Release the CrackenAGI to skyrocket your application quality, security, and scalability.
Emerged from the halls of MIT, CrackenAGI is a developer tool for application testing powered by generative AI agents. It autonomously hunts elusive bugs and vulnerabilities, supercharging manual quality (v1 phase), penetration (v2), and performance (v3) testing efforts. It generates and autonomously executes test cases described in natural language, just like a Product Manager, QA Engineer, or Ethical Hacker would. It outsmarts standard code-based e2e tests by being flexible and intelligent at every step of the testing process.
CrackenAGI draws inspiration from recent advancements in generative AI (ChatGPT, MLLMs) and gen-AI autonomy (AutoGPT, BabyAGI, LangChain). It is developed by engineers with decades of software architecture experience and is supported by a team of rockstar advisors: ex-Apple, Google, Fortune 100, FTSE 100 executives; MIT & Stanford PhDs. It has further received pre-funding support from the world's top VCs.
Many parts of the software development cycle still require substantial manual effort. Existing automation tools, while helpful, demand substantial time and financial investment and often underperform, limiting innovation and slowing solutions deployment.
Check out the latest related surveys by GitHub and StackOverflow:
https://github.blog/2023-06-13-survey-reveals-ais-impact-on-the-developer-experience/
https://stackoverflow.co/labs/developer-sentiment-ai-ml/
Alongside advancements in generative AI gen-AI autonomy frameworks, we can now harness AI's capabilities to streamline the software development pipeline. We also understand that the generalized autonomy language models like Adept's ACT-1, BehaviourGPT, and generalized frameworks like AutoGPT and SmartGPT can't handle downstream tasks effectively and are not alone viable for such applications. CrackenAGI, however, refines these models for the specific needs of software development, bypassing their inherent limitations.