Post
56
✅ New Article: *Effectful Ops That Don’t Break the World* (v0.1)
Title:
🧾 Effectful Ops in SI-Core: RML and Compensator Patterns
🔗 https://huggingface.co/blog/kanaria007/effectful-ops-in-si-core
---
Summary:
Structured Intelligence systems don’t just *think*—they *change the world* (payments, bookings, city actuators, learning/medical records). In distributed reality, partial failures and retries are normal, so “do it once” is a myth.
This article is a practical cookbook for making effectful operations *retry-safe, reversible (when possible), and auditable*, using *RML levels (1→3)*, *Sagas + compensators*, and “single storyline” effect traces—then measuring quality via *RBL / RIR / SCI*.
> A compensator is *another effect*, not a magical “undo”.
---
Why It Matters:
• Prevents double-apply / half-committed states by defaulting to *idempotency + durable traces*
• Makes rollback *engineering-real*: compensators must be *idempotent*, monotone toward safety, and bounded to a durable terminal/pending state
• Handles “can’t undo” honestly: model *partial reversibility* + remaining risk + follow-up tasks
• Turns failure handling into metrics you can operate: *RBL (rollback latency), RIR (rollback integrity), SCI (structural inconsistencies)*
---
What’s Inside:
• RML levels overview: *RML-1 (idempotent effects)* → *RML-2 (Sagas/compensators)* → *RML-3 (goal-native reversible flow graphs)*
• Compensator patterns: idempotent refunds, append-only “compensating logs”, corrective/restitution effects
• Cross-domain templates (payments / reservations / city / learning) + common pitfalls (ghost holds, out-of-order msgs)
• A full walkthrough: partial success → compensate → re-plan & re-apply as *one coherent conversation with the world*
• Implementation path: effect records → idempotency → mini-sagas → metrics → lift critical flows toward RML-3
---
📖 Structured Intelligence Engineering Series
this is the *how-to-design / how-to-operate* layer for effectful systems.
Title:
🧾 Effectful Ops in SI-Core: RML and Compensator Patterns
🔗 https://huggingface.co/blog/kanaria007/effectful-ops-in-si-core
---
Summary:
Structured Intelligence systems don’t just *think*—they *change the world* (payments, bookings, city actuators, learning/medical records). In distributed reality, partial failures and retries are normal, so “do it once” is a myth.
This article is a practical cookbook for making effectful operations *retry-safe, reversible (when possible), and auditable*, using *RML levels (1→3)*, *Sagas + compensators*, and “single storyline” effect traces—then measuring quality via *RBL / RIR / SCI*.
> A compensator is *another effect*, not a magical “undo”.
---
Why It Matters:
• Prevents double-apply / half-committed states by defaulting to *idempotency + durable traces*
• Makes rollback *engineering-real*: compensators must be *idempotent*, monotone toward safety, and bounded to a durable terminal/pending state
• Handles “can’t undo” honestly: model *partial reversibility* + remaining risk + follow-up tasks
• Turns failure handling into metrics you can operate: *RBL (rollback latency), RIR (rollback integrity), SCI (structural inconsistencies)*
---
What’s Inside:
• RML levels overview: *RML-1 (idempotent effects)* → *RML-2 (Sagas/compensators)* → *RML-3 (goal-native reversible flow graphs)*
• Compensator patterns: idempotent refunds, append-only “compensating logs”, corrective/restitution effects
• Cross-domain templates (payments / reservations / city / learning) + common pitfalls (ghost holds, out-of-order msgs)
• A full walkthrough: partial success → compensate → re-plan & re-apply as *one coherent conversation with the world*
• Implementation path: effect records → idempotency → mini-sagas → metrics → lift critical flows toward RML-3
---
📖 Structured Intelligence Engineering Series
this is the *how-to-design / how-to-operate* layer for effectful systems.
