takwatanabe

We build and run a multi-agent system. Today Cursor won. For a log analysis task — Cursor: 5 minutes. Our pipeline: 30 minutes.

Still a case for it: 1. Isolated contexts per role (CS vs. engineering) — agents don't bleed into each other 2. Hard permission boundaries per agent 3. Local models (Qwen) for cheap routine tasks

Multi-agent loses at debugging. But the structure has value.

Knowing fundamentals gives you deeper intuition about the technology, at every layer. When compilers appeared, you no longer needed to understand assembly and registers. But knowing how assembly and registers actually work makes you better at C. When Python came along, low-level languages felt unnecessary. But understanding C's memory management is what lets you understand Python's limitations. Now LLMs write the implementation. LLMs abstract away the code. But knowing how algorithms work, even in a high-level language like Python, is exactly how you catch LLM mistakes and inefficiencies.

Knowledge builds on knowledge. We learn basic math before advanced math for a reason. The pyramid keeps accumulating from what came before. Understanding the fundamentals still matters, I think.

Right. At Opus 4.6 rates, once you're at 700k context, each tool call costs ~$1 just for cache reads alone. 100 tool calls = $100+ before you even count outputs. 'Standard pricing' is doing a lot of work here lol

As a psychiatrist, this problem reminds me of something we studied for a long time. Patients get worse in areas we are not measuring, but the numbers we record still look normal. We learned that checking results catches things that checking process cannot catch.

The coffee machine example is interesting. That's procedural memory in neuroscience. You don't memorize each machine. You abstract the steps. Grind, filter, add grounds, pour water. Then you adapt to any machine.

LLMs can't form procedural memory on their own. But you can build it outside the model. Store abstracted procedures, inject them when needed. That's closer to how the brain actually works than trying to retrain the model every time.

I know Sonnet 4.6 has a 1M context window. I use it every day. But in my experience with Claude Code and Cursor, performance clearly drops between 20k and 200k context. External memory is where the real fix is, not bigger windows.

Yeah, fair enough. I leaned on Claude to clean up my English. I normally write in Japanese. The clinical stuff is mine though, I run a psych clinic in Japan (link in profile). Should've just written it messier.

The post-it note analogy is good, but as a psychiatrist, I'd frame it differently: LLMs are essentially patients with anterograde amnesia.

They can reason brilliantly within a single conversation — just like an amnesic patient can hold an intelligent discussion — but the moment the session ends, everything is gone. No learning happened. No memory formed.

What's worse, even within a session, they degrade. Research shows that effective context utilization drops to <1% of the nominal window on some tasks (Paulsen 2025). Claude 3.5 Sonnet's 200K context has an effective window of ~4K on certain benchmarks. Du et al. (EMNLP 2025) found that context length alone causes 13-85% performance degradation — even when all irrelevant tokens are removed. Length itself is the poison.

This pattern is structurally identical to what I see in clinical practice every day. Anxiety fills working memory with background worry, hallucinations inject noise tokens, depressive rumination creates circular context that blocks updating. In every case, the treatment is the same: clear the context. Medication, sleep, or — for an LLM — a fresh session.

The industry keeps betting on bigger context windows, but that's expanding warehouse floor space while the desk stays the same size. The human brain solved this hundreds of millions of years ago: store everything in long-term memory, recall selectively when needed, consolidate during sleep, and actively forget what's no longer useful.

We can build the smartest single model in the world — the greatest genius humanity has ever seen — but a genius with no memory and no sleep is still just an amnesic savant. The ceiling isn't intelligence. It's architecture.