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Multi-Agentic Software Development Is a Distributed Systems Problem
11–20 of 75 posts
Re: Multi-Agentic Software Development Is a Distributed Systems Problem
#12Earlier quoted context omitted.
Humans can also count the number of Rs in strawberry, but good luck proving that mathematically
LLMs don't see words. They see tokens, which is why previously they had a hard time counting the r's. You can certainly prove that mathematically, and giving that proof to an LLM it will give you the correct answer. Which is a prompting technique btw to improve accuracy of an LLMs results. Although the more recent LLMs have built in approaches to answer this question. Gemma4 for example: ----- The user is asking for…
Doubt if you can make a dumb model smart by feeding it proofs
Re: Multi-Agentic Software Development Is a Distributed Systems Problem
#13Makes sense. Coordination between multiple agents feels like the real challenge rather than just building them.
Re: Multi-Agentic Software Development Is a Distributed Systems Problem
#14Well it starts with agree list.
I don't agree next gen models will be smarter.
I would argue no real improvement in models in last couple of years just improvement in stability and tools (agentic ones) around it.
Re: Multi-Agentic Software Development Is a Distributed Systems Problem
#15Doesn't this whole argument fall apart if we consider iteration over time? Sure, the initial implementation might be uncoordinated, but once the subagents have implemented it, what stops the main agent from reviewing the code and sorting out any inconsistencies, ultimately arriving at a solution faster than it could if it wrote it by itself?
Right, but what you're describing is a consensus protocol. It's called 2 phase commit. The point of the article is just that we should really be analysing these high level plans in terms of distributed algorithms terms, because there are fundamental limitations that you can't overcome.
Re: Multi-Agentic Software Development Is a Distributed Systems Problem
#16Conway’s law still applies. Good architecture, actor models, and collaboration patterns do not emerge magically from “more agents”. Maybe what’s missing is the architect’s role.
The architect role is interesting because in practice that's what the "orchestrator" agent ends up being — but it hits the same limits as a human architect who's never on the ground floor. The agents that work best in my experience are the ones scoped tightly to a single concern (run this test suite, lint this file) rather than collaborating on shared state. Basically the microservices lesson all over again: shared-nothing works, shared-everything doesn't.
Re: Multi-Agentic Software Development Is a Distributed Systems Problem
#17The thing that TFA doesn't seem to go into is that these mathematical results apply to human agents in exactly the same way as they do to AI agents, and nevertheless we have massive codebases like Linux. If people can figure out how to do it, then there's no math that can help you prove that AIs can't.
Ive yet to see a human process which used an excessive number of cheap junior developers precisely architected to create high quality software.
If that could have been achieved it would have been very profitable, too. There's no shortage of cheap, motivated interns/3rd world devs and the executive class prefer to rely on disposable resources even when it costs more overall.
The net result was always the opposite though - one or two juniors on a leash could be productive but more than that and it always caused more problems than it solved.
Seeing the same problem with agents. Multi agent orchestration seems like a scam to manufacture demand for tokens.
Re: Multi-Agentic Software Development Is a Distributed Systems Problem
#18Earlier quoted context omitted.
LLMs don't see words. They see tokens, which is why previously they had a hard time counting the r's. You can certainly prove that mathematically, and giving that proof to an LLM it will give you the correct answer. Which is a prompting technique btw to improve accuracy of an LLMs results. Although the more recent LLMs have built in approaches to answer this question. Gemma4 for example: ----- The user is asking for…
Doubt if you can make a dumb model smart by feeding it proofs
Re: Multi-Agentic Software Development Is a Distributed Systems Problem
#19To be honest humans often have no overview over a application either. We navigate up and down the namespace, building the "overview" as we go. Nothing i see what prevents an agent from moving up and down that namespace, writing his assumptions into the codebase and requesting feedback from other agents working on different sets of the file.
Re: Multi-Agentic Software Development Is a Distributed Systems Problem
#20The fundamental assumptions of distributed systems is having multiple machines that fail independently, communicate over unreliable networks and have no shared clock has the consequence of needing to solve consensus, byzantine faults, ordering, consistency vs. availability and exactly-once delivery.
However, AI agents don't share these problems in the classical sense. Building agents is about context attention, relevance, and information density inside a single ordered buffer. The distributed part is creating an orchestrator that manages these things. At noetive.io we currently work on the context relevance part with our contextual broker Semantik.