Crafting My First 30-Day Video Journey with AI — LiliDi Blog
A detailed, anti-hype case study of a creator's initial 30 days using AI for video generation, focusing on practical learning and realistic outcomes. Learn fro…
By lilidi editorial
Crafting My First 30 Day Video Journey with AI Starting a new journey in content creation, especially one involving rapidly evolving AI tools, can feel like stepping into a whirlwind. There's a lot of hype, a lot of promises, and often a significant gap between expectation and reality. This article isn't about the hype. This is a practical, no nonsense account of my first 30 days diving deep into AI powered video generation, using a platform like lilidi.ai. My goal was not to create viral blockbusters immediately, but to understand the workflow, identify limitations, and, most importantly, build a sustainable process. Consider this a raw, unvarnished look at the learning curve, the successes, and the inevitable missteps. Week 1: The Initial Dive and Reality Check My first week was characterized by a healthy dose of experimentation and a quick reality check. I started with a simple
premise: generate short, educational videos on niche historical facts. My initial excitement about "just typing a prompt" quickly met the nuanced reality of effective prompt engineering. Day 1 3: Prompt Engineering Basics Learning the Language: I quickly realized that AI doesn't "understand" intent in the human sense. It understands specific instructions. Vague prompts like "cool history video" yielded generic, unusable results. I had to learn to be explicit: "A 30 second animated video depicting the construction of the Great Pyramid of Giza, focusing on the movement of large stone blocks. Style: realistic, ancient Egyptian color palette. No human figures shown." This produced much more relevant output. Iterative Refinement: My first video attempts involved multiple prompt revisions. It often took 5 10 iterations to get something close to my vision. This wasn't a "one click" solution,
but a process of careful calibration. Understanding Parameters: I spent significant time exploring aspect ratios, video lengths, and available styles within lilidi.ai. These parameters are not mere checkboxes; they are fundamental controls that dramatically alter the output. Day 4 7: The Output Quality Spectrum By the end of the first week, I had generated about 15 short video clips. The quality varied wildly. Some were surprisingly good, capturing motion and detail effectively. Others were abstract at best, or simply didn't align with the prompt, despite my best efforts. I learned that current AI video generation is not about flawless realism for every frame, but about generating compelling sequences that can be edited and enhanced later. Accepting Imperfection: Not every generated frame will be perfect. The trick is to identify the usable segments and build around them. Early Editing
Insights: Even rudimentary editing software became essential. Trimming, sequencing, and adding basic transitions transformed scattered clips into coherent narratives. Week 2: Finding My Workflow and Managing Expectations Week two was about establishing a more efficient workflow and recalibrating my expectations. I shifted from broad experimentation to focusing on a specific micro niche: explainer videos for complex scientific concepts, visualized simply. Day 8 14: Scripting and Storyboarding (AI Assisted) Pre planning is Paramount: I adopted a mini storyboard approach. For each 60 second video, I broke it down into 5 10 second segments and wrote specific prompts for each. This drastically improved consistency. AI as a "Visual Brainstormer": Instead of expecting AI to deliver a finished product, I started using it as a powerful visual brainstorming tool. I'd generate multiple versions of
a single segment's prompt to see different interpretations, then select the best one. The Cost of Iteration: Generating video clips consumes resources (credits, time). I became more strategic about when and what I generated to avoid unnecessary expenditure. The "Good Enough" Mindset I realized that chasing absolute perfection for every second was a fruitless endeavor with current AI technology. The goal shifted to "good enough" for the conceptual explanation. This meant accepting slight visual anomalies if the overall message was clear and engaging. Week 3: Integration and Enhancement By week three, I had a collection of raw AI generated video segments. This was where the real "content creation" began: bringing these segments to life with traditional editing and sound design. Day 15 21: The Power of Post Production Voiceovers and Music: A well produced voiceover significantly elevates
the perceived quality of even moderately generated video. I invested time in clear, concise scripting and good audio recording. Contextual Audio: Adding subtle background music and sound effects (e.g., a "whoosh" for a concept evolving, a gentle hum for a scientific process) made the videos far more immersive. Text Overlays and Graphics: Since AI video generation doesn't always handle text well within the frame yet, I relied on traditional editing for clear on screen text, titles, and basic info graphics. This ensured key information was conveyed regardless of the generated visuals. Speed Ramps and Transitions: Varying playback speed for generated clips and using thoughtful transitions (fades, wipes, dissolves) contributed to a professional feel. Leveraging lilidi.ai's Strengths I focused on using lilidi.ai for what it does best: generating unique, often surreal or difficult to film
visual concepts quickly. For instance, visualizing quantum entanglement or the expansion of the universe became feasible without complex CGI or stock footage libraries. Week 4: Refinement, Output, and Future Planning The final week was dedicated to polishing my existing projects, understanding output formats, and planning for continued integration of AI into my workflow. Day 22 26: Output and Platform Considerations Resolution and Format: I experimented with different output resolutions to balance file size and visual fidelity for various platforms (YouTube, social media shorts). Understanding codecs and export settings became crucial. Platform Specific Editing: A video destined for Instagram Reels needed different pacing and aspect ratios than one for a YouTube tutorial. My editing process adapted to these platform requirements. Day 27 30: Reflecting on the "AI Creator" Journey Looking
back at the end of 30 days, I had successfully produced 8 short educational videos, each around 60 90 seconds long. They weren't Hollywood blockbusters, but they were compelling, informative, and created much faster than traditional animation or stock footage compilation would have allowed. Time Savings: While not instant, the overall time investment for generating unique visuals was significantly reduced. Creative Expansion: AI opened doors to visualizing concepts I previously considered too complex or expensive. Skill Shift: My role shifted from "animator" or "videographer" to "prompt engineer," "visual director," and "post production specialist." It's a new skill set, not a replacement for old ones. The Ongoing Learning Curve The AI landscape is dynamic. What works today might be superseded tomorrow. Continuous learning of new prompt techniques, understanding model updates, and
exploring new features within platforms like lilidi.ai is not optional; it's fundamental for staying effective. Conclusion: AI as a True Co Creator, Not a Magic Wand My first 30 days with AI video generation have been incredibly insightful. It's clear that AI is not a magic wand that instantly produces perfect videos. Instead, it's an exceptionally powerful co creator tool that, when wielded with skill, patience, and a healthy understanding of its limitations, can revolutionize certain aspects of video content creation. The key is in the interplay between human creativity, strategic prompting, and diligent post production. It amplifies capability rather than automating the entire creative process. For anyone looking to explore the cutting edge of video production, embarking on your own structured 30 day journey is highly recommended. FAQ Q: How much time did you realistically save using
AI for video? A: For concept visualization and generating unique B roll footage, I saved significant time, potentially 50 70% compared to traditional animation or complex stock footage searches. However, this saving was partially reinvested in prompt engineering and meticulous post production. Q: Is current AI video generation suitable for highly realistic or narrative films? A: For highly realistic, feature film quality, or complex narrative films with consistent character arcs, current AI video generation is generally not yet suitable as a standalone solution. It excels more in abstract, explainer, or illustrative contexts where specific visual consistency across long sequences is less critical. Q: What was the biggest challenge in your first 30 days? A: The biggest challenge was bridging the gap between my conceptual vision and the AI's literal interpretation of prompts. It required a
significant shift in thinking to articulate visual ideas in a way that the AI could process effectively, coupled with managing expectations about inherent imperfections in the generated output.