I Struggled to Get AI to Write Useful Code — Here's What Finally Worked
The author faced challenges in getting AI to generate useful code for API endpoints. After numerous frustrating attempts, they discovered that providing detailed instructions and examples significantly improved the AI's output. This article shares the effective prompting technique that led to successful code generation.
- ▪The author initially struggled with vague prompts and incorrect outputs from the AI.
- ▪They realized that treating the AI like a diligent intern, rather than a senior developer, was key to success.
- ▪By providing explicit input/output formats and few-shot examples, the AI began generating reliable code.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/__c1b9e06dc90a7e0a676b/i-struggled-to-get-ai-to-write-useful-code-heres-what-finally-worked-432c |
| Publication time | Wed, 03 Jun 2026 08:01:28 +0000 |
| Retrieval time | 2026-06-03T08:11:59.578Z |
| Last seen | 2026-06-03T08:11:59.578Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | hOU9tuZmCT6n |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3953783) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } zhongqiyue Posted on Jun 3 I Struggled to Get AI to Write Useful Code — Here's What Finally Worked #ai #webdev #productivity #python Last month, I had to build a dozen API endpoints for a new microservice. I knew the patterns – CRUD operations, SQLAlchemy models, Pydantic schemas – but typing out all that boilerplate felt soul-crushing. I turned to AI, hoping it would save me hours. What followed was a rollercoaster of bad outputs, hallucinations, and frustration.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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