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I’ve had decent luck with Termius because it gives you a row of keyboard shortcuts above the usual keyboard. Still cramped, but it works.
Tmux is annoying with a mobile keyboard, so I vibe coded a little mobile-friendly wrapper https://github.com/zakandrewking/pocketbot
Someone is going to solve this with a non-buggy app, but it really needs to have all the features of Claude code. Everyone is a power user in this segment
The other day I asked chatgpt (o3) to help me compare a bunch of task orchestration systems and arrange them according to some variables I care about (popularity, feature richness, durability, whether can be self-hosted, etc.). I ended up using https://www.inngest.com/ -- which was new to me -- and that single tool sped up my particular task by at least 10x for the week. That was a one-off project, so it won't generalize in a clean way, but I keep finding individual cases where the particular strengths of LLMs can save me a whole bunch of time. (another example: creating and evaluating responses to technical interview questions). I don't expect that these are easy to quantify, but they are significant.
This is not to disagree with the OP, but to point out that, even for engineers, the speedups might not appear where you expect. [EDIT I see like 4 other comments making the same point :)]
I'm impressed by the product design here. A non-ai-expert could find this mode extremely valuable, and all openai had to do was tinker with the prompt and add a nice button (relatedly, you could have had this all along by prompting the model yourself). Sure, it's easy for competitors to copy, but still a nice little addition.
My coding flow today involves a lot of asking an LLM to generate code (blue team) and then me code reviewing, rewriting, and making it scalable (red team?). The analogy breaks down, because I'm providing the safety and correctness; LLMs are offering a head start.
I'm optimistic about AI-powered infra & monitoring tools. When I have a long dump of system logs that I don't understand, LLMs help immensely. But then it's my job to finalize the analysis and make sure whatever debugging comes next is a good use of time. So not quite red team/blue team in that case either.
This reminds me of one of my favorite books from a few decades ago: Websites that Suck http://www.webpagesthatsuck.com/ That might have been what turned me on to web design, and I'm still trying to make things that don't suck
I remember bookmarking gwern's GPT-3 Creative Fiction [https://gwern.net/gpt-3] sometime in late 2020. It's a labyrinthine article that was a bit confusing to work through: What here is written by a human? Is a neural network really writing poetry? Whatever you think about the impacts of LLM into the future (regarding AGI, etc), it's jarring to look back just five years. We each have a sense of what we expect to experience when we interact with digital computers, and the envelope of possible experiences has simply exploded.
Delfina [https://delfina.com] | Software engineers (data/backend) | ONSITE (hybrid) | SF
Delfina provides a leading pregnancy care data platform to improve maternal and child health outcomes. Our motivating challenge is the fact that in the United States, healthcare outcomes for pregnancy are significantly worse than in other similarly developed countries. We believe our technology-enabled solutions will help doctors better scale to better use data and in the end, deliver better care to their patients. We are looking for people who believe in our mission to join our team!
We are looking for both junior and mid level backend software engineers. It will help if you experience with: Python, Postgres, GCP, Beam, Spark, dbt, BigQuery, or similar Experience in healthtech, pregnancy care, machine learning, and design are all valuable as well.
Find the posting here, which include some details on comp & benefits:
Sorry you didn’t hear back! We aren’t able to reply to all the applications we get. This is an updated job description for the same opening.
Delfina [https://delfina.com] | Software engineers (data/backend) | ONSITE (hybrid) | NYC, SF
Delfina provides a leading pregnancy care data platform to improve maternal and child health outcomes. Our motivating challenge is the fact that in the United States, healthcare outcomes for pregnancy are significantly worse than in other similarly developed countries. We believe our technology-enabled solutions will help doctors better scale to better use data and in the end, deliver better care to their patients. We are looking for people who believe in our mission to join our team!
We are looking for both junior and mid level backend software engineers. It will help if you experience with: Python, Postgres, GCP, Beam, Spark, dbt, BigQuery, or similar
Experience in healthtech, pregnancy care, machine learning, and design are all valuable as well!
Find the posting here, which include some details on comp & benefits:
yup, we have 2 roles open
Delfina [https://delfina.com] | Software engineers (data, full stack, backend, devops) | ONSITE (hybrid) | NYC, SF, Seattle, Boston
Delfina provides a leading pregnancy care data platform to improve maternal and child health outcomes. Our motivating challenge is the fact that in the United States, healthcare outcomes for pregnancy are significantly worse than in other similarly developed countries. We believe our technology-enabled solutions will help doctors better scale to better use data and in the end, deliver better care to their patients. We are looking for people who believe in our mission to join our team!
We are looking for both junior and mid level software engineers. And we’re open to backend, frontend, or fullstack positions. It will help if you experience in one or more of:
- React, Python (FastAPI) - PostreSQL, GraphQL - GCP, GitHub Actions - Beam, Spark, dbt, BigQuery
Experience in healthtech, pregnancy care, machine learning, and design are all valuable as well!
See all four postings here, which include some details on comp & benefits:
Congrats Dima & Colin! We’ve been greatly impressed with Metriport. If there was ever a place that needs tons of well-designed & open-source software, it’s medical records.
Delfina | Data Engineering Lead | $150k-170k + equity | NYC ONSITE
We’re looking for an experienced data engineer to help us build the apps and systems that run Delfina Care, our intelligent pregnancy care platform. Delfina is a fast moving startup, and we have an incredible team of engineers building an integrated, ML-driven platform to make every pregnancy safer.
As the leader of Data Engineering, you'll play a crucial role in building and maintaining the data infrastructure that powers our innovative solutions. You'll be a key player in shaping the future of our data platform, ensuring its scalability, performance, and security as we grow. You will be a crucial part of our talented engineering team. You will work in person with the Chief Scientific Officer and data science teams to support them as they seamlessly deploy their cutting edge models, while being a crucial part of our talented engineering team.
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thanks, i'm really enjoying that paper
How would you handle schema migrations in a system like this?
Yeah, I guess I was heading in that direction with the last point. Earth organisms have a separation between lifetime learning (brain modification) and genetic evolution, but, for AGI, these could be combined into one, or further separated into three or more methods of goal-directed modification.
Makes sense!
I like the process that goes into these "imagine the architecture of AGI" articles. It's all hypothetical, but it's really fun.
But it's a missed opportunity if you don't embed LLMs in some of the core modules -- and highlight where they excel. LLMs aren't identical to any part of the human brain, but they do a remarkable job of emulating elements of human cognition: language, obviously, but also many types of reasoning and idea exploration.
Where LLMs fail is in lookup, memory, and learning. But we've all seen how easy it is to extend them with RAG architectures.
My personal, non-scientific prediction for the basic modules of AGI are:
- LLMs to do basic reasoning
- a scheduling system that runs planning and execution tasks
- sensory events that can kick off reasoning, but with clever filters and shortcuts
- short term memory to augment and improve reasoning
- tools (calculators etc.) for common tasks
- a flexible and well _designed_ memory system -- much iteration required to get this right, and i don't see a lot of work being done on it, which is interesting
- finally, a truly general intelligence would have the capability to mutate many of the above elements based on learning (LLM weights, scheduling parameters, sensory filters, and memory configurations). But not everything needs to be mutable. many elements of human cognition are probably immutable as well.
Delfina | $65,000 - $170,000 | Full time | SF or Remote | Senior Software Engineer
We’re looking for an experienced frontend software engineer to help us build the apps and systems that run Delfina Care, our intelligent pregnancy care platform. Delfina is a fast moving startup, and we have an incredible team of engineers building an integrated, ML-driven platform to make every pregnancy safer.
In this role, you will be the technical lead for our frontend development team. You will contribute directly to our codebase as a developer. And you will provide technical guidance, mentorship, and feedback to the rest of the frontend team.
A successful candidate will be able to jump immediately into writing code for either our React or Flutter codebase, with the expectation that they can mentor engineers in either frontend technology.
More details on our website:
https://www.delfina.com/careers/senior-software-engineer-fro...
To apply, email resume and brief statement of interest to careers@delfina.com.
Email me, Zak King (zak@delfina.com), if you have questions.
Thank you - exactly what I was curious to learn more about!!
Would anyone knowledgeable about the field update their priors about whether we’ll see commercial fusion in the next 30 years, after seeing these results? If not, is there a big milestone we’re waiting for? Or will fusion advancement be a slow grind with many small improvements over decades?
Delfina [https://delfina.com/] | Software engineer (junior or senior, back or front or fullstack) | Full time | Remote (Anywhere)
We are building intelligent pregnancy care for healthier moms and babies. Our motivating challenge is the fact that in the United States, healthcare outcomes for pregnancy are significantly worse than in other similarly developed countries. We believe our technology-enabled solutions will help doctors better scale to better use data and in the end, deliver better care to their patients. We are looking for people who believe in our mission to join our team!
We are looking for both junior and senior level software engineers. And we’re open to backend, frontend, or fullstack positions. It will help if you experience in one or more of:
- Flutter for iOS and Android or React - Python (FastAPI) - PostreSQL, GraphQL - GCP, GitHub Actions
Experience in healthtech, pregnancy care, machine learning, cloud operations, and design are all valuable as well!
Delfina offers competitive benefits, including health, dental, and vision coverage, unlimited PTO, and 10 weeks fully paid leave for parents of all genders and any parental event including adoption.
On the function hooks, that would be awesome. I was just implementing some of those SQL commands.
And I will look more at the realtime libraries to see the new stuff. Thanks for all the open code!!
I love the direction Supabase is taking; finding the building blocks of modern applications (database, auth, functions, presence, realtime subscriptions), making them easy to use, and then sharing the source code. I’ve learned a ton just from cruising around supabase GitHub.
Can you say which of these new components will be open sourced? There are some other features (e.g. function hooks) that are also closed-source at the moment. Is Supabase heading for an “open core” model?
These are evocative images. I love a bunch of them! Knowing that this model was trained on a huge corpus of existing images makes them feel a bit like the output of a visual search engine -- finding relevant pieces and stitching them together. But it's more than that, because the stitching happens at different levels. They are often thematically and aesthetically cohesive in a way that feels intelligent.
Maybe we're just search engines of a similar kind.
An additional aspect of human art is that it (usually) takes time to make. The artist might spend many hours creating and reflecting and creating some more. The artist's engagement with the work makes its way into the final product, and that makes human art richer. Could future Dall-E version create sketches and iterations of a work; is there a limit to this mimicry?
I'm feeling future shock; heavy future shock.
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Come work with us at the cutting edge of synthetic biology!
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Amyris has developed a platform for designing and building synthetic organisms. Our technology is being used today to make clean beauty products, bio-based renewable chemicals, and even vaccine ingredients.
Among the tools we have developed are a CAD/CAM system for genetic engineering: a compiler toolchain whose target architecture is life itself. This stack physically integrates high level genetic modules into microbial hosts. We also derive novel strains through random mutagenesis and directed evolution. Using our custom control platform, we then subject these experimental organisms to high throughput performance screening in our state-of-the-art robot labs.
Specifically, we are looking for a senior software engineer to join our software engineering team in R&D https://jobs.lever.co/amyris/475990a5-d88d-464b-8444-62ce51c...
We are also opening a DevOps position and other tech positions in the next couple week. If you're interested, you can reach out to me at king@amyris.com
You might also want some pathways to be pre-validated to work together in certain cellular contexts, like they have been doing with the BioBricks project
agreed! a couple things seem to be holding this back:
- the academic publishing model incentivizes groups to build their own tools
- the small-ish market for something like this has kept commercial software from taking off (Genomatica started by building a tool like this in the early 2000s, before pivoting to bioprocess development)
- it's really hard to specify pathways in concrete physical terms. Even a chemical like glucose is actually a collection of pseudo-isomers (alpha & beta D-glucose). And try firmly defining a "gene" in your database!
that being said, there's a ton of work going on in this field and many cool projects to follow: https://dd-decaf.eu, https://biocyc.org, http://bigg.ucsd.edu, http://metanetx.org
It’s cool to see this on HN. It’s a common activity in metabolic modeling & metabolic engineering circles to build new pathway visualization tools (I spent a chunk of my PhD on one called “Escher”). I keep waiting for a tool to come along that’s good enough to be sticky and win this little market. But it might be more like IDEs, where there are some classics (pathway tools = emacs?), and an endless supply of new entrants.