What professionals say about studying with Setthi Code
The reviews here reflect the experiences of people who have completed one of our three programmes. They are not selected only for being positive — we have included accounts that are measured and specific rather than promotional.
Back to HomeAccounts from programme participants
I came in knowing almost nothing about AI tools and expecting to feel out of my depth. The Business AI Literacy course was much more grounded than I expected — a lot of it was about how to ask good questions of a technical team rather than trying to become technical yourself. That framing was exactly what I needed. The weekly exercises pushed me to actually write things down, which made the ideas stick.
April 2025 · Business AI LiteracyThe Product Development Track gave me something I had not found in any of the online courses I had tried — actual practice writing product briefs for AI features, with real comments from someone who has done this work. The office hours were genuinely useful, not just a check-in. My main observation is that the track demands a real time commitment, so go in with clear eyes about that.
March 2025 · AI Product DevelopmentI enrolled in the Strategy programme with some scepticism — I had been through two other AI-related workshops at this point and found both of them overpromised and underdelivered. This one was different. The one-to-one structure meant that the work actually connected to my organisation's situation, not a generic case study. By the end I had a strategy document I could actually use, which was the point.
May 2025 · AI Strategy & ImplementationWhat I valued most was how careful the faculty were about not overstating things. A lot of AI education right now is essentially marketing dressed up as learning. Setthi Code was not that. The reading material was current, the discussions were honest about uncertainty, and I came away with a much clearer sense of where AI tools are actually useful and where they are not.
February 2025 · Business AI LiteracyI found the Product Development Track useful mainly because it forced me to think about AI features from a scoping and evaluation perspective, not just a design perspective. The exercise on writing evaluation criteria was something I had not done before, and I brought that directly into a project at work the following month. Practical in the right way.
April 2025 · AI Product DevelopmentAs a founder without a technical co-founder, I needed to understand enough about AI to evaluate the proposals I was receiving from vendors and contractors. The Business AI Literacy course gave me exactly that. It was eight weeks rather than a weekend, which felt appropriate — this is not material that settles in quickly, and the pacing gave the ideas time to work.
January 2025 · Business AI LiteracyThree participant journeys in more detail
Reframing how an operations team approaches AI vendor conversations
A senior operations manager at a Bangkok-based logistics firm was receiving an increasing number of proposals from vendors offering AI-based process tools. She had no framework for evaluating them and found herself either approving things she could not assess or deferring to a technical team that did not understand the operations context.
Over eight weeks, she worked through the course material while applying each written exercise to a real vendor proposal she had received. The exercises gave her a structured way to identify which claims were testable and which were not, and how to translate her operations knowledge into useful questions for a technical evaluation.
At the end of the course she had a practical evaluation framework she could apply to future proposals. She subsequently led the assessment process for a tool that her organisation did decide to trial — and the vendor feedback was that the questions she raised were among the most specific they had received from a non-technical buyer.
Duration: 8 weeksWriting a grounded internal strategy for AI work at a mid-size firm
The managing director of a Bangkok-based professional services firm was facing board-level pressure to articulate an AI strategy. He had attended several industry events and read widely, but had no coherent framework for translating what he had absorbed into something he could present internally with confidence.
Over five months, the one-to-one structure allowed the programme to be organised around the specifics of his firm — its existing technology, its organisational structure, and the areas where AI might plausibly support the work. Each written exercise was framed around his context rather than a generic scenario.
He completed the programme with a strategy document that the board accepted as the working basis for the firm's AI direction over the following twelve months. He described the document as the most substantive piece of strategic writing he had produced in several years — partly because the programme forced him to be specific rather than aspirational.
Duration: 5 monthsImproving how a product team scopes AI-related feature requests
A product manager at a Bangkok-based software company was regularly receiving requests from the business side to "add AI" to existing features. She lacked a clear process for translating those requests into something the engineering team could evaluate, which meant a lot of wasted scoping time and growing frustration on both sides.
The Product Development Track gave her a structured vocabulary for AI feature scoping and a template for the kind of product brief that allows an engineering team to assess feasibility without ambiguity. The office hours gave her a space to work through a live example from her own team's backlog.
She introduced a version of the brief template from the track into her team's process. The engineering team lead commented that the requests coming through were meaningfully clearer within a couple of months, and that the brief format had become the team's default starting point for any feature with a machine learning component.
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