Framework · 2023–now · AI Present
Multi-agent orchestration hype
LangGraph, CrewAI, AutoGPT cosplay — agents delegating to agents for tasks one function call could do.
Multi-agent frameworks failed as defaults because non-determinism compounds with every hop and observability lagged behind demo videos. They stuck in research and narrow automation where human oversight remains in loop. The costly fad was autonomous headcount replacement on slide seventeen.
Cost of the fad
Autonomous agent swarms burned API budgets on coordination loops that a single prompt and a cron job would have handled. Debugging "which agent lied" became the new on-call sport.
Patterns
Context
The stack gets a co-pilot
AI pair programming is already changing how code is written. Agent frameworks and vector stores are still sorting winners from demos. The durable layer will look familiar: evals, retrieval quality, product UX, and ownership. Autopilot rewrites without tests are just big-bang migrations with better slides.
Compare with
Related
Framework · 2023–now
LLM app frameworks
Chains, agents, and prompt wrappers shipping weekly. The durable pieces will be boring: evals, retrieval, and product UX.
Practice · 2023–now
Agent ops / LLM observability
Tracing, cost caps, and prompt versioning for production LLM features. Datadog for tokens.
Practice · 2024–now
Vibe coding
Accept AI output on feel, skip the diff, hope tests exist. Fast demos; fragile ownership.
$ Ship-to-prod without reading the diff became a flex until incidents revealed nobody knew which prompt wrote the auth middleware. Review debt arrived in one weekend demo.