@dhruvtwt_ 3. To make that claim, we would need evidence that the Dashavatar tradition was actually intended as a description of biological evolution rather than a symbolic or spiritual narrative.
@dhruvtwt_ 2. We see familiar shapes in clouds, constellations in random stars, and meaningful connections between unrelated events. The fact that two sequences can be mapped onto each other does not necessarily imply that one predicted the other.
@dhruvtwt_ 1. Interesting read. However, I believe these similarities are largely retrospective. Humans are exceptionally good at finding patterns and constructing narratives after the fact—even where none were originally intended.
AI systems are increasingly becoming distributed systems with probabilistic components.
The hard part is no longer the model.
It’s:
- orchestration
- reliability
- memory/state
- evaluation
- observability
- human oversight
LLM calls are easy.
Production systems are not.
Your AI demo works. Your AI system won't. The gap isn't the model. It's everything around it. Evaluation. Retrieval. Drift. Observability. Structured outputs. The model is the easiest part to replace. The system is not.
Read the full article here 👇
Everyone is building agents.
Very few are building observability.
If you cannot answer:
- Why the agent made a decision
- Which tool call failed
- Which memory corrupted the trajectory
- Which prompt caused drift
…you do not have an AI system.
You have a demo.
Old World
Idea → Code → Product
Code was bottleneck.
New World
Idea → Architecture → Constraints → Evaluation → Orchestration → Reliability
Code is increasingly automated.