Promptly student experiences

What students say about their time here

Honest accounts from people who completed Promptly's tracks — what they found useful, what was difficult, and what they built.

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From learners across Thailand

SP

Siriwan Phakdee

Bangkok · Track 01

I had used AI tools at work for a while but never really understood what I was doing. Track 01 changed that. The exercises forced me to think carefully about why a model was giving certain outputs, not just accept whatever came back. The final project took longer than I expected, which probably means I learned more than I planned to.

June 2025

KN

Kritchai Namsai

Chiang Mai · Track 02

Track 02 was harder than I expected — in a good way. Connecting a model to actual code and then testing that the whole thing behaves sensibly took real thought. The mentor's feedback on my second build was specific and saved me from a bad architecture decision I was about to repeat. Would have liked slightly quicker turnaround on submissions, but the quality of feedback was worth it.

May 2025

AT

Anchisa Tanaka

Khon Kaen · Tracks 01–03

I did all three tracks over about seven months. Track 03 was the most demanding — scoping the capstone, building it, documenting it honestly, and then presenting it in front of the mentor. It was also the most useful thing I've done professionally in a few years. The documentation requirement in particular forces you to think clearly about what your application actually does versus what you want it to do.

May 2025

PT

Phurit Thongchai

Udon Thani · Track 01

I was nervous about studying in English, but the material is written clearly and without jargon where it can be avoided. The pace worked for me as someone fitting study around a full-time job. The exercises are short enough to complete in an evening, and you see results quickly enough that you want to keep going.

June 2025

NW

Nipa Wongkamjan

Bangkok · Track 02

What I valued was that the course does not pretend AI applications are simpler than they are. Testing was given as much attention as building, which matched my experience trying to use AI at work — things that seem fine in simple demos break in real use. I came away with better habits around testing and documentation.

April 2025

WS

Warit Sombat

Nakhon Ratchasima · Track 03

Track 03 pushed me in directions I had not thought I needed. Writing an honest evaluation of my own capstone, including the parts that did not work well, was uncomfortable at first but genuinely useful. The mentor gave me specific suggestions for improving the safety section of my documentation, which I revised and improved before the presentation.

May 2025

Three learner journeys in detail

Case Study 01

From marketing analyst to AI application builder

Challenge

Siriwan used AI writing tools daily but had no framework for understanding why outputs were inconsistent. She wanted to build a text classifier for internal reports but did not know where to start.

How Promptly helped

Track 01 gave her a vocabulary for describing what was going wrong with her prompts. By the final project she had a working text-based tool that categorised internal reports by topic with reasonable accuracy.

Outcome

Completed Track 01 in 5 weeks. Now using the classifier on a small scale at her current role. Enrolled in Track 02 to extend it into a more complete application.

Case Study 02

Junior developer building a tested AI feature for the first time

Challenge

Kritchai could write code but had no experience integrating language models into applications. His first attempts produced outputs that looked right in demos but behaved inconsistently in real inputs.

How Promptly helped

Track 02 introduced him to systematic testing for AI features. Mentor feedback on his second project pointed out a specific pattern he was repeating that caused inconsistency. He revised and the output improved significantly.

Outcome

Completed three mini-builds in Track 02. Reduced the error rate in his final project compared to initial attempts. Now has a repeatable testing process he applies to new features.

Case Study 03

Researcher completing a full capstone for their portfolio

Challenge

Anchisa had studied AI at university and wanted a practical project she could present to employers. She had skills but lacked a structured process for documenting and evaluating her own work honestly.

How Promptly helped

Track 03 provided an evaluation framework and required her to document limitations as well as capabilities. The presentation format forced her to prepare answers to hard questions about her capstone's design choices.

Outcome

Completed a documented, presented capstone project over 10 weeks. The project now forms the centrepiece of her portfolio. Mentor feedback identified two areas to strengthen before final submission, both of which she addressed.

Where Promptly stands

140+

Students enrolled

4.6/5

Average satisfaction

3

Cohorts delivered

8+

Material updates per year

Contact information

Address

61 Si Chan Road, Nai Muang
Khon Kaen 40000, Thailand

Office Hours (ICT)

Mon–Fri 09:00–18:00
Saturday 10:00–14:00

Ready to start your own track?

Write to us with a brief introduction. We will suggest where to begin based on what you already know and what you want to build.

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