AI Workshops, Tranings, and Enablement

The AI Excellence Program: The Dual Training Path to AI Maturity

“Using AI” is not enough on its own. You need safe, strategic integration within your business. STX Next’s AI Excellence Program is built around two training paths for technical and non-technical roles, so your organization moves from experimentation to maturity with clarity and depth.

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Gemini company logo

Gemini

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GPT

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Copilot Studio

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n8n

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Power Automate

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Claude

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Copilot

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Program structure

Two dedicated training paths

Same ambition, different depth. Technical teams go deep on SDLC, code, and secure integration. Business teams master prompts, assistants, and agentic workflows with no/low-code interfaces.

01
TECHNICAL

For technical people

Engineers, architects, DevOps: The AI Bootcamp

  • AI across the SDLC & security guardrails
  • Quality-first coding with LLMs & tooling
  • Advanced integration & architecture patterns
02
Non-technical

For non-technical people

PMs, analysts, ops, HR, marketing: AI Enablement for Business

  • Precision prompting, RAG, and grounded use
  • Task-specific assistants (e.g. Copilot Studio)
  • Agents & automation (Power Automate, n8n)
What the training covers

Prompt Engineering

Context, roles, patterns, and grounded prompts that hold up at work.

Assistants

Task-specific copilots and assistants tuned to your workflows.

Agents

Multi-step agent flows, tools, hand-offs, and guardrails.

Automation

Connecting systems with automation (e.g. Power Automate, n8n).

Augmented Coding

LLM-assisted SDLC: design, implementation, review, tests, security.

Beyond standard tracks

Bespoke / tailored programs

Alongside the two defined paths, we design custom engagements around your organization’s reality: goals, toolchain, and governance, not a one-size-fits-all slide deck.

  • Agent archetypes: focus on the kinds of agents and assistants your teams will actually build and run (e.g. intake, research, ops, compliance-aware workflows).
  • Your automation toolset: exercises and patterns aligned with your stack (connectors, IDP, ticketing, CRM, data platforms you already use).
  • Technology choices: modules and labs tuned to models and vendors from your approved stack, not generic defaults.
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Schedule

Duration & suggested cadence

Each path has a clear time box so you can plan calendars and minimize disruption. Exact slots are agreed with your executive team, managers, or L&D team.

20 hours
TECHNICAL path

The AI Bootcamp: SDLC, secure integration, quality-first coding, and advanced tooling.

Recommended formats
  • 4 days × 5 hours per day or
  • 5 days × 4 hours per day
16 hours
Non-technical path

AI Enablement Masterclass for Business: prompting, assistants, and agentic workflows for business roles.

Recommended formats
  • 3 days × ~5 hours per day, or
  • 4 days × ~4 hours per day
Workshop objectives

What you will achieve

By the end of this program, your organization moves from AI consumers to AI Architects and an AI-augmented Workforce.

For engineers

Standardize AI across the SDLC for higher-quality code and faster delivery, without compromising security.

For business professionals

Master autonomous agents and prompting. Delegate complex work to “virtual employees.”

For the organization

Build a “Virtual Agentic Platform,” a library of internal agents that drives continuous digitalization.

For independence

Own the skills to build and maintain these systems, with less long-term vendor lock-in.

At a glance

Training agendas

Condensed outlines for both paths. The agenda links on each path card jump straight to the matching outline below.

The AI Bootcamp

20 hours | hands-on Training, Coding Agents orchestration

Short demos plus real implementation work, aligned with our public STX Next AI Bootcamp.

  1. Day 1. Project planning, context engineering, prompts, environment and tooling, UI exploration.
  2. Day 2. Backend: scaffolding, services, REST API, tests, debugging.
  3. Day 3. Frontend: UI, API integration, forms and validation, automated testing.
  4. Day 4. Catch-up, optional LLM tooling topics, summary and feedback.
  5. Q&A. Applying the workflow to your own projects.

AI Enablement Masterclass for Business

16 hours | agents & automation, prompting, assistants

For roles that do not ship code: grounded prompting, task assistants, lightweight agents, and automation using tools your organization already licenses.

  1. Block 1. How LLMs work in practice: limits, parameters, and realistic expectations.
  2. Block 2. Better prompts: context, roles, and removing ambiguity.
  3. Block 3. Reusable patterns: structure, examples, step-by-step reasoning when it helps.
  4. Block 4. Safer outputs: guardrails, grounding, and controlled formats.
  5. Block 5. Operations: working with documents, assistants, and security-minded habits in the enterprise.
  6. Block 6. Building AI agents: defining goals, tools, and hand-offs; prototyping multi-step flows in low-code platforms (e.g. Copilot Studio, Power Automate, n8n) without writing application code.
Training environments

Choose where the workshop runs

One curriculum. During discovery we fix the hosting model and toolchain so exercises mirror what your teams keep using after the workshop.

SaaS path

Typical picks are Google (Gemini) and Microsoft (Copilot, Power Platform) when that matches procurement and governance.

Your boundary

On-prem, private cloud, or air-gapped setups use only components your security and platform teams approve.

What flexes

Labs, connectors, model endpoints, identity, and guardrails. Learning outcomes stay the same.

Hyperscaler & managed SaaS

Public cloud & SaaS

Best when M365, Google Workspace, and managed APIs are already how you work. Sessions follow your tenant, identity, and data policies.

Examples in labs
Copilot Studio
Gemini Gems
Power Automate
n8n
Claude Cowork
Google Workspace Studio
Your infrastructure

Private, on-prem & isolated

Best when workloads must stay inside your network or run without public internet egress. Everything stays inside boundaries you define.

Examples in labs
Open WebUI
Ollama
OLM OCR
Internal gateways & APIs
Methodology

“Plug & play” learning

Learning by doing. We handle the heavy lifting.

Participants only need a browser. Roughly 80% of the time is about building hands-on; no death by PowerPoint, guaranteed. After the workshop, teams keep templates and sources for every agent and assistant created in-session.

What we provide

Full infrastructure

Accounts, models, and tokens so you can focus on outcomes, not setup.

Hands-on labs

Real workflows, not slide-only sessions.

Asset library

Reusable templates and sources to deploy immediately.

Business benefits
  • Accelerated digitalization: assistants become durable internal assets.
  • Lower operational cost: automate repetition; free time for strategy.
  • Risk mitigation: safer AI practices for data and reliable outputs.
  • Sustainable transfer: optional post-workshop hours with our experts.
  • Accelerated digitalization: assistants become durable internal assets.
  • Lower operational cost: automate repetition; free time for strategy.
  • Risk mitigation: safer AI practices for data and reliable outputs.
  • Sustainable transfer: optional post-workshop hours with our experts.

Our Approach: Why STX Next?

Architect-Led

Every project is guided by a senior architect who focuses on the business problem first, not the tool.

Vendor Agnostic

Whether it’s AWS, Azure, GCP, or on-prem, we recommend what is right for your performance and cost requirements.

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Structural Savings

We don't just find one-time discounts; we fix the underlying architecture to ensure costs don't drift back up.

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Transparent Collaboration

We use Agile/Scrum workflows, giving you full visibility into our progress through every sprint.

Proven Problem Solvers

A track record of successfully untangling complex legacy systems, architecting for massive scale, and delivering innovative features others deemed impossible.

Who We Partner With

AI, Data, Automation, and Cloud platforms we work with to modernize operations and enable AI adoption.

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AWS

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Azure

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n8n

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stackit

Let's talk

Schedule a chat with our Head of AI and to discuss your training needs.

Tomasz Jach
Head of AI/ML
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FAQ

What are the advantages of applying AI to my business?

Leveraging AI development services can transform your business operations by automating routine tasks, enhancing operational efficiency, and reducing errors. Our AI models and custom AI solutions provide businesses with intelligent insights for predicting customer preferences, fostering business growth, and enhancing the overall customer experience.

Why invest in AI?

Investing in AI software development services enables businesses to scale efficiently, reduce errors, and enhance customer service through automation and intelligent solutions. Staying current with AI technology is essential for maintaining competitiveness, ensuring your operations remain efficient and relevant in a fast-paced environment.

What are AI services?

AI services involve cutting-edge AI solutions, including natural language processing, computer vision, and predictive analytics, to solve business challenges, automate tasks, and enable smarter decision-making. Our comprehensive AI development services cater to various industries, providing custom AI solutions for finance, healthcare, manufacturing, and retail.

What is an example of AI as a service?

AI as a service, such as predictive analytics, uses machine learning to forecast trends, helping industries like retail manage inventory efficiently. By analyzing past sales data, AI software can predict product demand and optimize stock management, boosting profitability and customer satisfaction.

How much does an AI service cost?

The cost of an AI service varies based on complexity and business needs. At STX Next, we mostly start with a low-cost Proof of Concept (PoC) to assess feasibility and effectiveness using your data. Our unique approach ensures high success rates and ROI:

  • Proof of Concept (PoC): Quickly and affordably evaluates the AI system’s potential.
  • Workshops: Refines requirements and develops a detailed implementation plan.
  • Full-Scale Project: Optimizes the AI solution for maximum effectiveness.

By beginning with a PoC, we avoid the pitfalls where 60% of immediate full-scale projects fail, and 90% don't generate ROI. Typically, costs can range from a few thousand dollars for small projects to several hundred thousand for large, enterprise-level solutions.

What are the types of collaboration you offer?

As a leading AI development company, we offer flexible collaboration models, including team extension for ongoing support, project-based cooperation for specific AI implementation needs, and AI consulting to align AI strategies with your business goals.

What is STX Next’s unique AI proposition?

STX Next stands out as a trusted AI software development company, offering tailored AI development services with a focus on comprehensive AI development, from generative AI models to custom AI implementations. Our experienced AI developers and data scientists leverage advanced AI and ML techniques to deliver innovative solutions, ensuring your AI projects achieve measurable value and drive business growth.

How does STX Next ensure compliance with regulations?

We prioritize compliance by integrating AI solutions that adhere to GDPR, AML, PSD2, and SEC regulations. Our commitment to responsible AI practices ensures our custom software development aligns with regulatory standards, mitigating compliance risks for our clients.

How can AI integrate with existing systems?

Our AI app development services aim for smooth integration with your existing systems, utilizing AI-powered tools and technologies to enhance operational efficiency without disrupting your current business processes. We specialize in developing innovative solutions that align with your business intelligence goals.

What ongoing support does STX Next provide for AI projects?

Beyond initial deployment, STX Next offers continuous support for AI-powered solutions. Our project management approach includes regular updates, AI system optimization, and assistance in adapting to emerging challenges, ensuring long-term success for your AI development project.

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FAQ

Who should attend each track?

The Technical Track fits software engineers, architects, and DevOps engineers.

The Non-Technical Track fits PMs, analysts, operations, HR, and marketing: anyone owning prompts, assistants, and workflow automation without shipping app code.

What do participants need on their laptops?

Only a web browser. STX Next provides accounts, models, and tokens so teams can focus on building.

If you have your own setup and preferences, we can use that instead.

How much is hands-on?

About 80% labs and building; the rest frames context, patterns, and governance for repeatable outcomes.

We're not aiming to teach only theory.

What do teams take away?

An asset library: templates and sources for every assistant and agent built in the workshop.

Security and data handling?

Safe AI practices are built in, especially SDLC security in Track 1 and grounding/RAG patterns in Track 2. Controls can align with your organization’s policies during discovery.

Do you offer ongoing support?

Yes. An optional post-workshop support package with a defined number of expert hours for real-world rollouts.