Hot take: The 'AI script writer' is worse than just writing it yourself.

I've spent the last six weeks rigorously testing Fliki's core promise: the AI-powered script generation. My workflow involved creating 30 distinct short-form video scripts across three categories (product explainers, LinkedIn thought leadership shorts, YouTube ad hooks), using both the AI writer and manual drafting. The results, analyzed through a combination of qualitative assessment and basic readability/engagement score tracking, were unequivocally clear. The AI script writer, in its current iteration, is a net negative for anyone seeking coherent, brand-appropriate, or conversion-optimized output.

My primary methodological approach was a simple A/B test for each script idea:
* **Group A:** Generated via Fliki's AI writer (using detailed prompts, including target audience, tone, key points).
* **Group B:** Self-written, adhering to a basic PAS (Problem-Agitate-Solution) or AIDA framework.

The flaws in the AI-generated scripts were systemic and fell into predictable patterns:

**1. Hallucination of Facts and Features:** This was the most critical failure mode. When asked to write a script for a *software tool's specific feature*, the AI would invent steps, UI elements, or outcomes that simply did not exist. This isn't just unhelpful; it's dangerous for product marketing.
```
// Example Prompt for "Auto-generate meeting summaries":
"Write a 30-second script highlighting how our tool, MeetSync, automatically generates and shares concise meeting summaries."

// AI Output Snippet (Flawed):
"...with just one click, MeetSync not only creates the summary but also predicts action items and sends them directly to your team's Slack channel with due dates."

// Reality:
The tool creates the summary. It does not predict action items or integrate with Slack. The AI inserted common adjacent features from other tools.
```

**2. Catastrophic Tone Inconsistency:** Despite explicit prompts ("conversational and expert," "urgent and exciting"), the AI would often begin in one tone and jarringly switch to another mid-script, sometimes ending with a generic, lifeless call-to-action that undermined the established voice.

**3. Structural Fragility and Non-Sequiturs:** The scripts frequently lacked logical flow. The AI would present a problem, briefly allude to a solution, and then spend disproportionate time on a tangential point or include a completely unrelated sentence that appeared to be a statistical placeholder or a fragment from its training data.

**4. Optimization for "Sounding Good" Over Communicating:** The text often scored well on generic "readability" metrics (Flesch-Kincaid, etc.) but failed to drive a clear message or value proposition. It prioritized using moderately complex vocabulary and full sentences over persuasive structure.

From a pure efficiency standpoint, the argument for AI is speed. However, the time-to-useful-output metric told a different story:
* **AI Process:** 2-3 minutes to generate first draft + 8-12 minutes to fact-check, restructure, and rewrite problematic sections.
* **Manual Process:** 10-12 minutes to draft from scratch using a proven framework.

The manual process consistently yielded a superior first draft with zero factual inaccuracies. The AI process invariably produced a *seemingly* complete draft that required extensive, line-by-line editing to bring to a usable state—a classic example of the "editing paradox," where it's often more cognitively taxing to fix a bad draft than to create a good one from a blank slate.

My conclusion, based on this data, is that Fliki's AI script writer currently functions as a mediocre idea generator at best. It can sometimes produce a usable phrase or suggest a structure, but treating it as a *writer* is a mistake. For users without strong scriptwriting skills, it may provide a crutch, but one that teaches bad habits and injects inaccuracies. For experienced marketers or product people, it is an active impediment. The tool's value remains firmly in its voice synthesis and video assembly capabilities; the script input, however, should be sourced externally. I would strongly recommend the team focus on constraining the AI to avoid hallucinations and improve structural logic, or perhaps pivot to offering templated frameworks that users fill in, rather than attempting end-to-end generation.