You can just codex ... a farm
https://t.co/pwmS7IvqbH

Heard that AWS is where the cool kids are. Hello. We have GPT-5.5. https://t.co/TixKoaIS0D

Should we rename Codex to ChadGPT?

Want to try GStack /office-hours for your product idea as quickly as possible? It's one click here:

https://t.co/8g3LJkrV6i https://t.co/YEGSvd445K

"Leadership is presence, not absence." —@bchesky https://t.co/hMnmq6yqxH

Or the new way? https://t.co/aEXYsQ8VdH

CEO: “we have tens of thousands of AI agents running in production at massive scale right now”

CTO: https://t.co/eulDCgxkNQ

my #1 most used skill lol https://t.co/7nAW7T3vDE

You can get a sneek peek into Josh's full skills library here: https://t.co/d7n2UXsw6E

My top 6 takeaways from @Shpigford on how to build multiple products solo with AI agents:

1. Keep shipping even if the fear of embarrassment never goes away.

After 25 years as a solo builder, Josh still thinks "It's terrifying launching something. Every single time it's just like, what if zero people care?" But he ships early anyway: "The idea of spending months working on something before you put it out for other people to use, I think that's a real bad idea."

2. Charge from day one, and kill products that can’t pay for themselves.

For any product with built-in costs (e.g., hosting, LLM), Josh ships a paid version from day one. If the product can't cover its own costs, he doesn't hesitate to shut it down and refund recent payments.

3. Build features in parallel with separate git worktrees

Each worktree is a separate working copy of your codebase on its own branch, so features won't interact with each other. Worktrees stop context rot, isolate mistakes, and force you to test every chunk before moving on. Josh uses @conductor_build to manage them all.

4. Have GPT review Claude's work and vice versa

Josh builds with one model and then runs a review pass with another “GPT invariably finds three to five bugs that Opus overlooked.” Different models spot different mistakes. In Conductor, he sets a default review model so it runs on every PR.

5. Build a skill to make AI better over time.

Josh built a /learnings skill that runs at the end of each phase so that every "no, that didn't work" moment can be distilled into new rules to help the agent avoid repeating the same mistakes.

6. AI lets anyone ship, but real experience still matters.

Josh credits 25 years of building before AI for how fast he ships now with agents. "I know the general shape of how I want things to work, so I can very quickly get to that point." His advice for newer builders is to "just fail a lot, because the only way that you'll ever figure out what not to do is by doing the thing incorrectly."

Josh walked through his entire development workflow in our episode and shared more skills.

📌 Watch the full episode here: https://t.co/9brwr7daw8

As we enter the era of AI agents, one of the defining questions is how you develop competitive advantage when your competitor has access to the same AI models and intelligence as you.

The companies that are able to best harness their internal institutional knowledge, existing data assets, and domain-specific workflows -- connected with AI -- will be those that are able to stay ahead in the future.

Whether a company decides to build out the tech stacks themselves, or leverage a variety of best-in-class tools is certainly one core variable. But the key is to find the way that the enterprise can capture and protect the value created by their unique data, processes, and expertise over the long run. Each industry will have their own version of this, and the competitive advantage will vary by vertical.

We’re increasingly seeing this at Box, where customers want to ensure that they can take advantage of their institutional knowledge and have the flexibility of bringing any AI model and intelligence to their data at any time. This is a pattern that will increasingly become a core principle of strategy in the future.

AWS has massive enterprise traction, with large committed contracts from enterprises. So this partnership opens up both increased distribution for OpenAI’s models, but also likely drives an increase in token consumption overall across model providers. https://t.co/I9XJyDAq9F

it happened! https://t.co/7wi1xkA3co https://t.co/D3PDOwsOJ8

you don't have to work 7 days a week if you just have a swarm of Codex's running on /goal all the time

but you'll probably want to

Suzanne also mentioned she uses this with voice mode to make it easier to respond and more natural.

gist for the full prompt here: https://t.co/L0ffBeU1ua

been asking others at Anthropic how they stay in the loop with Claude and fully understand the work being done

this is one of my favorites from Suzanne: https://t.co/nqIMcGXiKI

vibecon https://t.co/zAqrtrfd1k

Prompt to business:

• website
• mobile app
• monetization
• Delaware corp

Start for free: https://t.co/r3LEz2slaT

walk in the park part II (feat. @taiuti).. coming soon 👀 https://t.co/57WdrRvICw

All you had to do to make life changing wealth was to invest in ~every public company along the 237 https://t.co/SDEx6JE3P7

Schrep and the Gigascale team are building something special.

They have been incredible partners to @southpkcommons portfolio companies.

@schrep is someone who I have looked up to for a long time and I am very excited to continue to collaborate with him. https://t.co/Jo3bZ5So5A

@xai @imagine see more about flipbook from @zan2434 and @eddiejiao_obj !

https://t.co/WHwtYQ3WWF

title undersells it - this @workos talk is doing v well and is the first to seriously challenge @mattpocockuk in weeks. team is ab testing https://t.co/puwZ8bKPH3 https://t.co/rRWOfwqjjq

@Microsoft @nvidia roundup of links: https://t.co/52cazFXk1f