AIONTHEFLY Technologies logoAI FDE TOOLKITDeveloped by Dr. Sudin Baraokar

Module 15 · skill stack

FDE stack co-relation

The sixteen skills on the badge wall are not a checklist — they are a dependency graph. This module correlates every skill with the L0-L9 enterprise layers it operates on, the toolkit modules that drill it, and the other skills it cannot function without. Select a chip to open its deep dive.

$ python -m fde_toolkit stack

Skill stack covered

select a chip for its deep dive

Linux & Bash

infrastructure · layers L0

depth
4/5
frequency
5/5
Why the FDE needs it
Every forward deployment starts on someone else's box, usually over SSH, usually with no GUI and no sudo. Disk, inodes, ports, systemd units and file permissions are the first four hours of any install.
Failure mode when it is missing
The pilot stalls on day one because nobody can read journalctl or free a full /var partition, and the customer concludes the product is fragile.
Drill
Run the environment scan, then work the instructor-mode workarounds for a locked-down host.
python -m fde_toolkit diagnosticsDiagnostics →SEOS →

Co-requisite skills

3 correlated

Correlation heatmap

hover a cell for the pairing · click to drill

skillLINDOCKUBPYTGITRESLLMMCPREADAGVECOPAAUDAMLSCOLIV

Skill-gap scenario builder

select the missing skills — the stack predicts what breaks

Deployment readiness

100%

Full stack present. The cohort can take this deployment end to end without a partner team.

  • Infrastructure3/3
  • Platform & integration3/3
  • Agentic runtime4/4
  • Knowledge & memory1/1
  • Governance3/3
  • Consulting craft2/2

Layer impact

  • L0Data centreclear
  • L1Business dataclear
  • L2Applicationsclear
  • L3Data pipelinesclear
  • L4Knowledge fabricclear
  • L5AI / ML fabricclear
  • L6Agent runtimeclear
  • L7Policy and quantumclear
  • L8Human controlclear
  • L9Audit and feedbackclear

Second-order degradation

No skills selected — nothing downstream is starved.

Module drill coverage lost

Predicted failure modes

Full stack present — no predicted failure modes for this cohort.

Prerequisite dependency graph

click a node to treat it as missing

prerequisites missing breaks downstream

Edges run left to right from prerequisite to dependent, columns are topological rank and rows are grouped by the lowest architecture layer the skill owns (L0 metal at the top, L9 audit at the bottom). Selecting Linux & Bash removes it and everything that cannot be practised without it.

Linux & BashL0Docker / Compo…L0Kubernetes bas…L0Python & asyncL2Git & CI/CDL2REST / OAuth /…L2LLM API mechan…L5MCP tool calli…L6ReAct loopsL6DAG decomposit…L6Vector & graph…L4OPA / RegoL7Audit loggingL9AML / KYC cont…L1Scoping & tran…L1Live recoveryL8

Prerequisite chains into Linux & Bash

0 upstream skills

Linux & Bash is a root of the graph — nothing has to be learned before it, which is exactly why it is drilled first in the cohort.

Downstream breakage without Linux & Bash

14 skills fall over

14 dependent skills12 modules dark8 layers unowned95% of stack depth lost
  • Docker / ComposeLinux & Bash → Docker / Compose1 hop
  • Live recoveryLinux & Bash → Live recovery1 hop
  • Python & asyncLinux & Bash → Python & async1 hop
  • DAG decompositionLinux & Bash → Python & async → DAG decomposition2 hops
  • Kubernetes basicsLinux & Bash → Docker / Compose → Kubernetes basics2 hops
  • MCP tool callingLinux & Bash → Python & async → MCP tool calling2 hops
  • REST / OAuth / TLSLinux & Bash → Python & async → REST / OAuth / TLS2 hops
  • Vector & graph DBsLinux & Bash → Python & async → Vector & graph DBs2 hops
  • Audit loggingLinux & Bash → Python & async → DAG decomposition → Audit logging3 hops
  • LLM API mechanicsLinux & Bash → Python & async → REST / OAuth / TLS → LLM API mechanics3 hops
  • OPA / RegoLinux & Bash → Python & async → MCP tool calling → OPA / Rego3 hops
  • ReAct loopsLinux & Bash → Python & async → MCP tool calling → ReAct loops3 hops
  • Scoping & translationLinux & Bash → Python & async → Vector & graph DBs → Scoping & translation3 hops
  • AML / KYC contextLinux & Bash → Python & async → DAG decomposition → Audit logging → AML / KYC context4 hops

Modules that stop working

Layers left with no owner

L0 Data centreL1 Business dataL3 Data pipelinesL4 Knowledge fabricL5 AI / ML fabricL6 Agent runtimeL7 Policy and quantumL8 Human control

Longest failure chain

Linux & Bash → Python & async → REST / OAuth / TLS → MCP tool calling → ReAct loops → DAG decomposition → Audit logging → AML / KYC context → Scoping & translation → Live recovery

Ends at Human control, so the gap is visible to the customer, not just to the engineer.

Skill × architecture layer

L0 metal → L9 audit

  • L0Data centre3 skills
  • L1Business data2 skills
  • L2Applications4 skills
  • L3Data pipelines1 skill
  • L4Knowledge fabric1 skill
  • L5AI / ML fabric2 skills
  • L6Agent runtime4 skills
  • L7Policy and quantum1 skill
  • L8Human control3 skills
  • L9Audit and feedback3 skills

Module skill load

which module drills which skills

  • ReAct
    23

    Python & async · LLM API mechanics · MCP tool calling · ReAct loops · Live recovery

  • Replay
    20

    ReAct loops · OPA / Rego · Audit logging · AML / KYC context · Live recovery

  • Diagnostics
    16

    Linux & Bash · Docker / Compose · Kubernetes basics · Live recovery

  • Tool synth
    14

    Python & async · REST / OAuth / TLS · MCP tool calling

  • Ontology
    13

    REST / OAuth / TLS · Vector & graph DBs · Scoping & translation

  • SEOS
    11

    Linux & Bash · Docker / Compose · Kubernetes basics

  • Policy
    10

    Git & CI/CD · OPA / Rego · AML / KYC context

  • AIQOS
    10

    Kubernetes basics · OPA / Rego · AML / KYC context

  • DAG
    9

    Python & async · DAG decomposition

  • RAG
    9

    Python & async · Vector & graph DBs

  • Memory
    8

    LLM API mechanics · Vector & graph DBs

  • Audit
    7

    Git & CI/CD · Audit logging

  • Cohort
    5

    Scoping & translation

  • Routing
    4

    LLM API mechanics

Tier profile

depth vs frequency

TierSkillsAvg depthAvg useWhat it decides
Infrastructure33.74.3The customer's metal, containers and clusters — where the demo actually has to run.
Platform & integration34.04.7Code, pipelines and the protocols that get you through the customer's edge.
Agentic runtime44.34.5The reasoning loop: routing, tools, plans and recovery.
Knowledge & memory14.04.0Grounding the model in the enterprise's own truth.
Governance33.74.3The deterministic half of the system — what turns a proposal into a permitted action.
Consulting craft25.04.0The non-code skills that decide whether the pilot survives the room.

Leverage ranking

depth × use + co-requisite degree

  1. 139 · deg 14
  2. 236 · deg 11
  3. 335 · deg 10
  4. 431 · deg 15
  5. 531 · deg 11
  6. 630 · deg 10
  7. 730 · deg 10
  8. 828 · deg 8
  • The stack is a chain, not a menu: the weakest tier caps the deployment. An FDE with a perfect agent runtime and no Linux never reaches the demo.
  • Governance skills correlate almost perfectly with each other — Rego, audit and AML domain literacy are effectively one competency in a regulated account.
  • Python is the highest-degree node: it links infrastructure to the agent runtime and to knowledge retrieval, so it is the first gap worth closing.
  • Consulting craft has the highest day-one depth requirement and the lowest teachability, which is why it is drilled live rather than read.