Brad Woods has an amazing website dynamically illustrating the concept of "juice", which he defines as "the non-essential visual, audio and haptic effects that enhance the player's experience".
There's an example of how you can juice up a simple "delete" button with various levels of UX. I encourage you to play around with it to juice up your own buttons!
Agreed. In my experience, product development is 60% of the work. There's a ton of other stuff like RTB tasks, infra overhauls, etc that good PMs acknowledge the importance of but is primarily driven by the engineering team.
Yeah I think this maps onto grep-based code search well. Right now agents grep, read the results, grep again, and every hit lands in context. This architecture turns that into one program: fan out the greps, filter and dedupe in the sandbox, hand back only what matters. The "won't know the codebase" worry flips around too. The first program shouldn't be "find the bug," it should be "build me a map" (grep the file tree, import graph, symbols). That needs zero prior knowledge, then the model plans the real search over that map. So it's less about replacing sequential exploration and more about making each grep step way wider without flooding context
We use AI to monitor hundreds of local government commissions and give real-time intelligence to B2B, residents, and governments. If you're a business trying to track what's happening in local gov for your policy, sales, or lobbying team, I'd love to chat.
The order of priority for most people is: 1\ output quality 2\ latency 3\ cost. I will always pays more money if output quality is significantly better and latency is worth the tradeoff. There's also enough cost optimization strategies for applied AI applications that token cost rarely outweighs unless it's a SIGNIFICANT difference (e.x. 100-200% more).
This is dumb. The solution for all music platforms should be to add a label for AI-generated tracks or artists so users clearly can disambiguate. It's frivolous to prevent someone from enjoying a piece of art whether AI or human. Furthermore, the line is blurred between what constitutes human vs AI development of music. Most producers today use pre-packaged samples, sequencers, and tracks to generate derivatives. Sure, they might manually have to mess around with Ableton to do so, but the line is already blurred.
Solid OSINT methodology here. The 10x AS path prepending is the most interesting detail to me b/c typically you'd see prepending used to de-prioritize a route, which raises the question: was this about making traffic avoid CANTV, or was it a side effect of something else?
A few thoughts:
- The affected prefixes (200.74.224.0/20 block → Dayco Telecom) hosting banks and ISPs feels significant. If you're doing pre-kinetic intelligence gathering, knowing the exact network topology and traffic patterns of critical infrastructure would be valuable. Even a few hours of passive collection through a controlled transit point could map out dependencies you'd want to understand before cutting power.
- What's also notable is the transit path through Sparkle, which the author points out doesn't implement RPKI filtering. That's not an accident if you're planning something (you'd specifically choose providers with weaker validation).
- The article stops short of drawing conclusions, which is the right call. BGP anomalies are common enough that correlation ≠ causation. But the timing and the specific infrastructure affected make this worth deeper analysis.
Would love to see someone with access to more complete BGP table dumps do a before/after comparison of routing stability for Venezuelan prefixes in that window.
I don't think the root cause here is AI. It's the repeated pattern of resistance to massive technological change by system-level incentives. This story has happened again and again throughout recent history.
I expect it to settle out in a few years where:
1. The fiduciary duties of company shareholders will bring them to a point of stopping to chase AI hype and instead derive an understanding of whether it's driving real top-line value for their business or not.
2. Mid to senior career engineers will have no choice but to level up their AI skills to stay relevant in the modern workforce.
There's an example of how you can juice up a simple "delete" button with various levels of UX. I encourage you to play around with it to juice up your own buttons!
Source: https://garden.bradwoods.io/notes/design/juice