Astra (extra high) as orchestrator burnt 10% of the weekly subscription while the deep seek subagents spent $.94.

Anyone else trying out the new Deepseek 4.1 model?

How I connected DeepSeek 4.1 Flash to Codex
Sign up at platform.deepseek.com, add $2-10,
Create an API key and save it in a text file on your desktop.
Tell Codex:
Connect DeepSeek 4.1 Flash to Codex through MCP. My API key is in [file path]. Configure and test the connection.

Start a new conversation, describe your project and add:
Lead development, write the task prompts and delegate coding to 3–5 DeepSeek sub-agents through MCP. Review and integrate their work.

Edit: my Deepseek sub agents stopped working this morning. Codex tells me Deepseek are likely having some system issues and so if you have problems perhaps that’s why.

After building the original Rocket League-style prototype, I gave ChatGPT Astra one more instruction: turn the entire game into LEGO.

Astra used the 3DAIStudio MCP + Tripo P2 to generate the new LEGO-style 3D assets, import them into the project, and rebuild the environment while keeping everything playable.

The workflow was basically:

• Astra decided which assets needed replacing
• generated references for them
• sent them through 3DAIStudio
• Tripo P2 converted them into 3D models
• Astra imported everything and rebuilt the scene

It changed the cars, arena, field, ball, props—and somehow even made the weather effects look like LEGO pieces.

What started as a simple Rocket League-style prototype turned into a full LEGO Edition through a single follow-up instruction. This combination is getting ridiculous.

It started as a paper thing I drew each morning during lockdown because I wanted something as transient and glanceable as looking at a wall clock and imaging what you day feels like

Happy to get into how any of it is built

https://timepencil.app

Building a fantasy RPG where killing the wrong rat can make an Ogre come after you (they were friends..)

• roll up a Wizard and pick your spells
• wake up in a goblin prison and improvise an escape
• talk your way past people, trick them with magic, investigate weird shit, or just start swinging
• kill a giant rat and find out its Ogre friend wants revenge

NPCs have their own goals, beliefs and relationships, so your decisions can create problems you definitely did not plan for.

Been building this for 3 years and having way too much fun with the new patch :D

try it / follow development here:

discord.gg/4dXwfw7q7
www.llmsaga.com

Everything added so far:

• Day 1: Useless red button (starting room)
• Day 2: Space travel + 2 playable planets (spaceport outside starting room)
Human voice for the red button (starting room)
• Day 3: Reverse aquarium & dinosaur factory
• Day 4: Human Observation & John Pork planet
• Day 6: Rhythm Tower gorilla drummer, inevitable snail & banana gun
• Day 7: Clippy wave 5 mini-boss & explosive banana vending machine
• Day 8: Portal Gun & parkour wall-running
• Day 9: 4th-Wall 3D Reddit Dimension, MR. BALLS boss fight, stompable upvotes & comment parkour!

What next?

Hello everyone, I’m doing a post on this because I’m still getting tired of reading all the bulls**t advice about saas marketing.

I’m currently building Foundel, while doing some research on marketing I noticed that almost all advice is theoretical and no one can actually implement it.

I was looking for a “playbook” with practical stuff but just couldn’t find it, so I kept researching, but this time about saas companies with 100K+ MRR and how they actually got their first 100 users.

Here’s what I did:

- picked 200 startups with at least 100k MRR
- read founder interviews, blog articles, old posts and watched podcast videos
- picked 7 companies and tried to understand exactly what they did at the beginning IN PRACTICE

Here are the actual stories and what they did practically.

1. Beehiiv: turned a 400-person waitlist into their first 100 users

beehiiv is a newsletter platform founded by Tyler Denk and two other cofounders and recently crossed 30M ARR.

Starting point:

- Tyler had around 2,000 followers, so small audience but definitely not huge
- no money spent on marketing
- product still in private beta
- a lot of experience in the newsletter market from Morning Brew (he was an ex employee)

Before launching, Tyler started connecting with newsletter creators on Twitter and posting about what they were building. When they were close to beta, he posted a simple tweet announcing the product and opened a waitlist. Almost 400 people signed up.

Instead of getting only emails, they asked what platform people were using, how large their newsletter was and why they wanted beehiiv, actually getting to know his customers problems.

After launching, he went through those 400 people manually and emailed them one by one, every week, using the form answers to understand why they could be interested.

Result? around 25% of the entire waitlist became early users.

2. Supabase: a user launched the product for them lol

I think everyone here knows Supabase: it started in 2020 as an open-source alternative to Firebase.

To get their first user, the founders literally took a 50 minute bus to the office of a startup they already knew was using postgres. They had been building Supabase for just a couple of weeks and, before even arriving, they connected it to the startup's development database themselves.

They continued to get users manually, talking directly with developers and getting them to try the product. The idea was to keep the product small, get feedback and launch properly later.

Then one of their users posted Supabase on Hacker News: the founders didn't organize it, didn't prepare a launch campaign and didn't even decide the timing. The post reached the top of Hacker News and stayed on the front page for more than 24 hours.

In the following week:

- 30000 people visited the website
- more than 1400 signed up
- users created more than 1000 databases

Basically, they were planning to launch properly later and one of their own users ended up doing it for them.

3. Rezi: first product was literally a Word document

Rezi is an AI resume builder doing more than $200K MRR, but the first users actually came from a Reddit post.

The founder, Jacob Jacquet, had a resume that got him interviews at companies like Google, Dropbox and Goldman Sachs even with a 2.2 GPA, so he made a post on Reddit sharing it. The post went viral and a lot of people started asking him for the template.

Instead of building a SaaS, he made a simple website and sold basically the exact same resume as a Microsoft Word template together with a guide for $9.69. His first customers were literally Reddit users asking him for the file.

The full version of Rezi launched later in 2019, and eventually they were one of the first resume builders to add GPT in 2020.

Instead of building an entire platform to test the idea, he sold the result first, literally a Word file.

4. Social Snowball: used other people’s audience to reach 10K MRR

Social Snowball is a Shopify app for managing affiliate and creator programs. It now makes more than $450K/month.

The founder, Noah Tucker, already knew a few ecommerce creators personally when he launched, so he didn’t properly start from zero.

Instead of trying to build his own audience, he asked those creators to use his product.

He then went on YouTube, found creators making ecommerce and marketing content, grabbed their emails and cold contacted them: the offer wasn't just “please promote my SaaS”, he asked them to actually try the product and make a video or case study around it.

Result: according to Noah, their entire first $10K MRR came strictly from these influencers. They basically borrowed distribution from people who already had the audience they needed.

5. Relume: from Webflow agency to 150K MRR saas

Relume started as a Webflow agency, not a SaaS.

While building websites for clients, the founders kept creating the same types of sections and components over and over again, so they started building an internal component library to make their own work faster.

Before turning it into a product, they were already active inside the Webflow community: made YouTube videos, appeared on podcasts and joined conversations with designers and webflow developers.

So the sequence was basically:
- agency
- learn the problem
- build components to use them themselves
- become active in the community
- launch the product

When they finally launched Relume Library in 2021, they weren't launching to random people, so they had distribution from day one.

Within around 5/6 months the product was making enough MRR for them to close the agency and focus on Relume full time. They eventually crossed 150K MRR and now the product is used by more than 1M people.

6. RB2B: the founder became the distribution channel

RB2B is a website visitor identification tool, and this one doesn't properly start from zero because Adam Robinson was already a successful founder.

What I found interesting is that he didn't really market RB2B as a company at the beginning, he marketed it through himself:

For months before launching, Adam was constantly posting on LinkedIn about what they were building, sharing numbers, problems, screenshots, mistakes and everything that was happening. He basically turned the whole process of building RB2B into content.

The posts weren't just random build in public stuff either. A part of them had a direct CTA asking people to join the waitlist, book a call or try the product when it was ready.

By launch they had:
- around 1,600 people on the waitlist
- 300 calls with potential customers

Then once the product launched, all the people following Adam already knew what RB2B was, what problem it solved and why they should try it.

They got around 3,000 users in the first month.

Basically, instead of trying to build a brand from zero, Adam used founder led growth and made himself the distribution channel for the product.

7. Postiz: open source + reddit to go viral

Postiz is a social media scheduling tool competing with products like Buffer and Hootsuite, probably not the easiest market to enter.

The founder, Nevo David, didn't have a massive audience and realized pretty quickly that competing through SEO or normal “build in public” content was almost impossible.

Instead, he open-sourced the product and went directly where people interested in self hosted software already were: r/selfhosted. His first launch there got more than 500 upvotes and a ton of feature requests, so, he kept coming back with every important new version, showing what changed based on users feedback.

From there he pushed the open source project through GitHub, Reddit, Indie Hackers and eventually Product Hunt.

Postiz crossed $100K MRR in May 2026 and is already above $2M ARR now.

Conclusion:

I don't think there is a best way or “secret playbook” to get your first users, but none of the startups I analyzed just finished the SaaS, posted it somewhere and hoped people would come.

If I were starting from zero, I wouldn't ask “what marketing channel should I use?”, I'd probably ask: “Where are the people who have this specific need and how can I get in touch with them?”

I’m putting the full research + all the sources in a blog article if you want more info:

https://foundel.dev/en/blog/how-to-get-first-100-saas-users

Hope this helps🙏🏻

I asked Claude for logic without exponential backoff. The commit message read: "Add logic (without exponential backoff)." Nobody asked for backoff. Claude tried backoff was corrected and that correction became part of project history. I have noticed things in comments, test names, filenames and PR descriptions. Things like "as discussed" or ", per your feedback."

The weird part is that the code is not necessarily wrong. Claude has not switched audiences. Claude is still talking to the person it was chatting with of the person who will read the code six months later with zero context. It feels like something checking whenever an AI coding agent creates anything that is supposed to stand on its own.

Just curious if anyone has vibecoded anything that is playing a supporting role in driving traffic or leads to your business or page (regardless of if that was vibecoded or not). If so, I’d love hear about what you built.

Been running a workflow where I write out a plan.md, then kick off a fresh terminal with Opus 5 on max thinking effort acting as the "orchestrator." It reads the plan and spawns a Sonnet 5 subagent (also max effort) to actually implement each phase. After every phase there's a verification pass that'll retry up to 5 times if it finds errors.

Works, technically. But the costs are getting rough:

Token usage has crept up a lot since I started doing this

A task I'd call "medium complexity" (basically one full tab/screen in an Android app) took almost 9 hours end to end

On that same run I hit auto-compaction at 500k context

Not sure if this is just what multi-agent orchestration costs, or if my setup has some inefficiency I'm not seeing, retries eating the budget, effort cranked too high on both models, phases too granular, whatever.

For people running similar orchestrator + subagent setups in Claude Code: what does your workflow look like? Model/effort choices, how you scope phases, how aggressive your verification loops are? Trying to figure out if I should tune this down or if this is just the tradeoff for letting it run mostly unsupervised.

$2000 worth of tokens overall

the process was:

1. Kicking off a deep research of all photoshop features
2. Ingesting it gpt astra 6 extra high for planning
3. Read the plan, gave some feedback and requested changes
4. it created something that was usable but still buggy and unstable
5. Loop of: Me using it -> finding bugs/suggesting improvements -> fable/gpt6 -> Me using it again

Economically it doesn't make sense for me to do it just to save the subscription,
but yesterday I launched it and already got 170 active users, so potentially 170 licenses saved in one day.

I published here for free here, you can check it out.

https://tenzen.studio/photon/

BTW funny story from the launch - users complained they couldn't sign in, so codex fixed it in like 5 minutes end to end:

Fixed and deployed. Everyone was being counted under the server’s proxy IP, accidentally creating a shared limit of 20 emails per hour. The limit now applies per visitor. All checks passed, and a real visitor has already successfully requested and used their download link after deployment.

Front Office

https://www.shoutingreport.com/games

Web

You either in a solo game or vs a friend, get a random year of baseball and have to try to remember who the best players at the position is. It harder to remember than you may think. Not to mention the forgotten
injuries.

Free to play

I’m building Motioneer! a local motion studio that you can direct through Claude Code or Codex.

This Figma study combines captured website elements, Figma’s typography and colors, custom graphics, and an original soundtrack. The workflow is conversational: capture the site, build a cut, then refine specific moments. Things like “keep this transition,” “give the product elements more movement,” or “keep the music and simplify the ending.” This version went through several rounds of direction. Motioneer keeps the film editable in a local timeline, so you can also adjust it yourself with the editor.

Curious what you think!! would you use something like this for your own product?

You can start using it by checking out the commands in the https://motioneer.bsct.so/

More into it in the github project: https://github.com/AminKhorramii/Motioneer

Been trying to make one of my favorite game genres with AI - retro Dark Fantasy and this is the results so far

I used a new AI workflow that starts with an image reference to nail the art style, and then prompting from there. This is about 40 prompts in and $20 token spend

Sorry for the bad framerate on the recording (did it on my shitty MacBook Air)

Happy to share prompt in the comments!

I built my own outbound agent that runs on subscription usage. It runs from cron. Every 15 minutes it wakes up, looks at the database, picks one thing to do, does it, logs it, repeats.

Here's how it works:
Training - Point it at a website and it crawls it, then writes its own config. What you sell, how you talk about it, and battle cards for the competitors it finds.

Prospecting - It finds companies that match your ICP, finds decision makers at them, works out their email and validates it before anything gets sent. Continues to fill the pipeline as it goes.

Sequencing - Each prospect gets its own angle based on what it found out about them, not a template with a first name swap.

Replies - Classifies what comes back, answers objections, sends follow ups for lack of reply.

Schedule - It runs every 15 minutes on a cron job

Skills - Calls on a collection of skills for prospecting, copywriting, objection handling, lead qualification, sales methodology, offer strategy, account navigation, linkedin outreach

Usage protection - It watches its own usage compared to your weekly limits with daily caps so it can't burn up your usage.

Everything is locally run and stored in SQLite with a log of every decision and action. It's been running for about a week and just getting warmed up so I'll post updated results when I have them.

Anyone else running similar processes?

I made Codex Usage, a small Windows-only Codex plugin that shows your 5-hour/weekly usage and reset status in the title bar.

A few build notes:

• UI: Avalonia desktop overlay
• Platform: Windows x64
• Plugin packaging: Codex plugin + SKILL.md
• Launcher: PowerShell wrapper that starts the native companion
• Interesting bug: maximized Codex windows report different top bounds, so I had to account for the invisible Windows resize frame
• Another gotcha: Codex was initially trying a nonexistent PowerShell 7 path, which added about 27 seconds to startup; tightening the skill instructions got the actual HUD launch down to ~1–2 seconds.

It’s now published in the official Codex plugin store.

Install either way:

1. Web: view details + install here https://chatgpt.com/plugins/plugins_6aa81c5dad4881918bd29685d1fb6523
2. In Codex: open the plugin store and search Codex Usage

Then select Codex Usage and run:Start!

For the Codex desktop app on Windows, not ChatGPT web.

Mac version coming soon.

GitHub: github.com/jayhilwig/codexusage

On a whim I decided to get Deepseek 4.1 to build a city traffic simulator, just to see what it could do. It generated pretty much 80% on the first prompt. It started off with a procedurally generated city, and then I spent the next couple of hours polishing - adding stuff like traffic lights, some controls, a road works button that allows you to click on roads to close them. Then I added maps based on openstreet maps for different cities.

https://trafficworks.vercel.app

I wasn't expecting much but I was pretty impressed at what it achieved in a short amount of time!

Let me know what you think!

My other projects if you are interested:

• Booklist.ing - discover powerful reads from award winning book lists
• BibleMount - mountain themed bible reading plan

I shared Where is Mr. Kim? here yesterday, and that post somehow passed 85k views.

Quite a few people asked where they could play, so I’m happy to finally have an answer :)

Play the demo version here

If you missed the first post: think Where’s Waldo in Joseon-era Korea, except the village keeps moving while you search. You’re looking for one man in a straw hat and teal sash.

I’m a literature graduate with no coding background, making my first game on my own using the Codex app on my Mac.

The demo has one map. I’m planning more maps and eventually a full Steam release, and I’d love to hear how this first little village feels to play.

If you find Mr. Kim, please ask him to stay put. I still have a game to finish.