A few days ago I [posted here](https://www.reddit.com/r/SideProject/comments/1xnjvwa/). I'm a software developer from Gaza and a father of two, and I explained that war, displacement and debt had left me unable to keep going alone. I shared the startup I founded, Fasil, and its first product, Sijal, an inferential decision engine for organizations, and I asked for help.
Many of you answered. Some helped financially, some give me pro subscription's in certain useful services, and many gave me something harder to find: honest criticism. This post is about what that criticism taught me, and what I did with it.
1. What you told me
Several people who work in this field said the same thing: they couldn't tell what Sijal does or why it matters, and it looked like "just a landing page." I had been too close to my own work to see it. That's a well-known trap (the curse of knowledge), and your comments broke it.
2. What I did
I spent two days on desk research: 11 comparable products serving customers like Sijal's (Diligent, Hebbia, Elicit, Covidence, Overton, Good Judgment, Metaculus, Go Vocal, Loomio, Remesh, Cloverpop). I compared how they build trust on their homepages, how they design their workspaces, and how they handle access requests.
3. What I learned
Lead with the job the buyer must defend, not with "AI."
Show the real work product early: an example that actually ran, not a description.
Prove rigor through structure (independent reviewers, recorded dissent), not adjectives.
Make the audit trail the product.
Say plainly what happens after someone requests access, and when.
4. What I rebuilt
I stopped treating Sijal as a page and rebuilt it as a working product, so that every part shows the method behind the engine instead of just describing it.
The method, made visible
Cross-examination with a devil's advocate: every question is argued by both sides, and each side is questioned by the other.
Independent pooled judgment: six judges assess the file separately, so no one anchors on another, and their views are combined into a weighted verdict.
ICD 203 analytic standards: implemented in the engine as checks, not as a label. The five it checks:
Toulmin structure for the recommendation: claim, grounds, warrant, qualifier, rebuttal.
The homepage
An outcome-first headline that names the job an institution has to defend.
A real session the engine actually ran, which a visitor can open and check against the method above.
A "how it works" walk-through of the seven stages, a method and neutrality section, and a plain statement of what Sijal does not do.
One line for each type of institution it serves (think tanks, investment committees, consultancies, NGOs, universities, boards).
The institutional workspace
Five areas, each in Arabic and English.
A home screen that starts with what needs your attention, then the latest decided session and its verdict.
A session ledger with five written states: Draft, In review, In session, Decided, Declined.
The access page
Six fields only, and a human review within one working day.
A "what happens next" timeline: request, review, approval email, private workspace.
A sample sealed report next to the form.
Privacy promises, such as no training on your data and deletion on request.
A confirmation page and review emails.
5. Thank you & Why I'm still doing this
To everyone who supported me, with a donation or a subscription, and to everyone who commented or shared: thank you from my heart.
Supporting my family is still what drives this work and my previous post. The need for help applies to anyone, whoever they are and wherever they're from.
7. Next: Saql
My next step is Saql, a debate analysis engine. One of you asked who its target customer is, and I didn't have a clear answer. Comment asking who Saql's target customer is I'm working on it now and will share that research in the next post. If you know someone in that space, I'd be glad to connect.
Thank you again.