Ya, we tried it a bit, but have stayed with agent-behind-MCP style patterns for now. I think A2A or something like it will become a big thing as everything matures. It just felt over complicated for our use case. One misconception I had was we would just slap A2A on our existing agents and they’d work well together. Kind of dumb in hindsight.
I have never been interested in the “normal” social media apps like Instagram, Twitter, Tiktok, and the like. The content never appealed to me as a consumer enough to get started. Occasionally something would go viral enough that a friend would eventually link it to me and that was the whole experience.
Recently, I made a dumb little app for my kids and decided to try marketing it on social media just to see what it is like. It is fascinating in a sense and disheartening as well. I have been very unsuccessful, but the most signal tends to come from the dumbest content I have tried.
In doing this, I have come into contact with the social media feeds I never felt the need to look at and man… they are like a drug. I find myself mesmerized by random IG reels. It is one thing to understand what they are on an intellectual level and a totally different to feel it first hand.
Interesting. I haven’t fully read through the rule change, but seems like HHS is directly adopting the controls required by HITRUST? I have been out of the industry for a while. Always interesting how the industry shapes regulation and vice versa.
The best are the Jira tickets with a huge wall of AI slop requirements. Usually full of nonsense of course including implementation recommendations in the wrong language or framework. Questions for clarification met with blank stares from the author. Ah well, copy/paste into claude code and say “do this. make no mistakes” and get back to browsing HN…
I ran through the eval loop for a side project’s task (personalization of a micro video game, no thinking) last night. Head to head with Gemini 3 Flash Preview, results came out at basically a wash on my rubric. The output quality was good, well grounded, and reliable across 144 runs. But not noticeably better. It isn’t a traditional coding task, so can’t infer anything there. The amazing part was how fast it is. It was consistently about 2x faster than 3 Flash Preview and slightly faster than 3.1 Flash Lite Preview which is amazing. For my task, the price difference doesn’t matter, so easy upgrade. I plan to write up a quick blog post with the results over the weekend.
Some data centers are more valuable as targets than others. For example, those comprising us-gov-east-1 and us-gov-west-1 or, god forbid, us-east-1. I don’t expect it is a difficult task to find them and other critical infrastructure for a state, but probably more involved than popping open google maps.
Data centers are such great targets in modern warfare. A few cheap drones can inflict billions in damage with low direct casualties (if the attacker even cares). I have heard AWS in particular is secretive about the exact location of their data centers, but no doubt every major country knows exactly where they are.
Opus 4.7 via code has been inconsistent for me. Sometimes, it feels like working with a brilliant collaborator and is as good as 4.5 and 4.6 were. Other times, it takes dumb and lazy short cuts. It can be quite frustrating. Its response when I tell it it did something wrong is often to write a memory... which is then does not always read. The inconsistency isn't due to session length or age either. These are all new sessions. I feel like sometimes, I get routed do a dumber model or some other hidden setting is applied.
It is scary building on the public cloud as a solo dev or small team. No real safety net, possibly unbounded costs, etc. A large portion of each personal project I do is spent thinking about how to prevent unexpected costs, detect and limit them, and react to them. I used to just chuck everything onto a droplet or VPS, but a lot of the projects I am doing lately need services from Google or AWS. I tend to prefer GCP at this point because at least I can programmatically disconnect the billing account when they get around to tripping the alert.
Very interesting. I just started researching this topic yesterday to build something for adjacent use cases (sandboxing LLM authored programs). My initial prototype is using a wasm based sandbox, but I want something more robust and flexible.
Some of my use cases are very latency sensitive. What sort of overhead are you seeing?
So much content is just straight copy/pasted from the LLM now. Articles, blog posts, linked in posts, reddit comments, etc. Even just using the LLM for 'editing' tends to shift the voice to an obvious LLM voice when used naively. It is getting worse too. Last week a co-worker sent me a screenshot of Claude for me to review their "work", which was just whatever Claude made up.
Usually, if something is very obviously unfiltered LLM output, I just stop reading.
I do use LLMs for writing myself. They are useful, but are poor authors.
Optimistically, I hope it filters out the people who were only interested in it for the money.
When I was in school, decades ago now, very few people went into CS compared to other majors. Everyone I knew going into it did it because they loved it. I would have done it regardless of the career opportunities because I want to build stuff.
Interviewing candidates over the years since then, my experience has been there are still very few of those passionate nerds and a lot of people who did it for other reasons, like the money or similar. There is nothing inherently wrong with this. I don’t fault people for it.
Maybe if we get very lucky, it will go back to a relatively few passionate people building stuff because it is cool?
I am working on a domain specific agent that includes the concept of skills. I only allow one to be active at a time to reduce the chances for conflicting instructions. I use a small sub-agent to select/maintain/change the active skill at the start of each turn. It uses a small fast model to match the recent conversation to a skill (or none). I tried other approaches, but for my use case this was worked well.
My model for skills is similar to this, but I extended it to have explicit use when and don’t use when examples and counter examples. This helped the small model which tended to not get the nuances of a free form text description.
A reason, at least for a period of time, was accuracy of the delivery systems. You can’t attack a hardened target with a 100kt weapon and a delivery system with a 1km CEP, for example.
We have done a similar operation routinely on databases under pretty write intensive workloads (like 10s of thousands of inserts per second). It is so routine we have automation to adjust to planned changes in volume and do so a dozen times a month or so. It has been very robust for us. Our apps are designed for it and use AWS’s JDBC wrapper.
My company has been intentionally causing attrition in the US by moving to effectively a 996 style schedule. As people quit, their positions are moved to the India office. It is not an officially communicated policy. I have just surmised this based on private conversations with the executives and what is actually happening.