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For platform, DevEx, and senior engineers rolling out and using AI coding agents

Make AI coding agents follow your engineering standards - at much lower cost

Context engineering is now a formalized discipline. We give you the operating model to manage it at scale.

One workshop, three things

The kit

the software - full source, yours to keep

The workshop

one live, hands-on day

The know-how

the theory, yours for good

Quick overview

1-day live workshop · Online · scheduled with your team

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The payoff · day one

Stop paying for tokens the task never needed

Scoped context replaces the giant rules file - spend drops from the first session.

You could save, per year

~$8k

10 devs

~$40k

50 devs

~$80k

100 devs

Models use only a fraction of long context - the rest is paid-for noise. Context Rot (Chroma, 2025).

Why choose us?

Not another AI Workshop

  • Company Infrastructure - Manage your AI context supply chain as a governed platform layer.
  • The True Operating Model - Built for teams already using AI agents who need consistency at scale.
  • CI-Validated Governance - Automated gates to test and release rules safely, with instant rollback.
  • Dynamic Context Scoping - Route the right standards to the right task, cutting token waste.
  • Measurable Team Proof - Real telemetry auditing adoption and quality across all repos.

Grounded in an emerging discipline - a 2025 survey of 1,400+ papers - with the governance layer it leaves unbuilt.

Dedicated & Tailored for you

A private workshop, built around your org

  • Private Delivery - Tailored to your tech stack, aligning platform owners and builders.
  • Strategic Timing - Best before procurement, security reviews, or rollout approvals.
  • Pilot Planning Session - 30-min call to map agent sprawl, pick repos, define boundaries.
  • Implementation Support - a 2-week implementation pilot plus 30-day follow-up Q&A, included.
Book a call - see if it fits

Try it - Context Diff

See the blast radius before an AI context change reaches your engineering organization.

A two-line change to an Agent Skill can affect repositories, generated code, security policies, and approval requirements. Modify the skill below and see what the system detects before deployment.

Edit a live Agent Skill and watch risk, blast radius, and approvals update. Runs in your browser - nothing leaves the page.

A normal Git diff shows what changed. The system shows what the change affects- whether it's safe, who must approve it, and how far it reaches - one control inside the governance layer it runs across your org.

The problem - and the fix

Context overload, token burn, standards drift - and no way to govern any of it.

The technical failure modes, and how they bite day to day - each one closed by the same governed pipeline.

Technical

Context & token overload

Rules pile up. Agents get slower, less accurate, and re-send tokens the task never needed.

Solution

Scoped context: maximum efficiency, minimal data - fewer tokens, sharper output.

Standards drift

CLAUDE.md, Cursor rules, and prompts diverge across repos, tools, and developers.

Solution

One reviewed source of truth, auto-delivered to every agent.

No rollback

A bad guidance change ships org-wide with no way back.

Solution

Versioned releases roll out in stages - roll back in seconds.

No proof

Leadership sees AI usage but not whether quality improves.

Solution

Telemetry turns adoption into leadership-ready evidence.

Day to day

The stale design system

Design ships a new API on Monday; agents keep generating the deprecated one all week.

Solution

One auto update propagates to every agent before their next session.

Day-one for a new hire

New hire's agent knows nothing about your conventions; first PRs get shredded in review.

Solution

One setup script and the whole team is aligned instantly.

The tool migration

Team moves from Cursor to Claude Code - every tuned rule evaporates.

Solution

One unified context, compatible across AI tools. Standards follow you.

The repeat PR comment

Staff engineer leaves the same note on agent PRs every week.

Solution

It becomes a validated skill - the agent gets it right first time.

The bill for having no AI organization-wide infrastructure in place

Not just spend: models don't use long context uniformly - accuracy drops as input grows, well before the window is full, so much of a bloated context is paid-for noise. Context Rot (Chroma, 2025).

Illustrative, at ~$3/M input tokens - baseline your real figure in the pilot.

Wasted, per year

≈ $160k / yr

burned on tokens the task never needed

The Assets & The Know-How

The production-ready assets to execute. The strategy to run them.

Working infrastructure to fix AI agent chaos on day one, plus the architectural blueprints to scale it across your org.

What you will get

  • The Complete Kit - Full source context supply chain code, compatible with top AI tools. Yours to keep.
  • Execution Assets - Validation, staged rollout, and pilot-report templates with instant rollback.
  • Telemetry Loop - Private event-level telemetry to track adoption and measure quality signals.
  • Ongoing Access - 30-day follow-up Q&A and private alumni channel post-workshop.
  • Official ACE Certification - Walk away with more than just knowledge. Complete the workshop to receive your official ACE Certified Context Engineer credential.
Preview of the ACE Certified Context Engineer certificate of completion

Your ACE Certified Context Engineer certificate - issued on completion. Tap to view full size.

What that gives you

  • Context Optimization - Stop burning money on massive prompt windows by learning how to feed AI agents only the exact context the task actually needs.
  • Deterministic Routing Context - Ditch unstable embedding-based routing for rock-solid rules that point models to the right domain instantly.
  • Automated Governance - Build automated gates in your current CI pipeline so stale design patterns or outdated security rules never make it to production.
  • Regression Testing - Set up a scheduled testing loop ('Skillgrade') to track AI code regression objectively, without relying on vibe checks.
  • Frictionless Rollouts - Ship the entire system via MDM or a simple setup script so your team gets corporate engineering standards out of the box, with zero friction.

"Finite budget" isn't just ours - it's how Anthropic frames context engineering. Effective context engineering, 2025.

How it works

One source of truth. Every agent stays current - automatically.

A context supply chain with two properties engineers feel on day one - plus the governance your security team will ask about.

01 · domain-aware

It knows what you're working on

The system detects the domains in front of the engineer - frontend, backend, platform, security - and delivers only the standards that apply. No thousand-line prompt file.

Smaller, sharper context means fewer tokens burned and cleaner output - every session, every engineer.

Why smaller wins: models attend unevenly to long inputs, losing signal in the middle. Lost in the Middle (2023).

02 · self-updating

It keeps itself current - nobody manages versions

Standards are written once, centrally, reviewed like code, and shipped as versioned releases. Every machine stays in sync - approved changes reach the agent before the next session.

No packages to publish, no dependency bumps, no update anyone has to remember. Onboarding is one script. Versioned for the platform team, versionless for engineers.

What that looks like in a monorepo

agent session · monorepo

$ cursor "add rate limit to /login and its form"

[context] detected domains: frontend, backend

[context] checking for changes…

backend/api-security   changed → regenerate

frontend/forms       changed → regenerate

backend/logging      unchanged → skip

frontend/design-sys  unchanged → skip

2 skills refreshed · 6 unchanged, skipped

agent ready on current standards

Touch two domains, get exactly two domains' worth of current standards.

  • Detects the domains you're actually working in.
  • Rebuilds only the skills that changed since your last session.
  • Skips everything unchanged - no full-repo prompt dump, no manual updates.

Agenda

Eight modules. Every one ends in a lab.

No slideware marathon - but the theory isn't filler:2h 40m of durable principles you keep for good, and3h 55m of hands-on labs where you do it yourself. Here's what you leave with:

■ theory 2h 40m·■ hands-on labs 3h 55m

  1. 01

    Foundations - why it works

    25′ theory · 10′ lab

    Map real agent failures to the LLM principle each violates, and decide skill-vs-gate before you've seen the tooling.

  2. 02

    The Drift Problem

    25′ theory · 20′ lab

    Trace how one standard moves from ownership to approved agent guidance.

  3. 03

    Corpus & Registries

    20′ theory · 40′ lab

    Add a new domain of standards and work through the governance checks that keep it safe.

  4. 04

    Generation & Validation

    15′ theory · 30′ lab

    Break sample guidance in controlled ways and see which validation layer catches it.

  5. 05

    Activation & Routing

    20′ theory · 40′ lab

    Tune routing language so the right guidance appears for the right work and stays quiet otherwise.

  6. 06

    Distribution & Rollout

    20′ theory · 40′ lab

    Move a context change through rollout and practice the recovery motion.

  7. 07

    Governance & the Policy Boundary

    20′ theory · 25′ lab

    Sort ten real engineering rules into "skills guide" vs. "CI enforces" - and defend your calls.

  8. 08

    Pilot, Telemetry & Evidence

    15′ theory · 30′ lab

    Simulate a pilot week and decide whether evidence justifies wider rollout.

AI Context Engineering, without the hype

One email a week: practical architecture, research, and engineering signal - plus workshop updates.

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Who it is for

Built for the people who own engineering standards.

Platform, DevEx, and staff engineering own the standards. But the system scales down just as cleanly - pick your entry point:

path 01 · on-ramp

The single owner

  • Context engineering is becoming a core skill you carry to every project and job.
  • Start as the one person who owns your team's AI standards.
  • Run the lightweight slice first, add rollout and measurement when ready.
  • Grow into full org rollout without migrating to a different system.

A real shift, not hype: vendors now call context engineering the successor to prompt engineering. Anthropic, 2025.

Public seats are closed - get notified about the next cohort →

path 02 · the primary path

The rollout team

  • Adoption sticks when the future co-owners train together: the people behind standards, tooling, and governance leave with one shared operating model - not three interpretations of it.
  • Staff / principal engineer - owns the standards.
  • Platform / DevEx engineer - owns rollout and installs.
  • Engineering manager / security - owns governance and sign-off.

Fits: a Private Company Workshop → your co-owners, one room

path 03 · go company-wide

Train everyone, not just the owners

Knowing how agents use context is becoming core engineering fluency. A private workshop trains your owners and builders together, tuned to your stack.

Book a 30-minute pilot planning call. We'll map your agent sprawl, choose a repo set, define boundaries, and decide the right format.

Best before procurement, security review, or broader rollout approval.

Book a private workshop

Recommendations

AI-assisted engineering is becoming the standard way of building software, and one of the most important things is how well you manage context. I have known both Daniel and Jaroslaw for quite some time now, and can attest to their expertise and professionalism. I've also taken a close look at the course material, and I really like how practical it is. If you're looking to optimize the way you are doing AI-assisted engineering, this is the course for you!
Portrait of Gregor Ojstersek

CTO · Founder of the Engineering Leadership newsletter (190k+ subscribers)

I spend my time on conference stages and inside other people's codebases, and it's always the same failure modes: prompts cargo-culted between repos, skills that quietly slow every agent down, a bad rule shipped org-wide with no way back, and adoption measured by vibes. This is the first thing I've seen that names those anti-patterns and builds the pipeline that closes them - the operating model I keep wishing my clients already had.
Portrait of Dawid Perdek
Dawid PerdekMicrosoft MVP

Senior Software Consultant · Conference Speaker

We've all accumulated random AI docs and CLAUDE.md files over time. Having a structured approach to managing that knowledge made a real difference as teams scaled their AI usage.
Portrait of Przemysław Sokołowski

Lead Software Engineer · Synergy Codes

It is incredibly frustrating when you know exactly what you want from an AI, but without the right context, it just falls back on broad assumptions - giving you irrelevant answers and wasting tokens in the process. We are all trying to figure out how to integrate these tools into our workflows, which is why taking the time for dedicated workshops is an absolute necessity today. Learning exactly how to build and optimize context is what shifts us from merely testing AI to actually steering our agents with precision and efficiency.
Portrait of Łukasz Boduch

Chief Architect · SoftServe

Instructors

Led by practitioners who understand enterprise constraints.

Portrait of Daniel Glejzner
2× Microsoft MVP

Principal Consultant & Tech Lead

10+ yrs25 clients
Portrait of Jarosław Żołnowski
Google Developer Expert

Lead Technical Architect

19+ yrs21 clients

Enterprise experience

29+

years combined

46

client engagements

20+

talks at international conferences & meetups

Selected cooperations

A selection from 46 engagements - many under NDA.

International conference speakers

Conference photo full size

Speaking at conferences across Europe and beyond on AI engineering, Angular, and platform architecture.

Need more than a workshop? Plan the pilot with us.

On-site audit, a customized adoption approach, and hands-on support for first rollout.

Book a pilot planning call

Pricing

One way to work with us: a private workshop for your company.

All prices excl. VAT. Scope and final price are set on the planning call.

Individual seats

Closed

Enrollment for the first cohort is closed. Individual seats and the team bundle are no longer sold. The second cohort will be announced separately - join the list and you'll hear first.

1-day live workshop · Online · scheduled with your team

Get the next cohort first

We'll email you when dates and pricing for the second cohort are announced.

We'll only email you about the next cohort, unsubscribe anytime. See our Privacy Policy.

Need it sooner, or for a team? A private workshop → runs on your schedule.

Supported by

Partners backing our work and community

  • Angular Space
  • Relocate.me
  • Engineering Leadership

FAQ

Questions before you book.

What exactly am I buying? Is it an app, or just some MD files?

Three things in one engagement: the complete context supply chain kit (a git repo of scripts, CI checks, and staged releases - full source, not slides), the live one-day workshop where your people operate it on a worked example, and the architecture behind it so your team can adapt it to your own standards afterwards. The kit isn't sold separately - the workshop is the only way to get it. Full breakdown in the “The Assets & The Know-How” section above.

Is this just another AI coding course?

No. Courses teach individual habits; this installs the governed pipeline around your company standards - ownership, CI validation, staged rollout, freshness, rollback, and measurement. You still learn hands-on, but you leave with the working kit, not just tips.

When is the workshop, and how long does it run?

It is a 1-day live workshop, online. Private company workshops are scheduled with you on the planning call - usually a few weeks out. The first public cohort (September 8, 2026) is closed to new enrollments.

Can I buy a single seat?

Not right now. Individual seats and the team bundle are no longer sold. The second cohort will be announced separately - join the list and you'll hear first. What is bookable today is the Private Company Workshop: delivered for your organization, tuned to your stack, with a 2-week implementation pilot included.

When is the second cohort?

It will be announced separately, with its own dates and pricing - we are not taking seat sales for it yet. Add your email in the pricing section (or subscribe to the newsletter) and you will hear about it before it goes public.

Is it live? Do I get a recording?

It is live and hands-on - you operate the kit yourself in guided labs, on a worked example. All templates, lab material, and the kit you take home are yours to keep. Sessions are not recorded unless we confirm otherwise in writing before the workshop begins, and participants may not record, stream, capture, or transcribe the session (including screenshots and AI note-taking bots) without prior written consent. The lasting value is the kit and materials you keep, not a video.

What if the date stops working for us?

Full refund up to 14 days before the workshop date. Inside that final 14-day window it switches to rescheduling - we move your private workshop to the next date that works for your team. Individual participants can always be swapped for colleagues at no cost.

Can't we just write a CLAUDE.md or rules files ourselves?

You can - and most teams start there. The problem isn't writing the rules, it's everything after: copies drift apart across repos and tools, nothing validates changes before agents consume them, there's no staged rollout or rollback, and nobody can measure whether agents actually follow the rules. The workshop gives you the operating model around the files - versioning, validation, distribution, telemetry - in one day instead of months of trial and error.

How is this different from an AI coding foundations workshop?

Foundations workshops teach engineers how to use agents better: prompting, context windows, hallucination prevention, MCP, and local project setup. This workshop starts one layer higher. It teaches platform and engineering leaders how to run a context supply chain as company infrastructure: owned, validated, released, rolled back, and measured across teams, repos, and tools. If your team is still learning the basics, foundations training is useful. If you already have agents in use and need consistency, governance, and proof, this is the operating model.

Won't a pile of skills just slow the agent down and burn tokens?

It absolutely can - we've watched a senior developer install a stack of skills, watch every prompt get slower and more expensive, delete them all, and go fast again. That's the trap - and it isn't only about cost: attention is finite even when the window isn't, so the more you pile in, the more the rule that actually matters for the task at hand gets buried and ignored. This system is built around scoped guidance instead: shared rules stay small, domain guidance is routed by the work at hand, only the skills that changed get regenerated, and the pilot tracks whether the right guidance is actually activating. You stop guessing which rules help.

How does it pick the right context - embeddings or rules?

Two layers, and neither is a black box. Scoping - which domains of standards apply in a repo - is deterministic and signal-based: the same repo resolves the same way every time, with an explicit override for monorepos. No embedding lottery, no per-run drift. Which specific rule then activates for a given prompt is the agent's own call from each rule's description - the probabilistic layer - which is exactly why we measure activation and eval it rather than assume it.

When you change a shared rule, how do you know output got better, not just different?

Three layers, and we're honest about each. Structure is gated automatically before anything ships, so a change that would break the corpus fails fast. Behaviour is checked with agent evals - multiple trials, rubric-graded - for the rules that justify the cost, run on a schedule rather than as a blunt per-commit gate (agent evals are slow and non-deterministic). And in a pilot, redacted telemetry shows the trend on real work. We don't pretend CI proves quality: CI proves the change is valid, evals catch regressions, telemetry shows the trend.

Is “context engineering” a real discipline, or just hype?

Real, and newly formalized. A July 2025 academic survey (Mei et al.) synthesized over 1,400 papers into a defined discipline: context as a finite, structured resource you assemble and optimize, not a static prompt. What the literature has barely touched is the operational layer - governing, versioning, and distributing that context across a whole team - which is exactly what this workshop and kit build. Reference: arxiv.org/abs/2507.13334.

How is this different from MCP?

Different axis. MCP gives agents capabilities: tools and live resources at runtime. This system governs standards: the company guidance agents should follow across repos and tools. Most mature teams eventually need both. MCP is a capabilities layer; this is the standards-governance layer.

If engineers never bump a version, how is any of this controlled?

Control stays with the platform team. Changes move through reviewed releases and staged channels, while engineers avoid per-repo update work. The workshop teaches the rollout and rollback motions so the system is governed centrally without becoming busywork for every developer.

What do our developers actually have to do?

Almost nothing. Once, they run a single setup script - or you push it to their machines through your existing MDM / managed-device tooling, so it's already there and they do nothing at all. After that it's invisible: the right standards load into their agent automatically, refreshed before each session. There's no system for them to learn, no versions to bump, no per-repo files to maintain. The platform team owns the pipeline; everyone else just codes.

Does it touch anything else on engineers' machines?

It is designed to avoid modifying application repositories. The install path is user-level, controlled by your organization, and can be disabled if your rollout policy requires it. The workshop covers the operational boundaries so platform and security reviewers know exactly what is in scope.

What happens after the workshop?

Every participant gets a 30-day follow-up q&a call with the instructors and access to the private alumni channel, on top of the templates and the kit you take home. The private workshop additionally includes a rollout roadmap and a 2-week implementation pilot for your organization; we can also set the kit up on your standards as a paid add-on.

Can you help us run the first rollout?

Yes. The Private Company Workshop includes a 2-week implementation pilot: we help your owners select a small repo set, define baseline metrics, install the pilot channel, review activation telemetry, and turn the result into a leadership-ready rollout recommendation. The point is not to promise generic ROI; it is to prove whether the system works in your environment.

What do I need to know or bring?

Comfort with git, a terminal, and JSON, plus a recent Node.js (v20+) installed - every lab tool is a single dependency-free script, so there is nothing else to set up. No specific coding agent or IDE is required.

Is this only for large enterprises?

No. Smaller teams can still get the core value: standards written once, current across their agent setup, and easier to review. Larger organizations use more of the governance, rollout, and measurement layers as they scale.

How do we book you for our team?

The Private Company Workshop is the format: from €15,000 (launch price), sized to your company and scoped on a 30-minute planning call - tailored to your platform and including a context architecture review, a rollout roadmap, and a 2-week implementation pilot to prove the rollout in your repos. It works from a handful of platform owners up to a company-wide rollout. We also take direct consulting engagements: an on-site audit of your AI coding setup, a customized adoption approach, and team training.

How do payment, invoices, and VAT work?

Private workshops are invoiced: we send a quote after the planning call, then a VAT invoice with your company details and VAT ID. Bank transfer, purchase orders, and vendor onboarding are supported, and card payment is available on request. All listed prices are excl. VAT; EU businesses with a valid VAT ID are reverse-charged (0% invoiced, you self-account).

I'm an individual - is there anything for me?

Not at the moment: we only sell the private company workshop, and individual seats are closed until the second cohort is announced. Put your email in the pricing section and you'll be told when seats open again. If you're employed, the other route is your employer booking a private workshop - the manager brief is written to be forwarded for exactly that conversation.

Private workshops

Book a private workshop for your company.

Enrollment for the first cohort is closed, so the private workshop is the way in - tuned to your stack, scoped on a 30-minute planning call, with a 2-week implementation pilot included.

1-day live workshop · Online · scheduled with your team · 30-day follow-up Q&A call with the instructors

Not a company decision yet? Grab the full outline above, or send the manager brief to your decision maker. Waiting on the second cohort? Get notified when it's announced.