Jonathan Baer, CEO and Co-founder of Overlap, a company specializing in multimodal AI agents for video marketing, recently highlighted the significant performance disparity between different approaches to AI agent implementation. In a tweet, Baer asserted that users who engage with AI agents as they would a new hire achieve dramatically superior outcomes, stating, "Our users who treat agents like training a new hire see 1000x results compared to those that expect it to instantly & perfectly do their job for them.
Overlap, a Y Combinator-backed startup, develops AI agents designed to autonomously understand, search, and edit video content, transforming long-form videos into social media clips and other marketing assets. The company's focus is on streamlining content creation for media companies and creators, leveraging advanced AI models to automate tasks that traditionally consume thousands of hours.
The sentiment expressed by Baer underscores a growing understanding within the AI industry: while AI agents are powerful autonomous tools, their optimal performance is often unlocked through iterative feedback and "training" from human users. Unlike traditional software that follows rigid rules, modern AI agents, particularly those powered by large language models (LLMs), learn and adapt based on interactions and data. This process mirrors the onboarding and development of a human employee, where initial guidance and continuous feedback lead to improved efficiency and accuracy.
Industry experts and best practices for AI agent adoption frequently emphasize the need for transparent communication, user-centric design, and dedicated training programs. Companies adopting AI agents are encouraged to foster a "human + agent" mindset, where human oversight and interaction are seen not as limitations but as crucial elements for refining agent performance and ensuring alignment with specific business goals. This collaborative approach helps mitigate biases, improves output quality, and builds trust in the AI system.
The market for AI agents is experiencing rapid growth, with projections indicating significant expansion in the coming years. By 2028, Gartner predicts that 33% of enterprise software applications will incorporate agentic AI, a substantial increase from less than 1% in 2024. This trend highlights the increasing recognition of AI agents as transformative tools capable of automating complex workflows and augmenting human productivity across various sectors. Overlap's success, driven by a philosophy of active user engagement and continuous improvement, exemplifies how strategic implementation can maximize the return on investment in AI technologies.