𝗔𝗜 𝗪𝗿𝗶𝘁𝗲𝘀 𝗖𝗼𝗱𝗲. 𝗜𝘁 𝗖𝗮𝗻'𝘁 𝗗𝗲𝗳𝗶𝗻𝗲 "𝗗𝗼𝗻𝗲."

I built an AI slide deck generator. You type a topic and get a presentation.

The AI demo worked instantly. It wrote an outline. It made slides. It exported a file. On my screen, it looked finished.

It was not finished.

The AI proved one user could make one deck one time. A real product is different. It needs to handle 100 users at once. It must bill them correctly. It must recover when a step fails. It must export a file that actually opens in PowerPoint.

The AI did not add these things because I did not tell it to.

When you build with AI, the hard part is not describing the feature. The hard part is defining what "done" means.

I used Velobase Harness for the foundation. It handled auth, payments, credits, and databases. This let me focus the AI on the PPT generation itself.

That is where "looks done" and "is done" pulled apart. I found four main gaps:

  • Concurrency: AI thinks one successful run equals a finished feature. A real system needs to split tasks into queues. You must generate each slide as its own job so workers can scale.

  • Billing: AI will deduct credits once and stop. A real product needs a state machine. You must reserve credits, settle based on actual usage, and refund on failure.

  • Self-review: If the backend retries a task silently, the user sees a spinning icon. You must show the status. The user should see "checking" or "redrawing" so they know the system is working.

  • Export: A slide can look great in a browser but break in a PPTX file. The requirement is not just to make a file. The requirement is that the file must match the web preview.

I changed my instructions. I stopped giving the AI a feature list. I started giving it acceptance criteria.

My new rules for the AI:

  • Build a production-ready SaaS, not a demo.
  • Support 100 concurrent users.
  • Use independent queues for planning and slide creation.
  • Connect every model call to the billing system.
  • Pause and resume tasks based on credit balances.
  • Run layout checks after every slide.
  • Ensure the PPTX export matches the visual preview.
  • Write tests for concurrency and failure, not just success.

AI writes code fast. It just does not know what makes code shippable. It treats a local demo as a full system.

ఇంజనీరింగ్ పరిమితులు, వైఫల్య సందర్భాలు మరియు వ్యాపార నియమాలను అందించడమే మానవ పాత్ర.

Harness SaaS పునాదిని అందిస్తుంది. AI లాజిక్‌ను పూర్తి చేస్తుంది. మీరు కేవలం అత్యంత ఖచ్చితమైన ఇన్‌పుట్‌ను అందిస్తే సరిపోతుంది.

మీరు AI ద్వారా నిర్మించిన ఉత్పత్తిని విడుదల చేస్తే, "ఇది పనిచేస్తుంది" మరియు "ఇది కస్టమర్లకు సిద్ధంగా ఉంది" అనే అంశాల మధ్య ఉన్న కష్టతరమైన అంతరం ఏమిటి?

మూలం: https://dev.to/velobasex/ai-can-write-the-code-it-cant-tell-you-when-the-product-is-done-4oh6