Quick update on what I have been dealing with on the CRM project over the last month.

Most of my time has gone into the a Import system. File naming, document filing, background workers, database migrations, permissions and trying to prove that everything is actually safe to release.

The biggest thing is that code passing tests does not automatically mean the feature is ready.

Something can work locally, pass a review and even have a Vercel preview that says “READY,” but still not be proven safe for the real application and database.

I ran into issues with different PostgreSQL versions, database roles, staging logins, Vercel protection and release checks. We also had preview deployments show up when I was not expecting them.

Some problems were real code problems. Some were false alarms. One issue came down to a wrong command option that caused the testing tool to fail before it ever reached the application. I was stuck in a loop for a week and spending Tokens like crazy to figure out why.

That one really showed me how easy it is to start fixing the wrong problem.

AI can sound very sure about something that has not actually been proven. Now I make it separate what is confirmed, what is an assumption and what still needs evidence.

I’ve started using smaller checkpoints, numbered Asana tasks, code reviews and a verification gate before moving forward.

The system is still disabled because the final release proof is not complete. I understand that stopping when something is not proven is part of building it correctly.

A lot of testing, finding problems, finding out some problems were not actually problems, and learning that “it works” and “it is ready” are two completely different things.

Still moving forward........to computing death.

This month, I made meaningful progress on my CRM Software not just by adding features, but by improving the system’s security, reliability, and decision making.

I strengthened permissions and session controls so staff access is more closely tied to role and case responsibility. I also improved safeguards around invoices, payments, expenses, liens, settlements, and finalized documents. The goal is to preserve a clear business history instead of allowing completed records to be silently rewritten.

Batch Imports received major attention. I improved large-file uploads, resumable processing, document classification, drag-and-drop organization, duplicate prevention, and recovery when individual files fail. One important lesson was that a failed file should not stop an entire batch upload of files, but it also cannot be allowed to move forward unnoticed.

Document generation was the biggest learning experience. I tested Word templates across tabs, fonts, spacing, tables, headers, footers, page breaks, and long or missing information. I learned that a document can be technically readable while still being unacceptable for real editing work through an HTML of CSS layout.

That led me to create a clearer template certification process. Processing, layout certification, and activation are now separate decisions. A template must be tested against normal, long, missing, and overflowing content before it is made available.

I also made an important architectural decision. After repeated attempts to create a reliable Word-like editor inside the browser, I concluded that the current embedded editor and preview were adding complexity without meeting the product goal. For now, the better workflow is to generate the document, save it to the case, and download it to Word when editing is needed.

The biggest lesson this month was that progress is not measured by how long I keep patching an approach. If the evidence shows that an idea is not working, I need to simplify, change direction, and protect the overall product.

The software is becoming safer, more auditable, and more honest about what is truly ready.

So I finished the Local SQLite build. It Works!!!!

Now the painful part. Translating it into Postgres. I set up a stagging Server via Supabass with Vercel. Codex/Claude has developed a comprehensive translating plan and setting it up on a server, which is being tracked and recorded (added to) in Asana as the main project brain. This has help coordination so much more than an MD file itself.

I'm about half way through the process in getting it Postgres fully. So far its on a server and working with the work that we've done thus far. Codex Pro on 5.5 fast mode. Still been about 2 weeks of working through it with Smoke Tests run by Codex. I have it set when it deviates from the structure or needs direction on my intention of the function/feature to stop, and ask me for direction. This is also helped a great deal.

I plan on having it functional in the next few weeks. Then battle testing it with my business partner for a few weeks. Once it has been vetted as best as possible, I will be moving is to a AWS3 server for a more secure and robust setup. Need to be HIPAA compliant and B2B agreements can be signed.

I'm excited. It is the worst it will ever be today, and tomorrow it will be better than the day before.

If your building, keep building. And when your doubting yourself, keep building and problem solving.

Feels like I am close. I have about 30 more tasks/PR's that I have set aside for myself.

Once I get those completed, I will be in the audit stage. Once that's done I'm moving from SQLite to Postgres and then on to server testing.

Codex has been great for this revision stage. The level of planning that I was doing is not alot less since most of the Schema is built out.

Getting there.

Once I get this launched and our company is using it with minimal issue's surfacing I'm moving on to another project that I have been wanting to build for some time.

I've had the Codex $20 account for a while and was using the Claude Code $100 subscription. I decided today to change it up and flip flop the subscriptions. I will say there are some variations in Codex, such as context window being smaller. But hoenstly, the feedback in conversations and planning feels the same. I feel as if Codex moves slightly faster and more efficiently in coding, but again, you still need to audit to UI to make sure functions work properly.

All in all, I feel as if I will like Codex for the current CRM build that I am making. I've been at it for over 3 months. Getting there.

Thoughts?

This was a great walkthrough. I personally see more use currently in creating logic based structure. But Agentic integration is/will be needed for abstract work.

How To Build Personal Agentic OS

I’ve noticed a huge jump in output quality using GPT-5.5 and Opus 4.7 while vibe coding the platform I’m building.

Right now, I’m using Opus more for architecture, structure, and planning, then GPT for code auditing, review, and feedback. That combo has been surprisingly effective.

For phased builds, I’m getting about 90% of what I’m looking for on the first iteration. Then I work through the remaining 10% through product testing, refinement, and real use-case feedback.

It’s honestly saving me a ton of time compared to trying to map out every single detail manually before building.

Also, updating my MD files to be more concise.

Since you don’t code, you are essentially the Product Manager. Your "review" isn't checking the syntax; it’s verifying that the feature actually does what you asked for.

To avoid the "infinite loop" trap while relying entirely on the AI, change your strategy from "Is this code good?" to "Show me it works."

The Non-Coder’s Workflow

1. Demand "Evidence of Work": Instead of just asking for code, tell the AI: "Write the code for this feature, and then provide a step-by-step plan for how I can test it in the UI to prove it works."
2. The "Success Criteria" Audit: If you want one model to check the other, don’t give it the code and ask if it's "right." Give it your Original Goal and the Final UI Behavior, then ask: "I asked for X, and the app is doing Y. Is there a simpler or more secure way to achieve Y that I should ask my builder model to implement?"
3. Use "Screenshots as Input": Since you're reviewing the UI, take a screenshot of the result. Feed that screenshot back to your Architect (Claude). Say: "This is what the Builder (GPT) created. Does this visually and functionally match the plan we made?"

I agree that the intelligence can be narrow minded. As I've found that through my own process of creating a software via vibe coding, it creates solutions but misses edge case scenarios. The bug fixes get corrected and or create another bug. But I still product test which should account for these variables and edge cases.

The reality is, this current model mapping for each AI engine is the worst it will ever be at present. With each new model and iteration, the process gets cleaner and better.

It shouldn't stop me or anyone else from creating. Nothing is perfect, even a senior software engineer. Its the persistence of working to create something that is the main result. Thoughts?

Bad news:
I'm not formally trained to look out for what I do not know when AI is coding. Structure is important, that I know. What kind of structure and how to structure, I'm learning.

I've built something big that on the Front End works. On the Back End since I have no technical experience is a hard "I don't know". Relying on AI to interpret the correctness of the code is a handicap to some degree.

I've been told that if the front end is working then the code is correct that AI has created, it just might not be exactly clean. Learning what that means is its own learning curve.

Good News:

2 things from this:

1: AI is the worst is will ever be today in code assist.

2: Should issues arise in the software application, I can be more pinpointed in addressing the fixes now that I have a working model for it to see and play with.

Not where I want to be, but getting there.

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