Stefan Popa

[Stefan Popa @pstefan15]

As models get smarter, better agent architecture is less about what you can add and more about what you can delete. Anthropic finds a single agent with skills often beats complex multi-agent setups: one customer saw ~2x faster execution.

[Tak 🦞 @cherry_mx_reds]

Anthropic is now recommending that companies REMOVE unnecessary subagents from their AI systems.

This is a pretty significant shift in agent architecture, with their team finding that a single agent equipped with skills can frequently outperform complex multi-agent systems, and one customer seeing roughly 2x faster execution.

The emerging rules of thumb:

→ Skills: Teach the agent HOW to do something, including procedures, expertise, and instructions.

→ Tools / MCP: Give the agent the ability to DO things through APIs, actions, and live data.

→ Subagents: Use for parallel work, isolated context, or tasks a single agent struggles with.

The interesting part is progressive disclosure. Instead of spawning specialized agents or stuffing everything into a giant prompt, one agent discovers and loads skills and tools as needed.

Their advice is to fold existing subagents into the main loop, turn their instructions into skills, expose their actions as tools, and run evals to see if performance holds up.

As models have gotten smarter, improving agent architecture is becoming less about what you can add and more about what you can delete.

https://t.co/DNq60Skkmc

[Stefan Popa @pstefan15]

The future of software development perspective. Even if half of these land, the bottleneck moves from writing code to reviewing it and deciding what to build. That's a management problem as much as an engineering one.

[Thorsten Ball @thorstenball]

Most predictions I see are still way too conservative.

Here's mine

[Stefan Popa @pstefan15]

The gap is visible inside engineering orgs too. Some teams treat LLMs as autocomplete, others redesign how they review and ship. The difference isn't tools, it's whether anyone owns the question 'what changes in our process?'

[Andrej Karpathy @karpathy]

Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.

- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.

The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.

So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

[Stefan Popa @pstefan15]

Yey

[Elon Musk @elonmusk]

Grok @Bot is like hiring an incredibly competent employee

[Tomas Kucera @GeekyLeader]

To build a strong #culture, put in place the right processes, artifacts, and rituals. Have clear values, share the right stories, remove assumptions, and follow through on the consequences. How To Build Employee Centric Culture https://t.co/VLfKWDCSlj

[Stefan Popa @pstefan15]

Botezul lui Eduard-Alexandru!
The baptism of Eduard-Alexandru!

[Stefan Popa @pstefan15]

Join me at New concept: TECH LUNCH - Moving Java Forward Faster, what to expect? https://t.co/BtwUhKhnT4

[Stefan Popa @pstefan15]

Facebook And Deloitte Digital Come Together To Help Brands Evolve Into Digital https://t.co/bFwRRDYLxR