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# The Work Begins After the Demo Works

**[Medium](https://daily.dev/sources/medium_js)** · 9 min read · 0 upvotes · 0 comments

## Summary

Getting AI to demo well is easy; running it reliably in production is roughly 70% of the real work. Key lessons: prefer deterministic workflows over agents unless the problem is genuinely unbounded (if you can draw the flowchart, build a workflow). LLMs are probabilistic, so evals are non-negotiable — budget 60–70% of dev time for them and run them continuously. AI coding tools have inverted the classic bottleneck: engineers now outpace product managers who can't write specs fast enough. AI also reintroduces marginal costs to software, making it a business-model question. Measure at three layers: system health, product usage, and business impact. Practical cost levers include model routing, prompt caching, batching, and right-sizing context.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/jeavio-pulse/the-work-begins-after-the-demo-works-bcb3c475bd2c>

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---

Tags: [#llm](https://daily.dev/tags/llm), [#ai-agents](https://daily.dev/tags/ai-agents), [#mcp](https://daily.dev/tags/mcp)

[View this post on daily.dev](https://daily.dev/posts/the-work-begins-after-the-demo-works-3s2pslo8g)

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