Every "yank" I know is also pretty great. The problem is a political system that has entrenched an advantage for a party that would otherwise be consistently in the minority, reducing the ability of the center to moderate policy.
Canadians are right to be skeptical that the next presidency will be significantly better than the current one. A serious amount of goodwill has been burned and I think the average view up north is that it's time to build a very solid backup plan.
It doesn't even fix things if the next POTUS is the exact opposite. The world has been shown what we are capable of doing. Any four-year stretch could be governed by a joke hired to "own the libs".
Caligula's horse can't be elected solely because horses don't live past 35.
For many day-to-day computing use cases, Jev seems far better suited than an autoregressive language model, if for no other reason than it is not wasting compute thinking about anything other than how to spit out a decision.
Do you have an architectural explainer yet for Jev or are you holding that close to your chest and letting the magic rip for now?
It's just a matter of time. Astra was trained on a new 3D modelling dataset. They will surely train it on CAD apps (if they have not already done so). I don't hold out much hope for competitors hoping to get in front of that train.
Cloudflare is the canonical example of why you can't vibe-code infrastructure. Knowing that this optimization was even necessary, let-alone having the ability to build it, is something that doesn't become apparent until you're operating at considerable scale. Once there, of course if you're Cloudflare, you use coding agents to build it. But outside of these temples of scale, good luck even knowing it was needed.
If you work at a SaaS of any kind, I think it's worthwhile considering what things will look like when scale is the only thing that is really defensible anymore.
The irony is that everything about this speaks to vibe coding. The writeup was written by Claude, in a good way (E.g "while the milliseconds are important, that second part may matter more").
I think things like this are now possible through vibecoding.
That's not what I'm saying at all. I guarantee Cloudflare engineers are using coding agents every day for everything they do. The point is that discovering what you need to build comes only with the experience of operating at tremendous scale. I do not believe that someone could replicate what Cloudflare offers today just because they, say, have invested $20K/mo for 100x Claude Max plans, all of which are cranking 24x7.
This is the SaaS advantage you can still have in an AI era. You can beat your competition by being exposed to more of the real world than them. For example, anyone can vibe code an accounting app, but no matter how good AIs get no vibe-coded AI app can have a track record of what happens in an complaince audit and whether it stood up during a tax audit from some particular jurisdiction. The real world will always be more complicated than an AI can vibe code a solution to, if for no other reason that as we advance in AI, the amount of stuff an AI needs to deal with is going to increase from everyone else doing AI stuff too.
nothing stops you from simulating load. something that scales, by definition, it will have something in the small that is more or less identical to something in the large. it goes both ways.
the obstacle was always the parade of tedious obstacles to create (in this case) a sophisticated virtual harness to simulate (in this case) whatever the hell this article is about. so yeah, actually, the capability of retail coding plans are kind of the only thing that matters...
For content delivery you can simulate the load one PoP would get. You don't need to be at Cloudflare scale to build a testbench with 800G+ of traffic at different pps.
It's a capital heavy investment in an already crowded marketplace (there are many CDN companies well predating Cloudflare) with little guarantee of return on investment. Who are you expecting to show up? If you want alternatives, there are plenty, for specific products/features.
A company is a collection of processes, capabilities, and resources. Many of the processes are currently run by humans, but over time, more processes will be automated - something that has been progressing for decades, but which LLMs greatly accelerated. One way to view things as they currently are (at least from my view as a tech CEO): We now use agentic LLMs every day to inform us on strategy and process implementation. And agents now run several processes, with more on the way every week.
But here's the thing: As we use agents to automate previously manual processes, we are elevating the humans to do work that is less amenable to automation. And the surface area of that work keeps expanding because the competitive market we exist in demands it of us.
To stretch an analogy, businesses are like organisms in a pond. A new nutrient (agentic LLMs) was recently added to the pond that makes business organisms more efficient and able to eat new kinds of food and explore new areas. As a result, those organisms that do the extra exploring and consuming grow much faster than their peers who do not. At the end of the day, the new nutrient will just be part of the pond and the old kind of organism will be a fossil.
Most of our use of agents for automation is inside of internal processes. I think most real companies have tons of internal processes that could safely be automated today. The reason they aren't yet automated likely falls to a) lack of awareness that this is possible, and b) lack of resources to conduct the automation work.
OpenAI and Anthropic have recently hired legions of "forward-deployed engineers" specifically to help companies do this automation work. It's a solid move. And, if you look at some recent product announcements, they are also hard at work building the necessary plumbing. For instance, the OpenAI Agents API lets you, "Build and run cloud agents with the Codex harness, fully managed by OpenAI."
This kind of enterprise-ready, cloud-hosted stuff really accelerates implementation of AI workflows within large organizations. Not every company is in the tech space (not by a long shot). Slop isn't the primary concern. Accuracy and reliability is the primary concern, and beyond that, just the capacity to actually make the changes happen.
We built a “code atlas” that provides the LLM with a semantically queryable map of how things connect and relate in a very large and sprawling codebase that evolved over 15 years. It tends to dramatically reduce the length of time models have to spend reading code while also making sure they are aware (within their context window) of nuances that are important that might be missed were they forced to just rely on reading the code in hundreds of repositories.
I strongly recommend trying this approach out yourself. The recipe is not rocket science. Get your coding agent to take a first cut at building the atlas itself, and then manually correct it. Once you’re happy that it got things right, put an MCP on it or a CLI or whatever. And your LLMs will know what to do from there.
How did you organize the atlas? I've tried a few things including embeddings and clustering files based on how often they change in the same commits, haven't yet found anything I want to bake into my tooling.
A bunch of things. First off, I got Astra to build a semantic map itself. So, not using embeddings. Just Astra looking at our Helm charts and then the underlying repositories to see how the different parts of the system talk to each other and rely on each other.
It also had access to our internal docs (Confluence), JIRAs, Slack conversation history… All via MCPs. So it could dig around to its heart’s content as would a human developer trying to figure out the same problem.
I did also add a Vectorize database (the whole thing is Cloudflare hosted behind zero trust OAuth) as a second step and that can be helpful in surfacing concepts via the atlas’ MCP interface.
Some old twitter users still have animated gif avatars that stop being supported years ago. Maybe their approach is to just stop supporting it for new avatars and grandfathering whoever manage to upload one before.
My goodness, the complaining... Just get all your devs a $200 ChatGPT Pro (20x) plan. Yes, you lose the "team" component, but you gain so much more. And what's $200 against the salary of a good developer? It's absolutely inconsequential, even in far cheaper non-US salary regimes.
Think they are pretty happy with 20x pro subscribers, even at a loss. Highest value customer base, they'll be happy to take a loss to gain market share.
i would love to give them $200 a month, but unfortunately I have no money
AI is just another case of the rich getting richer, people who dont really need AI with practically unlimited access, and people who need to it to try and change their lives being priced out
its a wealth inequality accelerator at the worst time in history for wealth inequality
i would take 50% less usage just to be able to use it in my own time, the plus plan without 5 hour limit gives me 1 days work a week, so 4 days of usage per month, and I was happy with that
now thats been taken away i get 15 minutes of usage then 5 hours later ive lost interest in the work, i now sit with 70% usage knowing 5 hours ago that a reset was coming and I couldnt even be bothered using it
its completely killed the product for me, im now paying 20 a month for something that is no use to me
Canadians are right to be skeptical that the next presidency will be significantly better than the current one. A serious amount of goodwill has been burned and I think the average view up north is that it's time to build a very solid backup plan.
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