Sebastian Schkudlara

Sebastian Schkudlara

I design and build production AI workflows: the backend paths, tools, retrieval, evaluation, approval steps, and operating controls that make AI useful beyond a demo.

Remote-first · contract / fractional / advisory · no public prices

GitHub profile LinkedIn profile

What I help with

Production AI Workflow Audit

Map one workflow, identify the real production risks, then define the safest first implementation slice.

Workflow map · risk list · architecture sketch · build / don't-build decisions

Agentic AI Pilot Rescue

Debug RAG, chatbot, or agent prototypes that looked good in demos but break under real data, users, or operations.

Evals · guardrails · observability · human handoff · production backlog

AI Workflow Build Slice

Build one end-to-end slice around real data, APIs, tools, approvals, evaluation, and deployment.

Backend/API · ingestion · tool boundaries · tests/evals · operational handoff

Fractional AI Architecture Support

Give founders and product teams senior AI/backend architecture support for vendor choices, evals, model routing, and implementation planning.

Architecture review · vendor/model decisions · implementation planning · unblock support

Delivery Partner Support

Support agencies and consultancies behind the scenes when AI delivery gets technically deep.

Architecture backup · delivery review · hard technical slices · implementation support

AI Evaluation and Operations

Set up practical checks, logs, review loops, cost visibility, and rollback paths so AI workflows can improve safely after they ship.

Evaluation cases · observability · cost checks · rollback planning

Production AI checklist

Before an AI workflow reaches users, I want clear answers to these questions:

  • What workflow does it own?
  • What data can it read?
  • What tools can it use?
  • How are outputs evaluated?
  • Where does human approval sit?
  • What gets logged?
  • How do we roll back, hand off, or recover when it is wrong?

Skill Surface

This page stays intentionally public-minimal: skills, open-source evidence, and machine-readable Scoutica data. Private identity, rate, and negotiation details stay off page.

Agentic AIModel RoutingMCP / A2ARAGKubernetesFastAPIRuby on RailsGoTypeScriptPostgreSQL

Operating Thesis

  • AI agents need memory, permissions, tools, review loops, and operational boundaries, not just bigger prompts.
  • Professional profiles should be agent-readable, privacy-zoned, and verifiable against public evidence.
  • Production AI systems need boring backend discipline: observability, cost control, deterministic gates, and rollback paths.

Open Source Projects

Scoutica Protocol

AI-readable professional profiles with deterministic fit scoring, privacy zones, evidence references, and agent workflows for opportunity evaluation.

Protocol design · Python · JSON Schema · agent workflows

Makakoo OS

Local operating layer for serious agent work: shared memory, skills, plugins, browser/media tools, cross-CLI workflows, and durable project context.

Agent OS · memory · skills/plugins · MCP · local-first tooling

Lope

Multi-CLI validator ensemble where one AI implements and independent AI tools review, vote, compare, deliberate, and audit the work.

Python · validator orchestration · scorecards · council review

switchAILocal

OpenAI-compatible gateway for routing across model backends and local/remote inference surfaces with cost-aware operational control.

Go · AI gateway · model routing · OpenAI-compatible API

Traylinx Stargate

P2P agent networking layer for distributed AI systems: identity, multi-transport communication, and resilient mesh patterns.

Python · P2P · NATS/libp2p · agent networking

A2A Ruby SDK

Ruby implementation work around Google's Agent2Agent protocol patterns for interoperable service and agent communication.

Ruby · A2A · JSON-RPC · OAuth patterns

2md

AI-ready web-to-markdown ingestion pipeline for turning messy pages into structured context suitable for agents and retrieval workflows.

Node.js · crawling · markdown · data ingestion

Scoutica Skill Card

The machine-readable profile below is the preferred public surface. It exposes capabilities and evidence while keeping private negotiation data out of public HTML.

profile.json evidence.json rules.yaml