The engineer’s approach
As a Lead Auditor of aerospace procedures, I learned not to accept claims at face value. A process had to be understood, examined and tested against what it was supposed to achieve.
I now apply that same mindset to AI tools and online training. I am less interested in what a sales page promises than in what the resource actually teaches, how current it is and whether a beginner could realistically use it.
I study the complete material
I watch the training or use the tool rather than relying on promotional claims or a brief demonstration.
I create transcripts and detailed notes
For video courses, I create transcripts so the full content can be reviewed carefully and important points are not missed.
I use AI as a second pair of eyes
I ask ChatGPT to analyse the transcripts and help check that I have captured the structure, key lessons and limitations accurately. The judgement remains mine.
I test it against practical criteria
I assess whether the resource is beginner-friendly, useful, realistic to implement and still relevant in a fast-moving AI environment.
I consider my own experience
Whenever possible, I use or implement the methods myself. This gives me a better understanding of what works, what takes effort and what may be overstated.
I decide whether it deserves inclusion
If I do not believe it will genuinely help my readers, it does not receive the Colin Reviewed mark.
What I assess
Beginner suitability
Can someone follow it without extensive technical knowledge?
Current relevance
Is the training still valid given the speed of AI development?
Practical value
Does it solve a genuine problem or improve a real workflow?
Implementation effort
What time, tools, money or consistency will realistically be required?
Clarity and completeness
Does the training explain the process properly rather than skipping important steps?
Personal confidence
Would I recommend it to a friend, reader or family member?
I do not review everything. I review what I believe may be worth your time.