Smarter User Personas, Context Tricks, and the Impending AI Takeover | Ep. 01 - Jason Arbon, CEO and Founder of Testers.ai and Checkie.ai

Our speakers

Jim Bennett is head of developer advocacy at Pieces, focusing on enabling developers to be more productive by leveraging contextual awareness of not only the code they write but the content they read and the conversations they have.

Jason Arbon the CEO and founder of Testers.ai and Checkie.ai, two services that use AI Agents to test your products. Previously worked on Bing search and Google Chrome. 

Watch below:

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Insights

🟢 AI enhances testing efficiency and user empathy by generating user personas that evaluate websites more effectively than humans.

🟢 Providing less context in AI prompts can lead to better accuracy, reducing hallucinations and improving response quality.

🟢 AI enables continuous testing, delivering real-time feedback before, during, and after development sprints.

🟢 AI can generate requirement specs, eliminating one of the biggest blockers in software testing and accelerating workflows.

🟢 AI-generated code raises regulatory and security concerns, requiring multi-LLM validation and compliance checks.

🟢 The future of software development is AI-driven, and within two years, AI might fully take over some of the coding tasks.

🟢 Humans must adapt to AI's rapid advancement, transitioning from manual testing to AI oversight and decision-making.

🟢 Maximize earnings now before the AI singularity, as automation could soon disrupt the entire software industry. 🚀

Timeline

0:00:00 - Intro

0:01:00 - Capturing context from everything you do, and how do you use it well?

0:03:40 - Humans expectations of AI have gone to infinite

0:10:00 - Selling an ATM to a teller, how can you sell AI to folks whose job will be replaced by AI

0:11:01 - Is AI better than humans at user empathy? Yes!

0:14:20 - Creating user personas with AI and testing your site with them

0:21:57 - LLMs can work better if your prompts are less detailed

0:26:30 - “What didn’t I think off” as a follow-on prompt

0:28:15 - How do we deal with our ego around AI being smarter than us

0:30:30 - How will humans learn to review AI generated code if we don’t learn to code as AI does it all

0:34:50 - AI generated code, regulatory compliance, and ensuring code quality

0:39:55 - Hacks via bad LLM suggestions and validating the responses for security and correctness with multiple LLMs

0:47:55 - Human-in-the-loop for quality validation

0:49:40 - AI can continuously test, giving faster feedback before, during, and after a sprint

0:52:20 - The biggest blocker in testing is waiting for requirements specs, but AI can generate these

0:57:36 - Where do humans fit into an AI future?