Wonder combines the speed and horsepower of AI with the accuracy, rigor, and expertise of humans to answer your business questions better and faster at every step.
Here’s how our rigorous selection and training process works:
APPLICATION
Our GMAT-like application tests for:
strategic cognition,
definitive decision-making,
aptitude for understanding text, and
proficiency in quantitative literacy.
Applicants are then screened for:
College degree
English language proficiency
Ability to write effectively
Proficiency in using LLMs & AI technology for research
2+ years of relevant experience in desk research, data analysis, or a similar field
Onboarding
Eligible applicants are invited to our Wonder Academy, a highly intensive, regularly updated, fully proprietary training.
Here, they are upskilled on the latest research tools and methodologies and receive extensive training on:
LLMs,
plug-ins & GPTs,
prompt engineering,
Boolean search, and
digital research best practices (including qualifying online sources and verifying online information).
Daily progress milestones
A comprehensive test on all material and topics covered
A mock research assessment graded on Wonder’s quality standard
THE FIRST 6 MONTHS
Analysts are paired with a senior research supervisor for their first 6 months to ensure they meet our quality and execution standards.
A new analyst's first 10 jobs are comprehensively audited, and feedback is provided to improve their performance where relevant.
We comprehensively audit and provide feedback where relevant for all projects, always.
Wonder researchers are constantly evaluated on dozens of other factors, including rigor, logically-sound research methodologies, credibility of sources, fully answering the question or addressing the inquiry, and more.
The goal of Wonder's extensive research audit process:
Consistently exceed your quality expectations while continuing to develop and strengthen our analyst network.
Ongoing EDUCATION & UPSKILLiNG
Analysts receive ongoing education and coaching to ensure research methods and outputs align with Wonder’s standards.
New modules regularly rolled out to Wonder analysts include:
Advanced research strategies:
Assumptions, proxies, triangulation, Boolean search
LLM & GenAI training:
Prompting engineering, prompt chaining, multi-LLM fluency and navigation for effective use of multiple AI tools to increase output and efficiency
Report & user experience optimization:
Improvements to deliverable quality and digestibility, new formats
You can rest assured:
Analysts use primary sources.
We only rely on secondary sources when primary information is
paywalled or not shared.
ChatGPT is never
used as a source.
We aim for
multiple sources of truth
to ensure we deliver top-notch, fully reliable results.
Analysts consult
robust checklists at every stage of the research process to ensure quality,
accuracy, and reliability.
Our never-ending commitment to being the best,
smartest, and fastest in the business.
Analysts have access to a robust and always-growing library of resources to stay at the
bleeding edge of research science, digital search, LLMs, prompt engineering, and more.
Best practices, new applications of traditional practices and tools, and knowledge are shared widely.
