About this site
I'm Henry Xiang. I build AI content automation that runs unattended for real tenants — agents, retrieval pipelines, and the GEO layer that makes generated content findable.
Why this site exists
Most AI tooling content online is written from documentation. Someone read the API reference, paraphrased the landing page, and published a "review" that never mentions what the tool did when the context window filled up or the token bill tripled. That is enough to rank, and it is useless when your own pipeline breaks at 2am and the tutorial's code sample silently truncates your document.
So this site is written from the other direction: I break things first, then write down what happened. Every guide names the version, the model, and the configuration. Where a step failed, the error message is in the post along with the fix. Where a tool is worse than its reputation, the verdict says so even when there is an affiliate link on the page.
How the testing works
The system behind these posts is a multi-tenant content platform: a .NET API serving tenant-isolated content, a Python retrieval and generation layer, and browser automation that publishes across platforms. It produces a few dozen articles a day across several brands. That is the environment every guide is written against — not a fresh account with three test rows.
Comparisons get at least a month of side-by-side runtime with the same corpus on both sides. Anything shorter than that is labelled as a first look rather than a comparison. Reviews state the runtime in the first paragraph, because "reviewed after six months" and "reviewed after one weekend" should not read the same.
Cost is part of the test, not an afterthought. Every tool that costs money per token or per seat gets measured against a real workload, because the vendor's pricing page and your actual bill are frequently different numbers.
Prices and version numbers go stale. When you spot one, the contact page is the fastest route; corrections are usually applied the same day and the post date at the top changes with them.
Who I am, briefly
A backend developer by trade, working mostly with .NET, Python and MySQL, which means I read logs for a living and have strong opinions about idempotency and retry limits. The AI automation work started as a way to stop paying for platforms that each did a tenth of what the pipeline needed. It turned into the thing I spend most of my working days on.
AgentStack is published by Quanzhou Luojiang Chengheng Information Technology Co., Ltd.. The site is independent: no vendor has paid for a placement, and no post has been reviewed by a company before publishing.
How the site makes money
Two ways, both disclosed on the pages where they appear. Display ads, once the site is approved for them, and affiliate links — if you buy something through a link on this site, the vendor pays a commission and the price you pay does not change. There is a longer explanation on the disclaimer page.
What that does not buy: a verdict. If a tool I have an affiliate link for is the wrong choice for your setup, the post says so, and there are reviews on this site of tools I stopped using entirely.
What this site will not do
- Publish AI-written guides without running the code first.
- Recommend a tool I have not run against a real workload.
- Give medical, legal or investment advice — that is a different job and I am not qualified.
- Publish a benchmark I could not reproduce twice.
- Use a stock illustration of a robot instead of a screenshot of the actual pipeline.
Get in touch
Email suhenggui@gmail.com, or use the contact form. I read everything. Corrections jump the queue.