I started thinking about this while leading an internal Ops platform at a previous operations-intensive tech company. As we automated Ops work, I found the bottleneck to shifting left was was defining the processes our Ops team followed. Eng entered late: first, we'd throw Ops resources at a new challenge; then gradually systematize it; wait for PM attention; document the process; and finally engage engineering. This was necessary since systematized bad processes meant scaled mishandling of issues and engineering rework.
Drafting AI offers a different path: teams begin automating processes organically as they discover them, growing toward full automation as understanding deepens. Human review catches edge cases, handles ambiguous situations, and gives an incremental path towards full automation without rework.
Hopefully this lets internal tools teams shift automation further left.
I'm looking for something similar: I want it to trigger when I'm on Twitter (or HN) during 9-5 hours, and ask me what I'm supposed to be working on. Just a small nudge to rubber duck what's blocking me
totally— this is for integrating into custom internal tools. Consider content moderation: you wouldn't want mods getting tickets in JIRA then switching to a different tool to action them.
If switching between screens is not a problem, by all means prefer Linear/Asana/Jira/etc!
Totally— OpsQueue is for custom internal React apps to have integrated task management. If workers can switch between Linear and your internal apps, or you don’t have a custom internal React app, you should use Linear.
In some ways OpsQueue’s goal is to be a headless, API-first Linear.
AI will solve web accessibility by screen readers that summarize visual content, ignoring ARIA and making it irrelevant. Multimodal GPT-4 can take a screenshot jpeg and answer questions about what’s in it (buttons, links, ads, headers, etc). The future of accessibility is rendering DOM to jpeg and asking GPT to be your eyes; we’ll look back on semantic markup as a failed idea that was never going to work
Law and Order is great because it's formulaic. You know what you're going to get every time, like a Big Mac in a town you've never been to before. It's not competing with prestige TV, it's competing with rewatching old shows (where you also know what's going to happen).
The punchline: GPT-powered infinite Law and Order might actually outcompete Dick Wolf-powered Law and Order
Prompt: write html using tailwindcss for a landing page of a website called "AI incident reports" that boils down to "there have been 0 incidents of AIs causing harm. The website should look like it's meant to have lists of incidents, graphs, and so on. Consider what someone thoughtful about AI x-risk would want to track. And then have 0 for all the categories and graphs.
Let's think step by step: what should be on the website?
Drafting AI offers a different path: teams begin automating processes organically as they discover them, growing toward full automation as understanding deepens. Human review catches edge cases, handles ambiguous situations, and gives an incremental path towards full automation without rework.
Hopefully this lets internal tools teams shift automation further left.