Our process - How we work
We are on a mission to make the AI industry easier to understand. We've created a simple process to help decision-makers, developers, and investors choose the right AI tools and companies. Our process has three main steps:
- Explore and Assess
- Investigate and Evaluate
- Get Insights
This approach helps us find, sort, and understand AI projects and partners. It gives you a deeper understanding than just looking at the surface.
Explore and Assess
In the first step, "Exploration," our team uses a diverse set of tools to find good AI startups, tools and products.
We search the web and read industry news to make a list of possible startups. We also use LinkedIn to get useful info and tips from our connections.
We go to industry events to find new AI companies. This helps us learn about the latest AI developments. The "Discover" step helps us understand new companies better before we look at them more closely.
Included in this phase
- Market Research
- Social Network Intelligence
- Event-Based Discovery
- Emerging Players
- Industry Insight
Investigate and Evaluate
Next, in the "Investigate & Evaluate" step, we carefully check how trustworthy and well-known the AI projects and partners are.
For open-source projects, we check how real and strong their community is. Our experts write test code and try it out using the project's materials to see how well it works.
We also talk directly with the founders and project leaders. This helps us understand the startup's goals and plans better. By doing all this, we make sure we really know the startup well before making any decisions.
Included in this phase
- Open Source Verification
- Code Evaluation
- Founder Interviews
- Strategic Assessment
- Practical Testing
Get Insights
In the final "Insights" step, we take all the info we've gathered and turn it into useful knowledge.
We provide helpful insights to people who make decisions, developers, and investors. This includes more than just numbers. We offer advice, look at trends, and compare different options to help them make smart choices.
The "Insights" step isn't just about collecting data. We turn the information into a useful tool. The end result is a custom AI Landscape that helps people choose the right AI tools and companies for what they want to do.
Included in this phase
- Strategic Insights
- Trend Analysis
- Comparative Evaluation
- Decision Support
- Tailored Recommendations
Our values - Helping Developers, Making AI Better
At AI Product Engineer, we help developers work better with AI. Our community:
- * Works with many coding languages
- * Connects coding skills to AI knowledge
- * Offers lists of helpful resources
- * Provides easy-to-follow guides
- * Lets developers work together
- * Shares talks with AI experts
We create a place where everyone can learn about AI, work together, and share what they know. Our goal is to make AI easier for all developers to use and understand.
- Inclusivity. We create a friendly space for everyone. We welcome developers from all over the world, no matter their background or how much they know. Everyone's ideas are important to us.
- Excellence. We make sure our resources, content, and community talks are always high-quality and accurate. We work hard to give you the best info and tools for AI Product Engineering.
- Collaboration. We think teamwork is important. We encourage developers to work together and share ideas. By helping each other, we all learn more about AI Product Engineering.
- Innovation. We love new ideas. We look into the latest tech and show off cool new projects. This helps inspire developers to try new things in AI Product Engineering.
- Openness. We believe in being open. When we share info, show work from our users, or do interviews, we're always honest. This helps build trust in our community.
- Community-Driven. We are driven by a commitment to empower developers worldwide through continuous learning pathways, user-generated contributions, and interactive features.