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Rahul Agarwal
Founder | Agentic AI...ย โขย 1m
Everyone is building agents, but only a small number truly understand what it takes to run them in production. Hereโs the part people usually avoid saying: ๐ ๐ฎ๐ธ๐ถ๐ป๐ด ๐ฎ๐ด๐ฒ๐ป๐๐ ๐ถ๐ป ๐ฑ๐ฒ๐ ๐ถ๐ ๐ฝ๐ฟ๐ฒ๐๐๐ ๐ฒ๐ฎ๐๐. In development, everything is clean and predictable: good data, simple inputs, and no messy old systems. Agents behave nicely. Tests go well. Logs make sense. ๐ฃ๐ฟ๐ผ๐ฑ๐๐ฐ๐๐ถ๐ผ๐ป, ๐ต๐ผ๐๐ฒ๐๐ฒ๐ฟ, ๐ถ๐ ๐ฎ ๐๐ต๐ผ๐น๐ฒ ๐ป๐ฒ๐ ๐ด๐ฎ๐บ๐ฒ. Security teams show up with urgent concerns. Users enter things you never expected. Data often comes in incomplete or confusing. APIs stop working without warning. Memory problems grow quickly and get hard to control. Latency climbs, costs rise, and your agent starts acting unstable. All of this together makes production feel chaotic. And then someone asks: โWhy does it work in staging but not in production?โ Because staging is a comfortable, controlled space, but production isnโt. ๐ง๐ถ๐ฝ๐ ๐๐ผ ๐บ๐ฎ๐ธ๐ฒ ๐ฎ๐ด๐ฒ๐ป๐๐ ๐๐ผ๐ฟ๐ธ ๐ถ๐ป ๐ฝ๐ฟ๐ผ๐ฑ: ๐ธ Treat agents like real software: use versioning, logging, monitoring, and testing. ๐ธ Expect problems. Agents will fail, freeze, or take the wrong path sometimes. ๐ธ Set up an orchestration layer with guardrails, fallbacks, and memory control. ๐ธ Connect with legacy systems early. Waiting makes it worse. ๐ธ Keep a close eye on cost. Prototypes fool you, production does not. The decade of agents is here, but only the preparedย willย succeed.
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