@hackproduct9: Most things people call "AI agents" are workflows. ⚡ That's not an insult — it's the right call. A workflow has a predefined path. An agent picks its own. Workflows are cheaper, faster and far easier to debug, and four of these five are workflows 👇 🟣 01 PROMPT CHAINING input → step 1 → validate → step 2 → final Break one big task into steps and check the work between each. If validation fails, it goes back a step. Best for: workflows you can decompose cleanly. 🔵 02 ROUTING A classifier reads the query and sends it to exactly one specialist. Best for: many input types, one clean front door. Support inbox — billing vs shipping vs technical. 🟢 03 PARALLELIZATION Fire several LLM calls at the same time, then merge. Best for: speed, voting on an answer, or covering many angles at once. The subtasks must not need each other's output. That's the only rule. 🔵 04 ORCHESTRATOR-WORKERS A manager LLM decides the subtasks at runtime and delegates. Watch the worker count change — 1, 2, 3 — because it can't be known upfront. Best for: "fix whatever files this bug touches." 🟡 05 EVALUATOR-OPTIMIZER A generator drafts. An evaluator critiques. Loop until it passes. Best for: high-quality output with clear success criteria. 👀 The one nobody says: only ONE of these five has an edge that points backwards. Patterns 1 to 4 go forward and finish. Pattern 5 loops — and the moment your design needs a loop, you've stopped writing a pipeline and started owning a state machine, a retry budget and a stopping condition. Most people reach for the loop first because it feels agentic. It's the one to reach for last. 🎯 The rule: most real systems are two of these, chained. 📸 Screenshot it before your next architecture call. Follow @hackproduct — we turn scary AI-engineering concepts into things you can ship. ⚡ . . #AIagents #agenticAI #AIengineering #LLM #anthropic

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Thursday 20 August 2026 23:58:34 GMT