Mmastodon TechnologyAI first seen 9 h ago, last 8 h ago, peak #2
Engineer blames agent failures on context, not reasoning
Original: I spent six weeks convinced my agents had a reasoning problem. They contradicted each other, repeated work, and confiden
A developer recounts six weeks troubleshooting AI agents that contradicted each other, repeated work, and confidently cited unverified facts. Upgrading models, rewriting prompts and adding a knowledge graph failed to fix the issues, pointing instead to how the agents share and manage context across tasks. The write-up is drawing attention from practitioners facing similar multi-agent reliability problems, as teams increasingly deploy agent systems in production and discover coordination, not raw model intelligence, is often the bottleneck.
Why now: Multi-agent AI systems are widely deployed right now, and shared failures in coordination and context management resonate with builders debugging similar setups.
Evidence
- I spent six weeks convinced my agents had a reasoning problem. They contradicted each other, repeated work, and confidently cited facts that nobody had established. I upgraded models. I rewrote prompts. I added a knowledge graph because the research said graphs were the future.… · hackaday@www.urbanmind.net · 4
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