I read the DevDay dump so you don’t have to.
• GPT-6.1 Sol: better coding/agents, much cheaper than Astra
• Astra Ultrafast: same model, way faster
• Dots: persistent agents with their own cloud computers
• Codex: parallel agents, cloud envs, auto reviews. Closer to an actual engineer
• ChatGPT Space: projects, context, and work stay in one place
• Pages/Slides + plugins: now feel like real apps, not chat add-ons
• Slack/Teams + meeting agents: it joins chats, takes notes, does follow-up
• $500/mo Pro: Ultrafast + higher limits
That’s the stuff that actually matters.
Tom Lee retweeted
Easiest SEO Keyword Optimization in the universe
(takes 2-5 minutes)
> Open GSC = Google Search Console
> Click the "Pages" Tab
> Order by Most Impressions
> Click Queries Tab
> Check Avg Queries' Position
> If close to 1: Add missing query to the page
> Done!
Repeat over, and over, and over until you are kig or queen of the world.
No one is more productive then when @thsottiaux announces a reset at a unspecified time. This should be studied.
A must do for all new sol models
At the top of my AGENTS.md:
- NEVER write unit tests after you write code.
- Highly prefer E2E tests as the sole testing mechanism. Use them to verify complex features work. At the end of E2E tests, produce a verifiable and repeatable artifact.
- If you must test a system in isolation, FIRST write all the ways it could fail, THEN write the code.
Benchmarks GPT-6 Sol & Luna:
• FrontierCode: 48.4% vs. Fable 5.1’s 48.7%, both at xhigh. $1.37 vs. $9.27 per task, roughly 85% cheaper.
• DeepSWE: 68.8% at max vs. Fable 5’s best result of 69.9% at xhigh. $2.74 vs. $13.41 per task, roughly 80% cheaper.
• AutomationBench: 33.2% at xhigh vs. Fable 5.1 with Opus 5 fallback at 31.4% on max. $0.27 vs. at least $2.45 per task.
GPT-6 Luna:
• DeepSWE: 66.6% at max vs. Fable 5’s 65.4% at medium. $0.22 vs. $6.09 per task, roughly 96% cheaper.
API pricing per million input/output tokens:
• Sol: $2 / $10
• Luna: $0.10 / $0.50
Tom Lee retweeted
My little SaaS, DataFa.st, just reached $30K MRR 🎉
It took 2 years, and I've never done real marketing.
I don't do SEO. I don't run ads. I don't do sponsorships.
My "audience" got me the first $300 MRR.
The rest is word of mouth.
I have a weird obsession with building features that make my users happy.
Sometimes it flops.
Sometimes they like it.
They share it on social media.
And new users discover the product.
So I wanted to thank the 1,387 paying customers who use my product every day.
I wouldn't be here without you.
Thank you ❤️
Tom Lee retweeted
The most interesting part of this is the monetisation strategy
It looks like an outrank bid type deal but for scenes within the game
Which is smart… if that’s what he’s doing
Because a game that goes viral needs to have immediate monetisation scalability (if that’s even a saying)
If you lock in to the old model someone would pay for an ad spot for a month and lock your viral game doing 1mil views into $200 of sponsorship
But with a bid system you are incentivised to build games that go instantly viral, get immediate attention, and monetize it straight away.
You could release a game and generate $10k overnight easily. Maybe more.
Aaaaaaand we're live!
diiverge.co
A persistent, infinite, point-and-click adventure.
Every picture is a fork. Click something in it, decide what happens, and the world grows in that direction.
Tom Lee retweeted
Memory Skill for OpenClaw with 26k+ users in 1 week🚀
OpenClaw's memory system is broken by default.
It requires curating massive MEMORY.md files or relying on duplicate-heavy generation. Hours are wasted tuning, and massive amounts of tokens are burned.
It's time to stop. So we built the memory skill to solve that prob
Here is our superpower ⚔️
🎯 Top #1 market accuracy (92.19%) after 8+ months of intense architecture iteration
🧠 The ultimate solution to keep the timeline, facts, and meaning perfectly in place
☁️ Local & Cloud + Version control
⚡ Super easy setup