SciMigo turns deep infrastructure products into hands-on courses, failure-driven labs, technical visualizations, workshops, and AI-assisted learning.
For developer-tool, infrastructure, AI platform, and distributed-systems companies.
Python · Docker · 11 modules · production agent runtime
Kill the Worker, inspect Event History, and prove what survives. The course grows one working AgentRun implementation through replay, failure, and deployment—not a summary of product documentation.
A complete learning system for products whose behavior only becomes clear when developers run them, break them, and inspect what happened.
Production-shaped code that establishes the architecture, vocabulary, and correctness boundary.
Runnable experiments with crashes, retries, replay, late data, upgrades, and recovery.
Structured learning for customers, partners, internal engineering teams, and live cohorts.
Diagrams and animation that make state, time, coordination, and failure visible.
Checks that measure applied understanding, not documentation recall.
AI-assisted support built on verified curriculum, source material, and observed system behavior.
The pipeline begins with product truth and ends with education that can be tested, taught, and extended.
Product docs, source code, and subject-matter expert knowledge establish the intended model.
A working reference implementation makes the architecture concrete.
Adversarial tests inject crashes, replay, version changes, bad timing, and load.
Observed behavior is turned into a clear learning design and correctness story.
Labs, courses, workshops, visualizations, and video make that story executable.
A grounded AI tutor helps developers reason from the verified material—not improvise around it.
Temporal, Restate, and Flink demonstrate the same standard: build the system, inject failure, inspect the evidence, and verify the explanation against observed behavior.
Build a durable agent-job runtime that survives Worker crashes, pauses for days, accepts new instructions, delegates to sub-agents, and outlives deployments.
Python · Docker · failure injectionBuild GatewayMeter and defend its invoice through late data, stalled partitions, TaskManager deaths, backpressure, upgrades, and hot tenants.
PyFlink · Kafka · live failuresCrash a running agent, count the model calls replay costs, trigger a journal mismatch, and fix both with one durable step.
Python · Restate · recorded runsWe partner with DevRel, Developer Education, Product Marketing, and engineering leaders when adoption depends on more than another documentation page.
A reference application, modular course, labs, instructor material, and launch-ready learning path.
Focused education around the hard behavior developers must understand before production.
Live or self-paced programs for customers, partners, field teams, and internal engineers.
Reusable diagrams, assessments, content architecture, and grounded tutoring for an evolving product.
Material is tested against the actual software: real code, observed behavior, and version-verified environments.
Failure injection, Event History inspection, replay tests, and runtime evidence expose the details generic tutorials miss.
AI accelerates production, but customers buy technical accuracy, pedagogy, experimentation, and developer adoption.
Tell us what your product does, where developers get stuck, and what adoption should look like. We will propose an executable education program grounded in the real system.
