Here’s how to go from 𝘻𝘦𝘳𝘰 tech skills to building 𝘢𝘯𝘺𝘵𝘩𝘪𝘯𝘨 with AI:
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There are 4 essential areas you need to master:
𝐍𝐮𝐦𝐛𝐞𝐫 1: 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈
First area: you need to understand fundamental Gen AI concepts and learn to build AI solutions – from basic prompting techniques all the way down to AI agents:
→ Generative AI: which part of AI is generative AI – and what you can do with it.
→ LLMs: how LLMs work behind the scenes – their potential and limitations
→ Prompt engineering: writing effective prompts to get better results
→ RAG: how to give context to LLMs to personalize and improve results
→ AI API workflows: calling LLMs via APIs inside automation workflows
→ AI assistants: building custom assistants for recurring, repeating tasks
→ AI agents: building AI agents that can perform non-deterministic tasks
→ Voice agents: building voice agents to send and receive calls
→ Data privacy and ethics: how to use AI safely and ethically
𝐍𝐮𝐦𝐛𝐞𝐫 2: 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐁𝐚𝐬𝐢𝐜𝐬
Next, you’ll also need to learn to build automations.
For this you should understand:
→ Web technologies: how the web works behind the scenes
→ Objects: what are business objects – a core programming concept
→ Automation Roadmap: how to identify the right things to automate
→ Automations: what are automations – and what is the right way to build them
→ Testing and debugging: how to test well and fix errors on your automations
→ Orchestration: how to build cohesive systems
𝐍𝐮𝐦𝐛𝐞𝐫 3: 𝐀𝐏𝐈𝐬 & 𝐖𝐞𝐛𝐡𝐨𝐨𝐤𝐬
Anyone who start to play with automation inevitably ends up learning APIs – the backbone that make these possible. Don’t skip it, it will unlock so many more options.
You should learn:
→ APIs: what are APIs, the API parameters, making API requests
→ API security: authentication, authorization and other security mechanisms
→ JSON: working with the JSON file format
→ API documentation: reading API docs and finding the right endpoint
→ Webhooks: setting up webhooks, mailhooks and webhook responses
→ Pagination: processing large data sets by chaining paginated requests
→ OAuth: authenticating a third-party app using OAuth
𝐍𝐮𝐦𝐛𝐞𝐫 4: 𝐃𝐚𝐭𝐚 & 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬
Last part – you should understand how to work with data and databases – whether these are hosted in SaaS solutions or no-code platforms.
Here’s the essential list:
→ Data types: the different forms and shapes data can take
→ Data collection: the best possible ways to collect data from users
→ Data transfer: the different techniques to move data from A to B
→ Data transformation: transforming data to get insights
→ Databases: structure and core properties of relational databases
→ Database functionalities: the features that make databases so powerful
→ Data normalization: how to best structure your databases
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Did I miss anything?
Cre: Alexandre Kantjas
