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A practitioner video outlines a repeatable daily workflow for building and iterating on LLM agents: start with a narrow task, instrument runs (traces, prompts, outputs), run quick evals on a small dataset, then refine prompts/tools and redeploy. The emphasis is on short feedback cycles, cost/latency...
A founder sold their AI startup for $1.8M and directs viewers to AgentZero, an open-source framework for building LLM-powered agents. The repo and site are positioned as a practical starting point to wire agents to real tools/services, which is relevant for backend/data teams exploring AI-driven aut...
A recent video argues engineers will spend less time hand-writing code and more time orchestrating AI to read codebases, generate tests, and propose changes. The emphasis moves to creating strong specs, test oracles, and rich observability so AI can safely automate larger parts of the workflow.
A short video demonstrates standing up a minimal AI service in about 24 minutes by scoping a single use case and wiring an LLM-backed workflow end-to-end. For teams, the practical takeaway is to time-box a thin slice, use off‑the‑shelf components, and ship a measurable demo with basic instrumentatio...