Stop mincing garbage. Learn 3 proven methods for #Automation, #AIAgents, and #ProcessIntelligence to find processes worth fixing. #RPA #GBS #SSC 

Most companies fall into the "Excel Trap" - sending out surveys to managers and getting back automation ideas that are either impossible to build or have zero ROI. In this episode of The AI Automation Dojo, Andrzej Kinastowski explains how to stop clogging your pipeline with "usual suspects" and start finding real gold nuggets in your organization.

We break down the three specific paths used at Office Samurai to audit corporate reality: the "Long Blade" (Full PD) for deep multi-year roadmaps, the "Short Blade" (Quick PD) for 2-day surgical sprints, and "Digital Sensors" KYP) to catch the messy truth of daily tasks. This episode is a must-watch for leaders in Operations, GBS/SSC, HR, and Finance who want to move from "experimenting with tech" to delivering "CFO-proof" business results.

What you will learn from this episode:

🔸 How to avoid the "Excel Trap" and why your current pipeline might be clogged with garbage

🔸 The "Samurai Criteria": Identifying tasks that are truly ready for RPA, AI, and digital agents

🔸 Shadowing vs. SOPs: Why Level 4 analysis finds the real ROI that documentation misses

🔸 The 2-Day Sprint: How to identify 10 automation candidates and fix "seams" between teams

🔸 Strategic Projects: When to use AI and agents for processes requiring "judgment"

🔸 Process Intelligence (KYP) as the ultimate "Bullshit Detector" for data-driven arguments

 Because the goal isn't to automate waste. It’s to sharpen your strategy so that every strike cuts clean through the problem.

Are your AI investments actually paying off? In this episode of #AIAutomationDojo, we deconstruct the #ModelWars and explain why traditional #RPA is hitting a wall.#AIAgents #GenAI #ROI #LightAGI

In this episode, Andrzej Kinastowski and Krzysztof Karaszewski deliver an "autopsy report" on the state of automation. They explore why the speed of AI development has made tools from just six months ago feel like ancient history. The conversation moves beyond the hype to discuss how "vibe coding" and agentic systems are allowing individuals to build systems that once required 1,500 hours of manual labor in just a few evenings.

For who? This deep dive is specifically designed for COO/CFOs looking for twarde ROI, CAIOs trying to escape "Pilot Purgatory" and Heads of Automation whose RPA pipelines have gone dry. Whether you are managing application license waste or trying to find vertical agentic use cases, this episode provides the strategic "diagnostic X-ray" your organization needs.

When you hear “productivity mining”, the first thought might be surveillance. But in practice, it’s much more about transparency and knowing what’s really going onin your teams. 

In this episode, we speak with Elena Olichowska-Szydłowska,Automation Excellence Manager at Vesuvius, about what it actually took to roll out task mining across Shared Services.From dealing with IT security, to communicating clearly with teams, to getting managers to act on real data – this is the unfiltered version.

We discuss:

• Why Vesuvius chose task mining over traditionalprocess mapping
• How Elena’s team handled employeeconcerns about being monitored
• What changed once leaders saw the workload data
• How the company reached break-even in 6 months
• What kind of findings led to better team balancingand workload reallocation

This is not a theoretical discussion – it’s a look into the operational and human aspects of rolling out task mining at scale.

Do you trust AI? Like… really trust it?

In this episode of The AI Automation Dojo, Andrzej Kinastowski, co-founder of Office Samurai, takes a katana to one of the biggest lies in enterprise AI. The idea that you can just let agents loose and hope nothing catches fire.

Imagine you are looking for a perfect product on the Internet. A lawn mower, like Andrzej did. A polite, confident AI helped research it, compare the models, read users reviews, and recommend the best one. It had perfect specs, a good price, but one small issue. It did not exist.

From there, Andrzej gets serious about what actually works today. Not sci-fi agent swarms. Not “just trust the model.” 

He talks about real automation for ticketing systems and shared inboxes, built with one simple rule: AI does the work. Humans stay in control.

You’ll hear how to:

🔸 Automate service desk tickets without hallucinated answers

🔸 Use AI to answer questions and execute actions, but only after proper approval

🔸 Handle password resets, SAP access, and onboarding without human button-mashing

🔸 Keep employees as guardrails instead of copy-paste machines

🔸 Run multilingual support queues without speaking every language on Earth

This episode breaks down a practical “human in the loop” setup that already runs in production. Jira tickets. Approval flows. RPA robots. 

No magic, no blind trust, just systems that follow your rules and stop before they do something stupid.

If you’re tired of being told that fully autonomous AI is “basically ready,” this one’s for you.

Because the goal isn’t AI that takes over. It’s AI that does the heavy lifting while you click approve.

Ticket closed.

In this episode we dive straight into the everyday reality of running AI projects, with Dagmara Sysuła, Delivery Manager at Office Samurai, as your guide. 

If you’ve ever tried to run an AI project the same way you run RPA or IT delivery, you already know how that story ends. AI refuses to behave. And Waterfall? It taps out early.

Dagmara walks through why AI needs a different kind of steering. These projects live on experiments. They shift. They surprise you. And unless you mix Agile discovery with the reporting discipline your sponsors demand, you end up with a confused team, an annoyed CFO, and a solution that never leaves dev.

The four types of AI projects we keep seeing are:

1. POCs and quick tests: two or three weeks to see whether the idea breathes or just gets sucked into the black hole.
2. Full deployments: big, messy, political, and the ones that actually move the needle.
3. Buying tools: buying the license is easy. Buying the knowledge to use it well is harder, and most companies skip that part.
4. Strategy work: setting guardrails, deciding where AI fits, and lining up the ethics and processes. This shouldn’t wait until “later.” It has to run next to the early delivery work so the strategy is shaped by reality, not PowerPoint.

That is why Dagmara came up with the 10 rules that can help put the puzzles of the AI project into the perfect place. Straight from the field, far from theory. 

We won’t spoil them that much in the description, so that you can get to know them yourself. ;) 

AI moves fast enough that these rules may look different a year from now. But for now, they’ll keep your AI projects from drifting into the usual swamp of confusion, hype, and half-finished work.

Listen to the flaming discussion between Andrzej and Dagmara to deliver you AI projects better. And faster. 

What do we really want to measure and how to do that?

This question belongs to Zuzanna Pamula, Process Transformation Manager at Office Samurai. 

When she started her career in process improvement, she thought she had it all figured out: data from enterprise systems, colorful dashboards, and enough KPIs to fulfill a Six Sigma dream. 

For a young analyst, it felt like going to Disneyland for the first time… until she realized that all her numbers were only showing the visible tip of a much bigger and messier iceberg.

The questions arose:

🔸 How much do people actually work? 

🔸 Where do they waste time? 

🔸 What happens between systems, outside of the ERP logs, in the real digital trenches of copy-paste, waiting, rework, and silent frustration?

She did what every Lean Six Sigma purist would do: measurement. She shadowed people at their desks, designed perfect Excel templates, and begged for time tracking compliance.

Guess what? It didn’t change anything. 

Because what she measured was how people SAID they worked – not how they ACTUALLY worked. Fear, bias, and corporate self-preservation kicked in. Everyone gave polished numbers that always added up to exactly eight hours a day. Pure fiction. 

That’s when she learned the hard truth: in most companies, process measurement is less about improvement and more about storytelling – the kind that makes managers feel safe.

And then, the horsemen of success arrived: technologies such as Task Mining, Process Mining, Productivity Intelligence.With those tools you could see the real process. The kind that reveals what’s actually slowing you down, not what people wish was true.

Because when you look at real data, you find things you didn’t expect:

🔸 People spending half their day in non-value-adding meetings 

🔸 Constantly checking and replying to emails which feels productive, but is it really?

🔸 Work fragmented across a dozen tools that were supposed to make life easier, but ended up eating more time than they save.

Zuza calls them the “(Un)expected Findings” – and every organization has them.They’re not about catching people on a lie. They’re about facing the truth.

In this episode, Zuza takes us from her early Lean days – measuring work with pen and stopwatch – to the present, where AI and data analytics finally let us measure how work really happens. She talks about the illusions of productivity, the small human hacks (like mouse jigglers), and the uncomfortable (but liberating) truth that comes when data replaces opinion.

This isn’t just an episode about process improvement. It’s about the courage to measure what’s real.

How well do you really know your processes?Most leaders rely on reports, meetings, and gut feeling but the real picture of how work gets done is still hidden in the data.In this episode of AI Automation Dojo, Andrzej Kinastowski talks with Adam Bujak, CEO and co-founder of KYP.ai, about how modern AI tools are changing the way organizations understand and improve their operations.The conversation also goes deeper into what it means to lead with data, build trust and transparency inside teams, and use AI to empower people instead of replacing them. It’s a practical look at how leadership and technology are evolving together, across every industry.We discuss:🔸 Why process discovery still fails in many organizations🔸 What “data-driven leadership” really means in daily operations🔸 How AI helps uncover hidden patterns and recognize silent top performers🔸 How to balance automation with privacy and trust🔸 What generative AI actually changes in process intelligence (and what stays the same)

Most video games today feel like déjà vu with better lighting. Sequels, remasters, recycled ideas wrapped in shinier engines. You know the pattern – Dying Light with more parkour and zombies, Far Cry giving you another dictator to overthrow, and Assassin’s Creed sending you to take a leap of faith into history for the 12th time.Well, it could be worse – like Silent Hill f, with its repetitive bosses, clunky combat, and a storyline so glued to Asian folklore that you spend more time Googling 1960’s Japanese books for kids to get hints than actually playing.It’s the same loop for most AAA titles: big budgets, big promises, small soul.And then, out of nowhere, you hit the “Whoa” moment.Clair Obscur: Expedition 33. A game that shouldn’t have been possible – made by 30 people in France, on a fraction of the usual budget. No corporate roadmap. No marketing empire. Just a small team with a clear vision and something to prove.What they created wasn’t just another RPG. It was art in motion.The visuals felt like a living painting. The music didn’t just accompany the story – it was the story. Every emotional note hit right where it should. Every character felt like a person, not a trope. It was about something studios often forget: meaning.The result? 9.7 user score on Metacritic. 5 million copies sold. And a stunned industry wondering how a tiny team did what 500 people couldn’t.This episode isn’t a fan review. It’s a story about how Clair Obscur: Expedition 33 rewrote the rules – and what its creators can teach anyone building products, leading teams, or just trying to make something that matters.We break it down into three simple rules:1. Make the thing you love and really want to use.2. Hire the spark – teach the skill.3. Hire smart people, then get out of their way. You’ll also hear about:🔸 The broken economics of AAA gaming – and how it mirrors corporate stagnation everywhere.🔸 The quiet power of creative freedom and why most leaders are terrified of it.🔸 Why inexperience might just be your biggest advantage.This isn’t just about gaming. It’s about leadership, creativity, and the art of trust.And if you do one thing after listening – check out this soundtrack. Let the “dim, dim, dam” echo in your ears a bit longer: https://music.youtube.com/playlist?list=PLox5pGvBTF_Unzs_XhD5Qm2DW5N6OLCvl&si=4m4tDqgFrU0efB2x

Most video games today feel like déjà vu with better lighting. Sequels, remasters, recycled ideas wrapped in shinier engines. You know the pattern – Dying Light with more parkour and zombies, Far Cry giving you another dictator to overthrow, and Assassin’s Creed sending you to take a leap of faith into history for the 12th time.Well, it could be worse – like Silent Hill f, with its repetitive bosses, clunky combat, and a storyline so glued to Asian folklore that you spend more time Googling 1960’s Japanese books for kids to get hints than actually playing.It’s the same loop for most AAA titles: big budgets, big promises, small soul.And then, out of nowhere, you hit the “Whoa” moment.Clair Obscur: Expedition 33. A game that shouldn’t have been possible – made by 30 people in France, on a fraction of the usual budget. No corporate roadmap. No marketing empire. Just a small team with a clear vision and something to prove.What they created wasn’t just another RPG. It was art in motion.The visuals felt like a living painting. The music didn’t just accompany the story – it was the story. Every emotional note hit right where it should. Every character felt like a person, not a trope. It was about something studios often forget: meaning.The result? 9.7 user score on Metacritic. 5 million copies sold. And a stunned industry wondering how a tiny team did what 500 people couldn’t.This episode isn’t a fan review. It’s a story about how Clair Obscur: Expedition 33 rewrote the rules – and what its creators can teach anyone building products, leading teams, or just trying to make something that matters.We break it down into three simple rules:1. Make the thing you love and really want to use.2. Hire the spark – teach the skill.3. Hire smart people, then get out of their way. You’ll also hear about:🔸 The broken economics of AAA gaming – and how it mirrors corporate stagnation everywhere.🔸 The quiet power of creative freedom and why most leaders are terrified of it.🔸 Why inexperience might just be your biggest advantage.This isn’t just about gaming. It’s about leadership, creativity, and the art of trust.And if you do one thing after listening – check out this soundtrack. Let the “dim, dim, dam” echo in your ears a bit longer: https://music.youtube.com/playlist?list=PLox5pGvBTF_Unzs_XhD5Qm2DW5N6OLCvl&si=4m4tDqgFrU0efB2x

Most video games today feel like déjà vu with better lighting. Sequels, remasters, recycled ideas wrapped in shinier engines. You know the pattern – Dying Light with more parkour and zombies, Far Cry giving you another dictator to overthrow, and Assassin’s Creed sending you to take a leap of faith into history for the 12th time.Well, it could be worse – like Silent Hill f, with its repetitive bosses, clunky combat, and a storyline so glued to Asian folklore that you spend more time Googling 1960’s Japanese books for kids to get hints than actually playing.It’s the same loop for most AAA titles: big budgets, big promises, small soul.And then, out of nowhere, you hit the “Whoa” moment.Clair Obscur: Expedition 33. A game that shouldn’t have been possible – made by 30 people in France, on a fraction of the usual budget. No corporate roadmap. No marketing empire. Just a small team with a clear vision and something to prove.What they created wasn’t just another RPG. It was art in motion.The visuals felt like a living painting. The music didn’t just accompany the story – it was the story. Every emotional note hit right where it should. Every character felt like a person, not a trope. It was about something studios often forget: meaning.The result? 9.7 user score on Metacritic. 5 million copies sold. And a stunned industry wondering how a tiny team did what 500 people couldn’t.This episode isn’t a fan review. It’s a story about how Clair Obscur: Expedition 33 rewrote the rules – and what its creators can teach anyone building products, leading teams, or just trying to make something that matters.We break it down into three simple rules:1. Make the thing you love and really want to use.2. Hire the spark – teach the skill.3. Hire smart people, then get out of their way. You’ll also hear about:🔸 The broken economics of AAA gaming – and how it mirrors corporate stagnation everywhere.🔸 The quiet power of creative freedom and why most leaders are terrified of it.🔸 Why inexperience might just be your biggest advantage.This isn’t just about gaming. It’s about leadership, creativity, and the art of trust.And if you do one thing after listening – check out this soundtrack. Let the “dim, dim, dam” echo in your ears a bit longer: https://music.youtube.com/playlist?list=PLox5pGvBTF_Unzs_XhD5Qm2DW5N6OLCvl&si=4m4tDqgFrU0efB2x