# Offline human review

## 1. Critical
- [9] Group 1: Avoid AI slop/purple prose (general)
    - Section 3 - weird AI formulation: "high-frequency scenarios where predictable costs and latency are paramount"
    - section 3: mention of "paramount" and "crucial" terms to avoid, we can add "Avoid Purple Prose" in the style guidelines
    - Avoid AI slop like ""leverage"", ""fast-moving world"" , ""But here’s the good news"", overuse of ""significant""
    - AI fluff is seen primarily in adjectives like trivial decisions, paramount, thrive, or phrases like critical decision with confidence, tackling a novel problem. Needs an overall upgrade with toning down AI fluff while keeping the human essence.
    - AI fluff specifics: In introduction: the line between a thriving product and a failed experiment is often drawn at this exact architectural seam. AND This lesson will provide a framework to help you make this critical decision with confidence. AND show you how to design robust systems that leverage the best of both worlds. By the end, you’ll be equipped to choose the right path for your AI applications. In Looking at State-of-the-Art (SOTA) Examples (2025): Workflows also transform creative and legal industries. AND In the developer world, coding assistants like In Zooming In on Our Favorite Examples: feature in Google Workspace perfectly exemplifies a pure, multi-step workflow. AND Perplexity's deep research feature is a fascinating hybrid. In CONCLUSION: You will constantly battle a reliability crisis. AND we will systematically tackle each of these issues. You will learn battle-tested patterns for building reliable systems, proven strategies for managing context, and practical approaches for handling multimodal data. AND frameworks that let you deploy with confidence. Your path forward as an AI engineer is about mastering these realities. By the end of this course, you will have the knowledge to architect AI systems that are not only powerful but also robust, efficient, and safe. You'll know when to use a workflow, when to deploy an agent, and how to build effective hybrid systems that work in the messy, unpredictable real world.
    - ""In the fast-moving world of AI, the line between a thriving product and a failed experiment is often drawn at this exact architectural seam"" -> too metaphorical?
    - "In the fast-moving world of AI" - fast moving worlds are oversuse AI slop.
    - "often drawn at this exact architectural seam." - AI verbosity
    - In the fast-moving world of AI, the line between a thriving product and a failed experiment is often drawn at this exact architectural seam. The most successful AI companies have mastered this balance. They understand that the choice isn’t a binary one between rigid control and total autonomy. Instead, it’s about finding the right point on a spectrum to solve a specific problem. Statements like these feel AI and overly generic.
    
- [3] Group 4: Issue with Section 3 MVP/rapid deployment statement (framing/accuracy)
    - Section 3 - hallucinated with: "For startups, Minimum Viable Products (MVPs), and projects focused on rapid deployment, workflows allow you to move fast without heavy infrastructure investment" which is not present in the article guideline
    - For startups, Minimum Viable Products (MVPs), and projects focused on rapid deployment. Tone shift, from addressing one person to making a general statement. Say: For projects or MVPs that require rapid deployment.
    - "Workflows allow you to move fast without heavy infrastructure investment" - not a good framing as Agents don't neccessarily need heavy infrastructure investment either.


## 2. Important
- [2] Group 10: Avoid 'These aren't just theoretical problems' (AI slop)
    - ""These aren't just theoretical problems; they are the day-to-day reality of building with AI"" -> feels LLM-generated"
    - "These aren't just theoretical problems; they are" - AI slop structure.

## 3. Minor
- [1] Group 14: Specific AI formulation in Section 4
    - Section 4 - weird AI formulation: "This lets the agent go beyond its internal knowledge and affect its environment"

## ! Clashing
- No clashing reviews found.

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