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A Twitter thread laying out concrete steps to build a working AI agent from scratch, skipping theory and focusing on actual implementation you can follow in sequence.
- Provides a step-by-step guide designed for beginners with no prior agent-building experience
- Emphasizes practical, hands-on instructions rather than conceptual background
- Aims to produce a functional agent that operates independently without constant user intervention
A developer shares concrete ways he's using AI to handle real-world information tasks—from extracting facts across large datasets to managing school documents and trip logistics—and notes that cheaper, faster models have made it frictionless to try AI solutions for routine problems.
- AI has crossed a threshold from "somewhat useful" to "reliably handles unstructured data tasks" like extracting calendar dates from school documents or gathering trip information, though he still spot-checks critical details.
- Cheaper and faster models remove the friction that used to make AI solutions feel like overkill—the difference between spending $50 and three hours versus $5 and 30 minutes changes what feels worth trying.
- AI still falls short on high-judgment questions (like "what books should I read?") and won't replace the top-tier work of a personal assistant, only the lower-judgment data management parts.