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ANTHROPIC JUST EXPOSED WHY MOST MULTI AGENT CODING SYSTEMS FAIL BEFORE WRITING A SINGLE LINE OF CODE the model is not the problem the plan is one bad dependency cut gets copied across six agents then three builders produce the wrong result in parallel spec → planner → three...

34,491 Aufrufe • vor 1 Monat •via X (Twitter)

16 Kommentare

Profilbild von kadd
kaddvor 1 Monat

Plan quality is the real multiplier

Profilbild von elune
elunevor 1 Monat

agre w u

Profilbild von Callan
Callanvor 1 Monat

bad planning parallelizes failure

Profilbild von elune
elunevor 1 Monat

yeah

Profilbild von beamnxw ./
beamnxw ./vor 1 Monat

thx for ur explanations

Profilbild von elune
elunevor 1 Monat

🫡🫡

Profilbild von Akbar Shaik
Akbar Shaikvor 1 Monat

The biggest insight here isn't even the number of agents. It's the dependency graph. Give each builder a clearly defined surface, let them operate independently, keep failures contained, then bring everything together only after verification.

Profilbild von SEO Mastery
SEO Masteryvor 1 Monat

One bad plan breaks everything downstream

Profilbild von Yasir Prototyper
Yasir Prototypervor 1 Monat

Basically supply chain optimization. I work with upstream dependencies daily. One bad plan stalls the whole line. Same principle, different stack.

Profilbild von Tony Tong | Founder | Ancient Systems x AI
Tony Tong | Founder | Ancient Systems x AIvor 1 Monat

A bad assumption early in the pipeline is the quiet killer. My production app tokenized with NLTK while my training pipeline lemmatized with spaCy, and that mismatch alone created more out-of-vocabulary words at inference than any downstream fix could catch.

Profilbild von Natalie Thompson
Natalie Thompsonvor 1 Monat

straight facts the plan really makes or breaks everything

Profilbild von Arick Goomanovsky
Arick Goomanovskyvor 1 Monat

Right - the model isn't the problem, the plan is. Which is another way of saying the failure lives in how agents are organized and hand off, not in any single agent. Multi-agent coding breaks at the seams, not the nodes.

Profilbild von Tara Curry
Tara Curryvor 1 Monat

The success of a multi-agent coding system rests on a well-thought-out plan and effective communication among agents, not just the model itself

Profilbild von غالي الاثمان
غالي الاثمانvor 1 Monat

bro this is so real, planning is literally everything

Profilbild von Shikhar Sugandhi
Shikhar Sugandhivor 1 Monat

Really interesting approach. Keeping agents isolated while feeding failures back into the spec makes a lot of sense

Profilbild von Leo Oliemans | Refinery
Leo Oliemans | Refineryvor 1 Monat

The dependency graph is part of the safety boundary. I’d want each parallel task to carry the assumptions it depends on, then get rechecked before merge. Otherwise the system can be internally consistent and still build the wrong thing.

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