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 :)]
Hi there, I was wondering if you'd be willing to share that ChatGPT chat with me (or everyone). I'm the CEO of a competing product (DBOS) and I'm just curious what your question and responses were that let you elsewhere. Thanks!
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.
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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
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Find the posting here, which include some details on comp & benefits:
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:
Hi guys, I saw you had a backend position with a March 31 deadline. I had applied in February and didn’t hear back. Is the data eng position still 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:
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.
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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.
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 :)]