Originally published on AI Tech Connect.
What you need to know An agent is four parts — an LLM brain, memory, tools, and a run loop. Get those right and the rest is detail. Scope ruthlessly — ship one workflow, make it reliable, then expand. A broad agent that does ten things badly helps nobody. Tool access is a security surface — unsafe tool access is one of the top reasons first agents fail. Apply least-privilege from day one. Evals are not optional — a measurable eval harness is what stops a prompt tweak quietly breaking last month's behaviour. Plenty of teams in Bengaluru and London have a working agent demo. Far fewer have an agent that has survived three months of real users. The gap between the two is not model quality — frontier models are more than capable. The gap is engineering discipline: scoping the job tightly,…
Top comments (0)