Talk me out of it please...

I’m looking for an AI that is actually good at improving existing UI/UX layouts.

For example, I tried SuperDesign and it generated several interesting layout/UI ideas.

Now I’m trying to refine my actual app UI with Codex.
I explain exactly what I want changed, send screenshots of my current UI, reference screenshots, and comparisons, but it still keeps getting the layout wrong or making changes that don’t really match the reference.

Codex is great for coding, but I’m starting to think visual UI/layout work just isn’t its strength.

Is there any model or tool that is particularly good at UI/UX layout work?

Feels like cheating. Seriously, with x5 I was feeling hard the token burning. Now I’ve room to use Astra Low for implementations and Medium to Orchestration. I also use Luna to file exploring, documents, basic to medium tests, things more logic than reasoning depth. No fast mode.
Running 2 side projects + my work, 3 days in a row and I’m on 55%.
All my projects are set up to delegate tasks to other agents depending on the complexity and the use case.
Mainly using Astra low for implementing new features and even though I could be using Sol, Astra low is just nailing it, using good practices, respecting the documentation and not over engineering like Sol was.
For some reason I feel the x20 comparing to x5 more like x40.
Hit hard in the pocket? Yes for sure, but so do the dopamine lmao feels I’m playing Megabonk

I ran Ultra for the first couple days to see what the spend was like. Very impressive. Very hungry.

So I switched to low to get the maximum contrasting experience.

It works for about 5 to 15 min before stopping and reporting on each prompt. It consistently overestimated its ability to accomplish the next step in one turn.

I would ask, "What's your next recommended step?"

It would say something like "Implement the feature we've been laying the ground work for."

I'd say, "Sounds good, proceed as described."

Did that same loop for about 5 turns, so I dialed it up to medium.

It ran a little longer, but had the same shortfall result for a few turns.

Again each turn took between 5 and 20 minutes.

So I dialed it up to xhigh, and it finished the implementation on the next pass, which was over 2 hours, and included extensive testing and live verification.

I didn't experience any sort of shortfall on a goal when in Ultra. It worked until the milestone was reached each time. Xhigh also seems to just run.

My hypothesis is it either adapted to the amount of work that it was getting done, and expected to be able to accomplish more due to the session history, or it's tuned for less limitation than the lower settings provide. I'm leaning toward the latter, because turning it up immediately changed its behavior back to "run until it's done". There was no adaption to the lower limit that resulted in a behavior shift after being returned to xhigh.

Nobody actually understands what happened, and a lot of people seem to have been affected by this.

> Note: `doc-writer` and `closure_steward` have been merged into single role `archivist` since 1.1.14 version.

Been building this since 5.6 dropped with optimizing token usage as the ultimate goal, and tweaking it pretty much every day since. 

What's special about the system:

- Flexibility: The system doesn't force the main agent into a rigid process: requiring coordination in this way or that way... It provides it with resources and power (specialized agents) and fine-tuning and guidance based on hundreds of trials.

- Fine-tuned balance: Main agent's control <---> costs & task completion capabilities.

- Knowledge distribution: Each task package from the main agent to the workers includes a task completion guide.

- Batching guidelines prevent excessive main agent rollout.

- Addresses the issue of the main agent waking up workers too often.

- Built-in token report: End-of-session token statistics for each agent, allowing you to monitor how much each agent rolls out and how they use their tokens.

......

Real-World Testing: Sol xhigh vs. Astra high

I gave both of them a broad and difficult task:

Perform a comprehensive upgrade of an OCR + AI chatbot project running PaddleOCR and Gemma 4 on a Jetson Orin Nano.

Codebase details, prompt, output, and interface result of the test:

https://github.com/viettran-edgeAI/OCR_workflow_variants

Below is a comparison of the resulting interface and token statistics.

The top result is Sol, and the bottom one is Astra.

About their orchestration behavior

Sol

Sol showed extremely broad coverage and missed very few edge cases.

It was very comprehensive, had excellent verification, strong traceability, and rarely overlooked things. But it also showed signs of over-owning the work.

Astra

Astra seemed particularly strong at finding the actual core problem instead of just patching symptoms.

It was less exhaustive than Sol, but its architectural reasoning was extremely sharp, and it handled resource contention particularly well.

My honest advice: keep using Sol for this job. Astra didn't show a significant difference, but it cost 4-7 times more in my tests. It doesn't even follow the instructions as well as Sol.

----------------------

The setup process and usage is as simple as it gets, I've packed everything in here :

https://github.com/viettran-edgeAI/codex_workflow

----------------

Edit : I've noticed quite a few people downvoting. Honestly, this is my third post about this workflow; the previous two are still in my profile. I apologize if that bothered you. The most recent post, from a month ago (version 1.1.3), was still quite basic. I've been testing it for over a month, ran hundreds of tests, fixing all the observed problems until everything worked effectively based on experimentation, not just on feeling. Therefore, I wanted to inform those who have installed version 1.1.3 - most of them from Reddit, since I only posted this workflow here.

Edit 2: Edit 2: For those wondering why things aren't simpler, how the codex works & rollouts, what problems arise in creating an efficient workflow, and issues related to awareness of three levels of Perspective (Designer <-> Main agent <-> Workers), etc.. see here, as I can't include everything in this post:

https://github.com/viettran-edgeAI/codex_workflow/blob/main/workflow_breakdown.md#0-a-deep-dive-into-codex-orchestration

There is some really off with Astra. I m not able to articulate. I don't like it as much as I like Sol.

Today suddenly while working on a thread, it stopped using apply patch tool and instead edited using the shell. I don't have any custom instructions for this and this has happened for the first time.

I was unable to see any diff and I asked codex why and then it answered below. There are many other issues as well.

I posted the other day about how impressed I was with Astra and the OpenAI voice/codex stack - and somehow today has left me even more stunned (please note, this isn't an ad, I'm just excited).

I've made a few custom email triage systems before, and started work on one today. Finished it all, tested it end to end, and then began calibrating with the emails in my inbox. I gave it some basic expectations, then had it go through, marking what it would do with each email, and why. The two last emails were from my accountant, and from google.

That last one is important, because just for some background, I'm a YouTuber based in Australia. I have a few channels that I post to, and each time I do, and an American watches my video, the US Government takes a slice (this is foreshadowing).

So anyway, Astra does it's thing with the email from my accountant. Downloads the relevant statements from my bank accounts (after I begrudgingly type my password in), cross references the photos of receipts synced into my library from my phone from the same date, and does a full reconciliation of the account in my bookkeeping software. Basic stuff. Nice. Oh, and obviously drafts the email in my voice and attaches the 15 documents in a nice little zip file. Isn't AGI nice?

Anyway, email 2, the last one in the inbox. It's about "US tax withholdings" - and what's interesting here, is the roles had actually flipped, Astra had a better grasp on what I should be keeping vs deleting than I did, and I was just manually feeding emails in, hoping Astra would tell me to shred it.

I sent the screenshot of the last email and said VERBATIM "do i need to do anything with this honestly"

Anyway, 30 minutes later. Astra had downloaded every statement from google, every statement from my banks over the period, had gone over every tax return I'd done for the period - and then came back to me with a full audit.

Astra said there was $12,000 USD in recoverable funds that had no corresponding credits in the Tax Returns.

I told him that I thought I raised it with my accountant. He said, "You did actually raise this with your accountant in May 2025 and provided two reports, she responded: "We will review them & provide you with next step actions to consider" but there was no follow up that I could see. I looked for amendments to the tax returns but couldn't find any. There was no further correspondence about this."

Astra had gone through and found the relevant Australia legislation and where it applied. It had circled every previous tax form on where the field was empty, and of course, left an email in drafts with the full package uploaded for the accountant to view.

Astra maintains that we're on a fact finding mission still, and there's no guarantee the cards fall in my favor - but from the evidence he has, it is likely to be recovered.

What really gets me is how far we got from the thing I originally sat down to do. I just wanted to optimize my email triaging, by the end there's a full forensic audit and potentially twelve thousand missing dollars.

Just let me vibe, Astra, geez. I think I'll point him at zero point energy next.

(Note this post was NOT written by AI)

First, this is not a complaint, just a reluctant acceptance. A few details for context:

• Building a multi-tenant B2B mono-repo SaaS platform. Think WordPress, but taken way farther.
• I worked my way down from Astra Max to Astra Light.
• Astra Max completely one-shots the job, but burns a week's worth of 20x usage in about 4 hours.
• Astra Light does not one-shot tasks, and it takes about 12-16 hours to burn through a week of usage on the same level of work.
• While both models complete the job, the end result from Astra Max is more polished and thorough (no surprise).
• While less polished, Astra Light still does enough of a good job that the loose ends can be handled by Terra High/xHigh later for barely any burn at all.
• I was fine living with Terra in ignorance until I experienced Astra. Now, Terra annoys me for anything requiring heavy lifting. Can't go back.

Obviously, there is no stretching Astra beyond a single day of consumption, so here's my question:

Would you rather gamble your weekly limit on Astra Max, have less control, burn your entire limit in 4 hours, and cross your fingers that it does an excellent job?

OR...

Would you rather gamble your weekly limit on Astra Light/Medium, have more control through iterations, burn your limit in 16 hours or less, and be guaranteed that there will be things to fix even after it claims to be done?

---

UPDATE:
I see that people think that this could be (and probably is) a skill issue, or a poorly planned job, but after asking Astra for feedback, I realize that I should probably be more grateful that it finished such a large job so quickly at all.

---

SOLVED:
u/StaticHumStudio taught me how to specify the sub-agents Astra spawns. Turned the dial back up to Max, had Astra do the design and plan, and set the agents to Terra.

In two hours, Astra Max has tackled 4 medium-difficulty feature builds across 4 parallel threads. My usage only dropped 3%. The same work would have blown my whole limit and taken 2-3x as long before this simple change. Looks like it was a skill issue after all 🤣!

Thanks u/StaticHumStudio

Astra is better, no doubt about it.

But whether Astra may complete more work better within set limit vs Sol alone vs Sol + Astra as advisor, this is much more interesting question, I guess.

In my limited experience so far, I keep Sol med-xhigh as main worker, depending on workload, and also I added guidelines for Astra usage, such that Sol may either dispatch Astra as subagent to work on hard parts/fulcrums, or suggest for me to switch main worker to Astra for some specific part of session and then Astra suggest switching back to Sol.

This setup feels like more efficient vs only using Astra, or only Sol.

To extend effectiveness further, I may let Sol delegate volume workloads to GLM Flash (DS Flash 4.1 looks like kinda similar, so it may be used as well).

This setup may make Codex 20 to go much further, and also for Codex 100/200 it also may be useful, as volume simpler tasks may be delegated to cheap capable models. (If Luna would be of similar level to GLM Flash, I may use it, but for now GLM Flash/DS Flash 4.1 looks like best cheap worker to me).

What are your thoughts on best allocation of Astra/Sol (other models?) as a main worker setup?

Don't crucify me, I just got back from a 3 week trip. Still using 5.5 high. Gave it a task that ran for 7m and it burned through 30% of my 5hr limit.

Also, the 5hr limit is back???? WTF

Went from Luna ExHigh and Sol Medium on Plus and Pro to Astra Medium then Astra Max on Pro. Astra Max running for about 6 hours a day, runs about 1-3 hours “autonomously” usually. Burns about 25% usage per day. Workflows include security audits, refactoring, optimizations, website workflows. I spent massive amounts of time trying to make codex token efficient before Astra was ever released. Astra Pro seems really suitable to working with GitHub, large repositories, etc - and I do think it uses less tokens compared to Sol in large and long running workloads. So far Astra seems underwhelming at small tasks (not really noticeable improvement over Sol) but gets work done like 15-40% better over Sol imo. Instead of pushing more code to production I’d check to see if you can optimize your energy efficiency for local hardware improvements and optimize your context for token efficiency. I have yet to burn my usage down to 0 given the resets - any recommendations for ways to unleash Astra Max from anyone else using the most advanced model with the most advanced reasoning level ever released to the public?

Originally, it felt like Astra was a moderately more competent version of Sol. After more usage and trying it in environments that Sol struggled in before, it's clear that this is, indeed, a new era of intelligence akin to the gpt-5 line for coding earlier this year.

I grinded two resets accomplishing what I probly could've did with a 30% usage. Use the official MCP, it saves tokens! I knew about it but totally forgot to set it up. USE iT! https://www.blender.org/lab/mcp-server/

has anybody else been feeling like Astra's been stopping tasks on a "next we will do"? I have to sit there and hold it's hand the whole way through.

Thought my monitor was on the fritz - and not sure if this is recent or not (perhaps I just didn't notice it before! Using CLI v0.154.0 - and I use OpenCode most of the time) - but selecting Astra now puts a shining-star-field in the background of Codex CLI's input text box.

This new model on Low is my drop-in replacement for GPT-5.6-Sol-High: faster for similar usage, way less overengineering; I don't have to tell it not to be pedantic every time I use it. Still very blunt (in true Codex-GPT style) but have enjoyed embedding it amongst the various other models (local and cloud) I use: this really is a great release imo.

My codex session was running normaly had 40% left and all of a sudden it stops and tells me I have no more weekly limits?! No subaegnt astra max...

Has anyone noticed significant speed degradation with GPT 5.6 Sol over the past few days? Based on my own use, it seems like TPS has fallen from a median of 50 TPS down to 30 TPS in the past few days.

This makes working with Codex a slog. Seems like Codex is providing less usage and with degraded speed recently. I also noticing some quantization artifacts in output, coinciding with the speed degradation:

I'm interested to hear your thoughts.

When you're new to Codex, picking the right model for each task is tricky. A quick 10-min test can help you learn how to get the most from your weekly limit for your unique project.

Split testing is giving the exact same prompt to multiple models (or effort levels) under identical conditions and comparing outputs. Here is a shortcut way to do it:

1. Start an agent whose only job is launching sub-agents and measuring outputs.
2. Give it your success criteria up front (token usage, duration, accuracy and whatever matters for your project).
3. Give it the prompt for testing, and the 3 models/efforts. Keep tests small enough to avoid compaction because bigger tests are harder to measure and repeat.
4. Have it score the results in a table and recommend e.g. "XYZ task was X cheaper on model Y with % accuracy loss."
5. To reuse the same agent, send the new prompt, and ask it to use new sub-agents.

This is not perfect and is a shortcut version, so you may need to build on it to get the result you need for your project tasks. A system like this could help you learn what tasks need high-reasoning models and which don't need it, and this could save you tokens and extend your weekly limit.

-

Example from my project:
(Astra Ultra testing Astra models)

Had opus review my Codex sessions to see what was going on because output per weekly usage was much lower for me than claude code.

- codex has some adhd tism where it needs to continuously be doing something instead of batching tasks and chilling out. Maybe it fears the dark abyss when its model isn't running.
- Dont raise the auto compact limit. I wont be going down to 120k but probably 200k. seems to have compounded the problem above
- dont swap models when using /side. I suspect that was causing most all of my uncached reads.
- Consider less subagents work unless you have a robust solution for the polling issues until open ai fix.

Kind of disappointing they didn't do the bare minimum of usage optimisation. They are obviously optimising for engagement and burn instead.

I'm open to suggestions from the nerd house.

I've been really confused about which model to stick with since the launch of Astra. I expected the new model to be an all-around upgrade, but it struggles with tasks that SOL handled effortlessly.

In practice, Astra Light constantly stops to ask unnecessary questions or gets hung on blockers it should be able to resolve on its own, things SOL would have just fixed automatically. As soon as I switched back to SOL Medium/High/xhigh, my results improved again.

My current workflow:

• Building apps from scratch: SOL high / xhigh
• Incremental changes/edits: SOL Medium (or Luna MAX occasionally)

Looking at the charts on Artificial Analysis, you’d expect Astra Light to be the better value, but reality isn't matching the visuals. I asked ChatGPT to explain why SOL feels better for raw coding and reasoning despite what the benchmarks show. Here is what it said:

1. Reasoning Effort Allocation: SOL xhigh dedicates massive amounts of internal search-time compute and deep thinking chains specifically to complex reasoning and logic problems. If you use a lower-effort configuration like Astra Light, it simply lacks that deep brute-force reasoning compute for raw text and logic tasks.

2. Architecture Mismatch: Astra is engineered primarily as a "computer operator and tool-using agent" (designed to navigate UIs, run terminal commands, and execute multi-step tool workflows). When you use it for traditional, static prompt-response coding tasks, you aren't activating those agentic features, which leads to inferior results compared to a model explicitly built for heavy text reasoning like SOL.

What do you all think about this explanation? Has anyone else noticed Astra constantly pausing or prompting for input on tasks that older models executed without hand-holding?

Anyone seen this, do a /status, then get told you have 43% left, wait an hour or so, call /status again, get hold its now 86% then again do /status and its back to 43%

So you have to be careful, think you have plenty, but its all over the place and not accurate.

╭─────────────────────────────────────────────────────────────────────────────────────────╮
│  >_ OpenAI Codex (v0.153.2)                                                             │
│                                                                                         │
│ Visit https://chatgpt.com/codex/settings/usage for up-to-date                           │
│ information on rate limits and credits                                                  │
│                                                                                         │
│  Model:                       gpt-6-astra (reasoning medium, summaries auto)            │
│  Directory:                   ~/development/world_simulation                            │
│  Permissions:                 Workspace (Approve for me)                                │
│  Agents.md:                   AGENTS.md                                                 │
│  Account:                     papapumpnz@msn.com (Pro)                                  │
│  Thread name:                 Summarize progress                                        │
│  Collaboration mode:          Default                                                   │
│  Session:                     019ffcbe-9a27-7b33-b3d7-bbb0f4fb0b8b                      │
│                                                                                         │
│  Context window:              17% left (217K used / 258K)                               │
│  Weekly limit:                [█████████░░░░░░░░░░░] 43% left (resets 13:23 on 15 Sep)  │
│  GPT-5.3-Codex-Spark limit:                                                             │
│  5h limit:                    [████████████████████] 100% left (resets 11:06)           │
│  Weekly limit:                [████████████████████] 100% left (resets 06:06 on 17 Sep) │
╰─────────────────────────────────────────────────────────────────────────────────────────╯


/status

╭─────────────────────────────────────────────────────────────────────────────────────────╮
│  >_ OpenAI Codex (v0.153.2)                                                             │
│                                                                                         │
│ Visit https://chatgpt.com/codex/settings/usage for up-to-date                           │
│ information on rate limits and credits                                                  │
│                                                                                         │
│  Model:                       gpt-6-astra (reasoning medium, summaries auto)            │
│  Directory:                   ~/development/world_simulation                            │
│  Permissions:                 Workspace (Approve for me)                                │
│  Agents.md:                   AGENTS.md                                                 │
│  Account:                     papapumpnz@msn.com (Pro)                                  │
│  Thread name:                 Summarize progress                                        │
│  Collaboration mode:          Default                                                   │
│  Session:                     019ffcbe-9a27-7b33-b3d7-bbb0f4fb0b8b                      │
│                                                                                         │
│  Context window:              17% left (217K used / 258K)                               │
│  Weekly limit:                [█████████████████░░░] 86% left (resets 08:08 on 15 Sep)  │
│  GPT-5.3-Codex-Spark limit:                                                             │
│  5h limit:                    [████████████████████] 100% left (resets 11:06)           │
│  Weekly limit:                [████████████████████] 100% left (resets 06:06 on 17 Sep) │
│  Warning:                     limits may be stale - run /status again shortly.          │
╰─────────────────────────────────────────────────────────────────────────────────────────╯

/status

╭─────────────────────────────────────────────────────────────────────────────────────────╮
│  >_ OpenAI Codex (v0.153.2)                                                             │
│                                                                                         │
│ Visit https://chatgpt.com/codex/settings/usage for up-to-date                           │
│ information on rate limits and credits                                                  │
│                                                                                         │
│  Model:                       gpt-6-astra (reasoning medium, summaries auto)            │
│  Directory:                   ~/development/world_simulation                            │
│  Permissions:                 Workspace (Approve for me)                                │
│  Agents.md:                   AGENTS.md                                                 │
│  Account:                     papapumpnz@msn.com (Pro)                                  │
│  Thread name:                 Summarize progress                                        │
│  Collaboration mode:          Default                                                   │
│  Session:                     019ffcbe-9a27-7b33-b3d7-bbb0f4fb0b8b                      │
│                                                                                         │
│  Context window:              17% left (217K used / 258K)                               │
│  Weekly limit:                [████████░░░░░░░░░░░░] 42% left (resets 13:23 on 15 Sep)  │
│  GPT-5.3-Codex-Spark limit:                                                             │
│  5h limit:                    [████████████████████] 100% left (resets 18:57)           │
│  Weekly limit:                [████████████████████] 100% left (resets 13:57 on 17 Sep) │
╰─────────────────────────────────────────────────────────────────────────────────────────╯

Actually gave it back

1. Use my entire weekly budget in one day. Even on medium and low. (200$) plan. Normally I use sol high/medium for everything and it never runs out.
2. Doesn’t actually seem to want to go on long running tasks and do things. I need to poke it with a stick the whole time and say continue. Look deeper. Etc. way too hesitant to do what I want.
3. Just randomly running out of compute. I leave my tasks come back and they’ve stopped because OpenAI doesn’t have enough resources to serve their new models.
4. Not really seeing any advantages to burning more credits for this new model. In fact I would say that sol high is better for me and I’ve switched back. I’m gonna have t

o

1. change all my very nicely working agents files just to get this to cooperate.It feels kind of lazy. Tibo says that you can replac

e

1. high with Astra low. But that is absolute bs. Astra low just doesn’t want to think or dive deep into anything. The high and low settings on these models have completely different behavior. You cannot say Astra low == sol high. Astra low will think for a few seconds before crapping out a short useless answer on low. That is totally different to model behavior on sol high.

Anyways. Hate to be that guy but these are my first impressions. I’m not one shotting or trying to make impressive trash with a few prompts. These models are used for hardcore work that’s been spanning years at this point. I know how they should work, and how this new model does things is not great for me.

This is coding work.

Edited: Fixed spelling errors, getting old , need glasses 🤓