 3.10. The docs promised 3.10. An custom.debian12 Don't ask a code model to re-emit a 70 KB file. For one big frontend change I asked Qwen to return the whole updated index.html . It gave me back a file 23 KB smaller — it had silently dropped an entire settings module and never implemented the feature I asked for. Lesson learned: give a code model the changed functions , not the whole file, and diff the result. I hand-wrote that feature instead. An adversarial review round caught 11 real bugs. Before shipping the multi-company refactor, I ran a small multi-agent review — finders proposing bugs, independent verifiers trying to refute each one. It surfaced a discount-field name mismatch that would have 422'd every settings save, and a stored-XSS in a free-text config field. Both would have shipped. Verified findings only; the skeptics killed the noise. Filming the demo caught the best bug of all. The demo video is recorded programmatically Playwright drives the real app; ffmpeg cuts each scene to the voiceover . While reviewing the edit-then-approve scene frame by frame, I noticed the issued quote document still showed the pre-edit numbers — the orchestrator was rendering the quote object it held before the human gate, while the edit endpoint had replaced the gate's copy. On-screen: totals said $32,550, the artifact said $21,930. One-line fix, a regression test, redeploy — and a new rule: watch your own demo like a judge would. It would have been easy to make QuotePilot fully autonomous and call it a day. The interesting product decision was the opposite: make the pause good . The operator sees the drafted quote, the risk flags, and a plain-language summary, and can approve, reject, or edit — adjust quantities, prices, discounts, add or remove line items. When they edit, the server re-prices in Decimal and re-renders the document; approve then issues exactly what they saw. A block -severity risk flag disables approval outright. Autonomy with a brake. For a document that becomes a contract, that's the whole ballgame — and it's what I'd want a judge to remember. It's genuinely great at mechanical breadth — CRUD endpoints, form UIs, wiring, tests-to-spec — and it's fast and cheap at it. It is not the place to hand over money math, security-sensitive parsing, or large-file surgery ; those are exactly where a confident-but-wrong output costs you. The reviewer's job isn't ceremony. It's knowing which outputs to trust on sight and which to read line by line — and never letting the model near the ledger. Qwen built most of QuotePilot. I made sure it never did the math. Try it: https://mark24680617.github.io/quotepilot/ https://mark24680617.github.io/quotepilot/ demo login: judge / qwen2026 · Code: https://github.com/mark24680617/quotepilot https://github.com/mark24680617/quotepilot