Miguel Oller

🇩🇴 · 🇵🇷 · 🇺🇸

CTO & co-founder @MakeswiftHQ

[Miguel Oller @ollermi]

It’s fully programmable now 🤩 Here it is adding 18 + 24. Only thing left is to make it Turing complete so it can be a “real” computer. All we need to do that is a conditional jump instruction 🏃🏻‍♂️

[Karri Saarinen @karrisaarinen]

The fallacy of this is that more creates more. More hours, more hiring, more something.

And it is true in a sense. If you put in more work, more work will happen. But I think for most startups, the leverage is really in how differently you approach the problem, how well you cultivate your team, and the strategy.

Any large company can outspend you on hours. They have thousands or tens of thousands more people, spending more hours. If hours worked were the metric, every large company and government organization would always win and do the best work. More hours, better output.

This thinking is often representative of younger founders, where the startup becomes their identity and life. They have a hard time doing anything else, and cannot understand that your work is not the person that is you. But activities outside of work can grow you as a person too and make you do better work.

I’ve never worked this way. As a designer, I always saw the need to take a step back, to take a break. At times, I might work 12 hours or 16 hours, or whatever amount was needed, but it wasn’t the norm. You just can't grind design, you need inspiration. But taking that step away from the work, would give me more perspective, inspiration and I could approach the problem differently or I could just see the solution.

Grinding is never good for any creative problem, and startups or creating new products are often mostly about creative problem solving. Grinding works ok for email jobs, or where you just executing on very clear playbook.

With Linear, we’ve never worked this way. We work reasonable hours, 5 days a week. All of us founders have families. Many of our employees have families. I personally stop every evening, spend time with the family, cook dinner for the family, eat dinner together, and focus on things outside of work. Sometimes I work in the late evenings or weekends, but to me the pride is that I don’t need to. Company should be succesful without it.

My goal is to build a company that is sustainable in the long term, and doesn’t require heroics or personal sacrifices every single day.

There are times when our team is heroic. Launches, incidents, some other work that just needs to be done. They will work late into the night because they know it is the right thing. But we don’t require that every day or every week, and the more this happens, the more I think it is a failure of our company and leadership. The team and the leaders should always keep a reserve to use when something is needed.

Our thinking was also that quality, which we value, doesn’t emerge from working more or stressing people more. It emerges when you create the conditions for it to emerge. Often it is the appreciation, space, time, and how the person feels. A person who is rested will do better work.

I wouldn’t attribute much of our success to working a lot. The success came from having clear thinking, ideas, and focus to do the right things.

I sometimes wish we could move the culture more toward a Zen master.

Real mastery is not exerting the most effort. It is achieving the outcome with the least necessary effort.

[Miguel Oller @ollermi]

@jaredpalmer @Xbox @asha_shar Congrats man!

[Sameen Karim @sameenkarim]

Excited to share our progress on @GitHub Stacked PRs 🥞

[Claude @claudeai]

You can now enable Claude to use your computer to complete tasks.

It opens your apps, navigates your browser, fills in spreadsheets—anything you'd do sitting at your desk.

Research preview in Claude Cowork and Claude Code, macOS only.

[Dillon Mulroy @dillon_mulroy]

and so it begins

[Rhys @RhysSullivan]

if you can read the first one, you can read the second one

[Bun @bunjavascript]

Bun v1.3 is our biggest release yet

[colinhacks/zod @colinhacks]

Introducing Zod 4.1 and its flagship feature: CODECS

z.codec() is a new API for defining *bi-directional transformations* in Zod

[Miguel Oller @ollermi]

@OpenAI Society needs to adapt, fast. We risk having a large group of people fooled by a few wielding these superpowers. Indeed having widespread AI looks more and more as the right solution—knowing what’s possible protects you from being a victim.

[Lee Robinson @leerob]

Last month, I stepped away from my role working on Next.js.

I've been reflecting on that journey and wanted to write down some thoughts on the state of the React community.

https://t.co/vcuNh0F9c1

[Miguel Oller @ollermi]

@shuding Why was the RSC-like protocol necessary? Were transferrable objects, structured clone, and MessageChannel not enough? Had to build something similar at Makeswift but didn’t find the need to build a protocol like this, so curious what inspired it 😁

[Miguel Oller @ollermi]

@jaredpalmer @vercel Good work, man. Excited to see what you do next!

[Matt Pocock @mattpocockuk]

The video you've all been asking for

https://t.co/3zlLTf76Bl

[Andrej Karpathy @karpathy]

+1 for "context engineering" over "prompt engineering".

People associate prompts with short task descriptions you'd give an LLM in your day-to-day use. When in every industrial-strength LLM app, context engineering is the delicate art and science of filling the context window with just the right information for the next step. Science because doing this right involves task descriptions and explanations, few shot examples, RAG, related (possibly multimodal) data, tools, state and history, compacting... Too little or of the wrong form and the LLM doesn't have the right context for optimal performance. Too much or too irrelevant and the LLM costs might go up and performance might come down. Doing this well is highly non-trivial. And art because of the guiding intuition around LLM psychology of people spirits.

On top of context engineering itself, an LLM app has to:
- break up problems just right into control flows
- pack the context windows just right
- dispatch calls to LLMs of the right kind and capability
- handle generation-verification UIUX flows
- a lot more - guardrails, security, evals, parallelism, prefetching, ...

So context engineering is just one small piece of an emerging thick layer of non-trivial software that coordinates individual LLM calls (and a lot more) into full LLM apps. The term "ChatGPT wrapper" is tired and really, really wrong.

[Storm @AndersonAndrue]

As promised, how to generate both client AND server from Effect Schemas. This one's a bit longer today, thank you for your patience, and as always..

Use @EffectTS_ !

[Miguel Oller @ollermi]

@AndersonAndrue This is nice. What’s the best place to explore what’s available in the Effect ecosystem?

[Tsung Xu @tsungxu]

Having no experience did not stop me from making a VTOL with world-class range and flight time, all in 90 days.

This is the thing I'm most proud of building to date!

[Miguel Oller @ollermi]

@rwieruch I wonder if an approach where the action is passed as-is but onSubmit is used, together with preventDefault, to handle progressive enhancement, optimistic updates, and also these event-based side effects can be abstracted in a clean way like this 🤔

I would think probably

[Mitchell Hashimoto @mitchellh]

https://t.co/39Xj39wheA 👻