Search: #ProductionAI
The agent stayed inside budget. It still closed 412 tickets in forty minutes. Tokens, tool calls, time, and dollars were all fine. A new prompt widened "out of scope," and every write looked cheap. The total change was the bug.
#AIAgents #ProductionAI
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AI workflow shipped.
Pager exploded.
Memory went vertical.
State was being duplicated at every agent boundary.
2 → 4 → 8 → 16 → 32…
Fix: strict contracts.
Pass full state in. Return only what’s new.
Boundaries are the architecture.
#AgenticAI #ProductionAI
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Your LLM demo works. Production needs 7 controls it does not have yet:
auth, rate limits, input guardrails, output guardrails, tracing, evals, and fairness checks.
The checklist, with one test for each:
llmarchitect.ai/go/x-demo-co…
#ProductionAI #LLMArchitecture
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Ray Anam Inc. Studios shifts to enterprise AI, focusing on robust MLOps pipelines and production-grade AI systems.
#mlops #aiintegration #productionai #rag
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An AI prototype can prove that a model, agent or workflow works.
It doesn't prove the system is ready for production.
Authentication, state, security, observability, governance and enterprise integration still need engineering.
cerait.com/?utm_source=x&utm…
#ProductionAI
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AI is easy to demo. Getting it into production is the harder part.
Disconnected systems, fragmented delivery, and scaling beyond pilots remain real challenges for businesses.
The focus needs to shift from building AI to making it work at scale.
#Colate #ProductionAI #EnterpriseAI
Giving an agent production access is where the operational questions begin. George Stan from @gameloft looks at how agents already running in production are controlled and monitored, and how mistakes are stopped before they become incidents.
#bdw2026 #productionai #aiops
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The most dangerous AI failures look like success.
We've built production voice agents for clients. One risk: an agent confirms a CRM update, but the write fails.
The conversation looks fine. The task didn't happen.
Verify outcomes, not just responses.
#ProductionAI #VoiceAI
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Production RAG needs more than embeddings and a vector database.
Think ingestion, metadata, access control, retrieval quality, observability, and continuous updates:
dev.to/ayshriv/building-rag-…
#RAG #ProductionAI #AIEngineering #SpringAI
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LLMs are stochastic, not deterministic. Here is why agent loops break in production, and the guardrails, schema checks, FSMs, circuit breakers, that fix it.
#aiagents #productionai...Show more
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Your demo worked. Then production happened.
@cdatasoftware's Amit Naik on why 50-60% accuracy doesn't survive contact with real budget, real customers, real stakes 👇
youtu.be/_u9QcoSz7GQ
#EnterpriseAI #AIAgents #ProductionAI
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50-60% accuracy might pass in a demo. It won't survive production.
Amit Naik of @cdatasoftware on why a wrong forecast, response, or write-back costs so much more once real budget is on the line.
youtu.be/_u9QcoSz7GQ
#EnterpriseAI #ProductionAI
Clean data isn’t automatically AI-ready data.
An agent also needs business meaning, permissions, lineage, refresh logic, and a way for people to verify the answer.
Clean tables are only the starting point.
#DataQuality #BusinessContext #ProductionAI
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Six Pattern Families Every AI Systems Engineer Needs to Know romeepanchal.com/posts/ai_en… #AIengineering #LLMsystems #productionAI #systemdesign
Why production LLM apps need schemas, validation, observability, retries, and deterministic boundaries around the model.
#aisystemsengineering #productionai...Show more
The demo worked perfectly.
Nobody asked who owns it when the model drifts at 2 AM on a Sunday.
25 years of enterprise deployments. Three truths about production AI. This is the second of three.
▶ Watch.
#ProductionAI #Quadra
Tutorial-grade vs production-grade extraction.
The gap between these two is the entire job. Most people never cross it.
#DocumentAI #ProductionAI
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The 4 layers of a document-extraction pipeline that survive in production.
Most tutorials teach layer 2 and stop. Layers 1, 3 and 4 are the job.
#DocumentAI #ProductionAI
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Neurix v3 Just got delayed But these features are coming tomrrow Ai firewell Prompt Regression Testing Self-Healing Structured Outputs Live Failure Observability Automated Red Team Testing #AIReliability #ProductionAI #BuildInPublic
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AI reliability infrastructure isn't optional anymore. It's the difference between a production system and a demo with real users.
Neurix V3.5 is live. Free beta. No excuses.
#AIReliability #ProductionAI
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