现已上线！2025 年 Telegram 研究 — 年度关键洞察 
BA community
前往频道在 Telegram
Lead community of business and system analysts. Follow us on LinkedIn: https://www.linkedin.com/groups/9800419. Admin: @nadina_12.
显示更多2 488
订阅者
无数据24 小时
-57 天
-2630 天
数据加载中...
相似频道
标签云
进出提及
---
---
---
---
---
---
吸引订阅者
六月 '26
六月 '26
+8
在0个频道中
五月 '26
+23
在0个频道中
Get PRO
四月 '26
+27
在0个频道中
Get PRO
三月 '26
+28
在0个频道中
Get PRO
二月 '26
+35
在0个频道中
Get PRO
一月 '26
+37
在2个频道中
Get PRO
十二月 '25
+69
在2个频道中
Get PRO
十一月 '25
+42
在2个频道中
Get PRO
十月 '25
+78
在0个频道中
Get PRO
九月 '25
+35
在0个频道中
Get PRO
八月 '25
+52
在1个频道中
Get PRO
七月 '25
+137
在2个频道中
Get PRO
六月 '25
+246
在2个频道中
Get PRO
五月 '25
+797
在2个频道中
Get PRO
四月 '25
+42
在3个频道中
Get PRO
三月 '25
+98
在3个频道中
Get PRO
二月 '25
+67
在4个频道中
Get PRO
一月 '25
+71
在1个频道中
Get PRO
十二月 '24
+39
在1个频道中
Get PRO
十一月 '24
+56
在1个频道中
Get PRO
十月 '24
+66
在2个频道中
Get PRO
九月 '24
+60
在2个频道中
Get PRO
八月 '24
+121
在2个频道中
Get PRO
七月 '24
+70
在2个频道中
Get PRO
六月 '24
+82
在3个频道中
Get PRO
五月 '24
+53
在0个频道中
Get PRO
四月 '24
+74
在1个频道中
Get PRO
三月 '24
+119
在2个频道中
Get PRO
二月 '24
+100
在1个频道中
Get PRO
一月 '24
+33
在0个频道中
Get PRO
十二月 '23
+24
在1个频道中
Get PRO
十一月 '23
+15
在0个频道中
Get PRO
十月 '23
+18
在1个频道中
Get PRO
九月 '23
+20
在0个频道中
Get PRO
八月 '23
+69
在0个频道中
Get PRO
七月 '23
+95
在0个频道中
Get PRO
六月 '23
+12
在0个频道中
Get PRO
五月 '23
+18
在0个频道中
Get PRO
四月 '23
+8
在0个频道中
Get PRO
三月 '23
+4
在0个频道中
Get PRO
二月 '23
+6
在0个频道中
Get PRO
一月 '23
+17
在0个频道中
Get PRO
十二月 '22
+20
在0个频道中
Get PRO
十一月 '22
+21
在0个频道中
Get PRO
十月 '22
+39
在0个频道中
Get PRO
九月 '22
+31
在0个频道中
Get PRO
八月 '22
+10
在0个频道中
Get PRO
七月 '22
+29
在0个频道中
Get PRO
六月 '22
+24
在0个频道中
Get PRO
五月 '22
+15
在0个频道中
Get PRO
四月 '22
+10
在0个频道中
Get PRO
三月 '22
+7
在0个频道中
Get PRO
二月 '22
+370
在0个频道中
Get PRO
一月 '22
+26
在0个频道中
Get PRO
十二月 '21
+71
在0个频道中
Get PRO
十一月 '21
+298
在0个频道中
Get PRO
十月 '21
+327
在0个频道中
Get PRO
九月 '21
+31
在0个频道中
Get PRO
八月 '21
+59
在0个频道中
Get PRO
七月 '21
+87
在0个频道中
Get PRO
六月 '21
+67
在0个频道中
Get PRO
五月 '21
+11
在0个频道中
Get PRO
四月 '21
+610
在0个频道中
| 日期 | 订阅者增长 | 提及 | 频道 | |
| 16 六月 | 0 | |||
| 15 六月 | 0 | |||
| 14 六月 | 0 | |||
| 13 六月 | 0 | |||
| 12 六月 | 0 | |||
| 11 六月 | 0 | |||
| 10 六月 | +2 | |||
| 09 六月 | +1 | |||
| 08 六月 | 0 | |||
| 07 六月 | 0 | |||
| 06 六月 | 0 | |||
| 05 六月 | +1 | |||
| 04 六月 | 0 | |||
| 03 六月 | +2 | |||
| 02 六月 | +1 | |||
| 01 六月 | +1 |
频道帖子
GPT-5.5: WHY THIS MODEL UPDATE MATTERS FOR BA/SAs 🔶
OpenAI released GPT-5.5 as a model for complex professional work - and for Business and System Analysts, the key point is not only stronger reasoning.
The real signal is workflow maturity. GPT-5.5 is positioned for coding, online research, information analysis, document and spreadsheet work, and tool-based execution. It also supports long-context work in the API, which makes it more relevant for real analytical environments: specifications, transcripts, legacy documentation, tickets, policies, and system descriptions.
What matters most for BA/SAs:
🔹 Better support for complex tasks
Analytical work is rarely one prompt → one answer. It usually means reading context, comparing versions, finding gaps, checking assumptions, and preparing structured outputs.
🔹 Stronger tool use
GPT-5.5 is designed to work better across tools. For analysts, this matters because BA/SA workflows increasingly connect documents, spreadsheets, tickets, diagrams, and knowledge bases.
🔹 Long-context analysis
Large inputs are normal in analysis: BRDs, API specs, discovery notes, call transcripts, business rules, and old documentation. Better long-context handling means better synthesis and fewer isolated answers.
🔹 More reliable professional outputs
OpenAI also highlights stronger performance in professional tasks and reduced hallucinations in GPT-5.5 Instant. This is important because a polished but wrong AI output can easily become a bad requirement or misleading decision note.
For BA/SAs, the practical use cases are clear:
• requirements review
• acceptance criteria drafting
• gap and contradiction analysis
• stakeholder meeting summaries
• documentation comparison
• impact analysis
• test scenario preparation
• backlog refinement support
My takeaway: GPT-5.5 is another step from AI as a chatbot toward AI as a workflow assistant.
But the analyst’s responsibility does not disappear. The value shifts to context control, validation, traceability, and knowing where AI output is useful — and where it is only a hypothesis.
The best analysts will not be those who simply use GPT-5.5. They will be those who can integrate it into analytical workflows without losing ownership of quality.
BusinessAnalysis RequirementsEngineering GPT55 OpenAI
| 2 |  Is a software release just a technical procedure? 🤔
For a digital native - I believe yes. But for someone who spent 20 years in Event Management before pivoting to system analysis at 40+, a release is a high-stakes performance.
At first glance, these two universes seem to exist on opposite poles. One is about spotlights, catering, and microphones, the other is about SQL queries, API contracts, and Jira tickets. However, as I navigate my career path, I’ve realized that a software release and a large-scale forum share the same DNA.
Imagine a major international summit. You have months of planning, a diverse group of stakeholders with conflicting interests and ambiguous requirements, and a hard deadline that cannot be moved. That is exactly how a software release feels. In both worlds, your "backlog" is the event program. Your integrations are the external vendors and speakers who must perform in perfect sync. If the sound system fails during a speech, it’s a critical bug in production. If the registration desk is slow, it’s a bottleneck in the system architecture.
As a system analyst, I’ve found that my event brain gives me a massive advantage. In event management, you learn to spot a crisis before it happens. You become a master of requirements gathering because if you misunderstand the client’s vision for a gala dinner, there is no undo button once the guests arrive. In IT, this translates to meticulous analysis. I don't just look at the data fields, I look at the guest journey, user experience.
My transition was never about discarding my past, it was about reformatting it. When I’m analyzing a complex database structure, I use the same logical patterns I used to coordinate a 1000 person event. Both require a high-level view of the system and attention to details. Whether it’s a post-mortem report or a sprint retro, the goal is the same - to learn how to do it better next time.
If you are considering a career shift at any age, stop viewing your previous experience as white elephant. It is your secret weapon. You’ve spent years solving real-world puzzles under pressure. IT is just a different set of tools to solve the same human problems. Experience is the most stable architecture you can build.
BusinessAnalysis SystemAnalysis | 214 |
| 3 | Requirements Engineering is changing fast — and AI is one of the main reasons why.
At IREB exploRE2026 in Wrocław, many discussions focused on the future of requirements work, business analysis, system analysis, and the practical impact of AI on our profession.
As a Business and System Analyst at Andersen, I had the opportunity to speak on the topic: “AI-Aware Business Analysis: New Skills and Practices for IT Analysts in the LLM Era.”
The key problem to address is simple: AI can generate, summarize, compare, and review analytical artifacts much faster than before. But faster wording does not automatically mean better understanding. A polished requirement may still hide weak assumptions, missing context, or unclear business intent.
📝 In my presentation, I focused on several practical ideas:
- AI should support analysts, not replace their responsibility.
- Analysts should move from simple artifact production to analytical orchestration.
- Context engineering becomes as important as prompt engineering.
- AI can help with discovery, elicitation, drafting, review, and system analysis — but every output must be validated.
- Traceability, source awareness, and human approval become even more important in the AI era.
🟢 For me, the future analyst is not an “AI scribe.” The future analyst is a professional who can manage context, challenge outputs, validate decisions, and build reliable, traceable, and responsible AI-supported analysis.
IREB exploRE2026 RequirementsEngineering | 288 |
| 4 | 🗣 Product + Marketing = Results
Why do some products skyrocket while others go unnoticed?
Quite often, it’s not just about the idea or execution – it’s about how well the product and marketing are aligned throughout the entire user journey 👀
📅 On June 18, we’re holding a meetup where we’ll explore how product and marketing teams can operate as a single system – from market understanding to retention and growth.
Agenda:
– Where collaboration creates the biggest impact;
– What each team truly brings to the process;
– Why a lack of alignment leads to missed opportunities;
– What a practical framework for joint decision-making looks like;
– How to strengthen positioning and drive real impact.
🧠 No theory overload – just real-world scenarios and approaches you can apply right after the meetup.
Speakers:
🎤Natallia Tarasevich – Product Manager/Product Owner/Business Analyst
🎤Aryna Barysionak – Lead Marketing Manager | Digital Marketing Manager
🔗 Register here: https://lnkd.in/dB9AJPD6
Two experts. One user journey. One result!
Meetup details:
⏰ Time: 18:00 (СEST)
🕒 Duration: 60-80 minutes
🗣 Language: English
💻 Online: the link to the stream will be sent to your email specified in the registration form
See you! | 407 |
| 5 |  Major conference of IREB is now behind us 👏
Our community member Alexander Malyarenko recently represented us at IREBexploRE2026 - one of Europe's leading conferences on Requirements Engineering!
As proud partners with IREB, we're thrilled to support this collaboration and gather valuable insights from cutting-edge events like this.
Alexander shared powerful takeaways on Business Analysis in the LLM Era: AI isn't just adding tools - it's reshaping how analysts work. From AI-assisted interviews to orchestrating analytical workflows, the BA role is evolving toward contextual understanding, validation, risk governance, and managing ambiguity. 💡
📌 Stay tuned and Alexander will share more deep insights and practical tips in his upcoming posts!
IREB exploRE2026 BusinessAnalysis RequirementsEngineeringAI | 373 |
| 6 |  Communication is about empathy 🤍
We live in an era of total communication, yet it remains a weak spot for many in IT. There’s a reason why soft skills are a top priority for recruiters. Let’s dive into how we can boost our projects and careers using a few simple, often overlooked tips.
✔️Hearing vs. Listening 👂
What’s really behind your peer’s or manager’s frustration? Have you ever tried to walk in their shoes?
Understanding the roots of the other person's thoughts is the key to success. Try looking at the situation from a different angle. Perhaps, you’ll find out that in the same circumstances you would behave the same way. Make the ability to truly listen to your core trait and it’ll change the way you handle daily communication.
✔️Why your “Awesome” is actually useless?
We can easily write a negative review for a restaurant. But what about our colleagues? Aren’t we afraid to hurt their feelings?
Actionable feedback isn't about offending people — it's about growth. We can’t fix our blind spots if we don’t know they exist.
• Be fair and polite.
• Encourage others to give you feedback, too.
• Be extremely specific! Saying “You did it wrong” or “You’re awesome” is too ambiguous. It gives the other person nothing to work with.
✔️Don’t be a Meeting Ghost
Even if you have a brilliant Scrum Master or PM, don’t hesitate to be their wingman.
Imagine yourself standing in front of a crowd that doesn’t react to your jokes or questions. It’s just as awkward in a Zoom call as it is on a real stage.
Even if it’s not your job to lead, a simple supportive phrase or a proactive answer breaks the ice. It makes the conversation more comfortable for everyone and speeds up the decision-making process.
Communication isn't just about "talking." It's about empathy, clarity, and team support. By mastering these three simple habits, you’re not just being a "nice" person — you're becoming a high-value professional who can navigate any corporate environment.
#SoftSkills #TechCommunication #FeedbackCulture | 454 |
| 7 | Hey, Community 👋
On June 9, we’ll talk about how to turn chaotic business requests into clear and actually useful dashboards.
At the meetup, we’ll discuss:
— Why many dashboards end up unused;
— How to formalize requirements for metrics and data sources
— How to improve communication between business teams, analysts, and data engineers.
If you’ve ever dealt with endless revisions, last-minute “can we add one more chart?” requests, or discussions like “what exactly should this metric calculate?” – this meetup will definitely be useful for you 👀
🎙 Speaker – Darya Drobova, Principal BI Developer at EffectiveSoft with over 12 years of experience in BI and expertise in Power BI, Tableau, and IBM Cognos Analytics.
🎟 Register here
You’ll get real-world cases, practical approaches, and templates you can start using in your work right after the meetup.
Event details:
⏰ Time: 19:00 (Minsk time, GMT+3)/18:00 (CEST)
🕒 Duration: 1 hour
🗣 Language: Russian
📍 Offline: Andersen’s office in Minsk
💻 Online: The link to the stream will be sent to your email specified in the registration form
This meetup will definitely come in handy 👀
Become a speaker
See you! | 373 |
| 8 |  WHAT BA/SAs SHOULD READ ON AI: APRIL PAPERS AND BOOKS
📕 April was a useful month for BA/SAs who try to understand AI not as hype, but as a working instrument.
My short reading focus would be this:
1️⃣ First, papers on LLMs in requirements engineering. The most interesting part is not that AI can generate user stories. We already know that. The real question is whether it can help with gaps, contradictions, traceability, validation, and domain understanding.
Example: Formal Requirements Engineering and Large Language Models by Alessio Ferrari et al., 2025.
Why it fits: it is not just about generating requirements. It looks at how LLMs can support correctness, reliability and validation in requirements engineering. A good example for the idea: AI can draft, but the analyst must validate.
2️⃣ Second, materials on AI in business process modelling. This is especially relevant for analysts, because the discussion is moving from “AI writes text” to “AI helps structure work”.
Example: BPMN Assistant: An LLM-Based Approach to Business Process Modelling by J. T. Licardo et al., 2026.
Why it fits: this is about moving from text to process logic. The paper shows how LLMs can help create and edit BPMN models, which is directly relevant for BA/SA work.
3️⃣ Third, books about AI and knowledge work. For BA/SAs, the best AI books are not only technical. They should explain how decisions, roles, responsibility and collaboration change when AI becomes part of the workflow.
Example: Ethan Mollick, Co-Intelligence: Living and Working with AI.
Why it fits: this is not a technical book about models. It is about how people work with AI, how responsibility changes, and why human judgement remains central in knowledge work.
My conclusion is simple: reading about AI is useful only if we read with an analyst’s mindset.
Not “what can this tool do?”
But: “what responsibility still stays with me?”
#BusinessAnalysis #SystemAnalysis #RequirementsEngineering #AI #BA #SA | 466 |
| 9 |  Bad requirements or bad users? 🤔
In 1935, Boeing built a plane so advanced it crashed on its first test flight.
Engineers immediately blamed "pilot error". But the reality? The machine was simply "too much airplane for one man to fly".
They did not ask for smarter pilots, they just added a simple checklist.
I’ve been thinking about this from BA perspective.
It is easy for us to design a complex flow and just expect users to "get it". When they get confused, click the wrong button, or abandon the process, our first instinct is often to write it off as user error. We assume they just didn't read the screen carefully.
But honestly, I'm realizing we might be wrong to think like that. Often, what we call "user error" is actually a sign that we designed a system that is just too hard to fly.
When a user makes a mistake, it usually means we built "too much airplane". Look, real users aren't sitting in a quiet room studying our systems. They are:
- distracted
- rushing
- just trying to get a task done
We can't expect perfect users. Instead, we have to accept our own blind spots as the people creating the system, and build safer paths. We need to guide users so naturally that they don't have to struggle.
Great software shouldn't force people to think harder. It should just help them fly safely.
#BusinessAnalysis #SystemDesign #ProductThinking #UXDesign #SoftwareDevelopment | 447 |
| 10 | “I’ll do it myself 😌” or the story about how hyper-control emerges
Most of the time, the problem in a team is not the team. Sometimes things are broken not by processes. And not by deadlines. But by a person who can’t let go of control.
🪤“Atlas Syndrome: How to Stop Carrying the Project Alone and Start Leading”
🎤 At a meetup on May 20, Julia Karvat (HR expert with over 12 years of experience, Master of Psychology, Corporate Trainer) will break down what is usually left unsaid:
- Why “I’ll do it myself” is not heroism but a trap;
- How hyper-control kills initiative and drains energy;
- Where the “dopamine loop” of micromanagement comes from and how to break it;
- How to delegate without losing quality and finally get some sleep.
🎟 Join the meetup
It’s going to be hot - not because of the weather 🔥
Meetup details:
⏰ Time: 19:00 (Minsk time, GMT+3)/18:00 (CEST)
🕒 Duration: 1 hour
🗣 Language: Russian
📍 Offline: Andersen’s office in Minsk
💻 Online: The link to the stream will be sent to your email specified in the registration form
Become a speaker
See you soon 👋 | 455 |
| 11 |  IT at 41: Too Late or Just the Beginning or true story of a System Analyst 🚀
“You’re too old to compete with digital natives!” “The Golden Age of IT is over.” “AI will replace everyone.” If you’re 30+ or 40+, I bet you’ve heard these horror stories.
I spent 20 years in marketing and events. At 41, I decided to become a System Analyst. Spoiler alert: it worked. Here’s how. 👇
Event Manager → System Analyst
I spent the last 8 years in the "stress-deadline-chaos" mode. Then, I chose... System Analysis! 🙂
This wasn’t a spontaneous jump on the bandwagon. I spent months researching the market and looking for something that would bring me joy every day.
💡 Tip #1: Choose wisely and take your time. This isn’t a choice your parents made for you — you’re in charge now. Your life experience is a superpower that makes you incredibly efficient.
The Grind 📚
I enrolled in the beginner courses at Andersen. Was it hard? Yes. Was it worth it? Absolutely.
I studied for 10 – 12 hours a day. My secret weapons were the skills I’d spent years building:
✅ Proposing initiatives.
✅ Staying calm under pressure.
✅ Communication (we are the generation that isn’t afraid to make phone calls!).
💡 Tip #2: Use your transferable skills as a competitive edge.
The Result: 42 is the Answer 🌌
Within 8 months of making my decision, I landed my first role as a System Analyst.
Now I’m 42. For Douglas Adams fans, that’s the "Answer to the Ultimate Question of Life, the Universe, and Everything." For me, it’s the perfect age for a career pivot.
I haven’t faced any ageism. In fact, I feel like I’m 20 again, but with all the perks and wisdom that come with experience.
Bottom line: If you’re still on the fence - drop your fears and take the leap. It’s worth it. 🚀
What’s stopping you from making a career switch? Or are you already in the middle of it? Let’s discuss in the comments!
#CareerTransition #SystemsAnalyst #LifelongLearning | 416 |
| 12 |  AI DIGEST FOR BA/SAs: APRIL UPDATES 🗓
April was not only another month of “better models”. It showed a clearer shift in AI tools: from chatbots to work systems.
OpenAI released GPT-5.5 and updated ChatGPT/Codex around more practical work use: stronger reasoning, easier model selection, and a stronger move toward agentic workflows. 🧠 For analysts, the signal is clear: AI is becoming less about one good answer and more about helping with a chain of tasks.
Anthropic introduced Claude Opus 4.7, with emphasis on coding, agents, vision and multi-step work. 💻 This matters for BA/SAs because many analytical tasks are also multi-step: reading context, comparing versions, finding gaps, checking assumptions, and preparing structured outputs. 📊
Google’s April updates were strongly focused on the “agentic era”: Gemini Enterprise Agent Platform, Deep Research Max, Gemma 4, and broader enterprise AI infrastructure. This is important because AI is moving closer to business workflows, not just individual productivity. 📈
Microsoft continued to develop Copilot Studio around agent governance, intelligent workflows, app integration and control over agent operations. For enterprise analysts, this is one of the most relevant directions: not just using agents, but managing how they work inside real business processes.
Mistral released Mistral Medium 3.5 and expanded its agent direction with remote agents in Vibe and Work mode in Le Chat. 🌐 The interesting part is the same: models are becoming execution layers for multi-step tasks, not only text generators.
DeepSeek released DeepSeek-V4 Preview with open weights and a 1M context window. 📚 For BA/SAs, long context is especially relevant: requirements, transcripts, legacy documentation, APIs and business rules rarely fit into small isolated prompts.
Yandex/Alice AI also continued moving toward search-connected AI, especially for Russian-language work and ecosystem-based assistance. This is relevant for local markets where language quality, search integration and document work matter more than benchmark leadership.
The practical takeaway for BA/SAs is simple.
AI tools are becoming more agentic, more integrated and more workflow-oriented. This does not remove the analyst from the process. It changes the analyst’s role.
Less manual drafting. ✍️
More validation, orchestration, source checking, context control and responsibility for the final decision.
#BusinessAnalysis #SystemAnalysis #RequirementsEngineering #AI #BA #SA #AgenticAI #DigitalTransformation | 421 |
| 13 |  How much of a BA's daily work can AI already handle – 30%? 50%? More? 👨💻
Writing requirements, validating them, prioritizing – a lot of it can be automated today. The question isn't whether it will happen, but how fast?
On May 19, we'll get specific:
– which BA tasks AI is already taking over?
– which skills are becoming more valuable as a result?
– and what Business Analysts can do about it now?
🎤 Nadzeya Siskevich, Senior BA & PO at Andersen Lab
⏰ May 19, 5:00 PM CET | Online | German
👉 Register here
And see you :) | 484 |
| 14 |  Remote work in 2026 isn't new anymore. But most people are still figuring it out🧕
The first wave was survival mode : kitchen tables, back-to-back calls, no real separation between work and everything else. The setups have improved since then. The habits, for a lot of people, haven't.
What remote actually takes:
Office work had structure baked in. The commute as a transition. Lunch as a reset. Colleagues as checkpoints throughout the day.
Remote removed all of that and handed you a blank calendar. Which sounds like freedom until you're three years in and still can't switch off at 7pm.
The people who handle remote well aren't the ones with the nicest home offices. They're the ones who rebuilt those transitions on purpose.
What tends to work
• Create a start ritual. Something short and consistent that signals the workday is beginning. A walk, 10 minutes of planning, coffee somewhere that isn't your desk. The brain needs a cue. Without one, you're open and technically working but not really there yet.
• Separate communication from thinking. Slack open during deep work is like trying to read with someone talking next to you. Closing notifications during focus blocks isn't ignoring your team. It's how the actual work gets done.
• Build a fake commute. A 15-minute walk before and after work. It sounds unnecessary until you try it for a week. A lot of remote workers consider it non-negotiable once they start.
• Make your availability predictable. Remote teams run on trust, and trust comes from knowing when someone is in, heads-down, or done for the day. Communicating that clearly removes more friction than most people expect.
• Change your physical spot when the work changes. Deep focus at the desk. Calls from somewhere else. Admin tasks in a different room or a cafe. Context switching physically helps mentally more than it should.
What it comes down to
Remote work is a skill, not a perk. The people who get the most out of it treat it that way and keep adjusting until something holds.
The setup matters less than the habits. And the habits take longer than everyone assumes.
How do you approach this? What's one thing you wish you'd figured out earlier about working remotely❓
#RemoteWork #WorkFromHome #Productivity #TechLife #WorkSmart #CareerGrowth #FutureOfWork | 458 |
| 15 | Hello, dear community! 👋
Recently, together with IIBA Poland Chapter, we held a joint meetup in Krakow - and it was a great evening of practical BA conversations.
We've discussed:
🔹How to work with a client who wants a product but can't explain what exactly they need - and how an analyst helps build a vision from uncertainty.
🔹 Facilitation as an analyst's superpower to turn disagreements into aligned decisions.
Thank you to our speakers Valentin Kostin and Edyta Dziados, as well as our esteemed representative of IIBA Kateryna Subbotina, and everyone who joined offline in Krakow, and those who watched online. You made this happen 🙌
📺 Missed it? Watch the full recording here:
🔗 link
❓ Still have questions? Drop them in the comments here- our speakers will be happy to answer.
More joint events coming soon - see you :)
#BusinessAnalysis #IIBA #Andersen #Meetup #AnalystsHub | 470 |
| 16 |  Most tech professionals don't have a work-life balance problem. They have a structure problem 🤔
The hours exist. The energy exists. What's missing is a system that actually protects both.
Why it feels impossible in tech:
The work doesn't have natural "endpoints". Slack threads don't close. In remote setups, there's no physical moment of "leaving" to signal that the day is over.
On top of that, productivity tools have quietly raised the baseline of what's expected. You can deliver more, so more gets assumed. The efficiency gain rarely comes back as time.
What people are actually doing about it:
Here are a few patterns that show up consistently across different roles and team setups:
• Protect the first 90 minutes. Before Slack, before email. Use that window of time for the work that actually requires thinking. Reactive tasks can wait. Deep work usually can’t.
• Pick a real end time. “I’ll stop when I’m done” - it doesn’t work because in tech, you’re never fully done. A fixed point, communicated to the team, makes the difference between a boundary and a vague intention.
• Batch responses instead of reacting constantly. Most messages can wait two hours. Processing Slack in blocks rather than in real time cuts mental load without anything actually falling through.
• Match hard work to high-energy hours. A focused 6-hour day beats a scattered 10-hour one. Knowing when you think well and scheduling accordingly matters more than logging time.
What this comes down to:
Balance doesn't appear on its own. Someone has to decide it's worth building and start treating their time like it has a shape.
The good part: none of this requires a perfect company or a special role. It requires stubbornness more than anything.
What's your experience with this? Has anything genuinely shifted how your days feel, or is it still a work in progress? ♎️
#WorkLifeBalance #RemoteWork #Productivity #DeepWork #TechLife #CareerInTech #WorkSmart | 499 |
| 17 |  AI IN DISCOVERY: HOW TO GENERATE HYPOTHESES, NOT NOISE ✔️
AI can be very useful in discovery. But only when we use it to generate hypotheses, not just more text. That is the key difference.
In discovery, the goal is not to produce the longest list of ideas. The goal is to surface better questions, possible patterns, risks, unmet needs, and directions worth checking.
🔥 Used badly, AI creates noise:
- random feature ideas,
- generic user needs,
- obvious assumptions,
- and a lot of words with little value.
✅ Used well, AI can help analysts:
- reframe a problem,
- generate alternative explanations,
- map possible user pain points,
- identify missing questions,
- and spot areas that need validation.
❗️ The important part is this:
- AI should not decide what is true.
- It should help you explore what might be true.
That is why discovery with AI works best when the analyst stays active: give context, narrow the scope, compare angles, challenge outputs, and turn ideas into testable hypotheses.
Good discovery is not about asking AI for answers. It is about using AI to think more broadly — without losing focus.
For BA/SAs, that makes AI less of a shortcut and more of a structured sparring partner.
How do you use AI in discovery work today?
#BusinessAnalysis #SystemsAnalysis #AI #GenerativeAI #Discovery #ProductDiscovery #RequirementsEngineering #BusinessAnalyst #SystemAnalyst #BA #SA | 0 |
| 18 | HOW MUCH TIME DOES AI REALLY SAVE AN ANALYST? 📊 | 0 |
| 19 | HOW MUCH TIME DOES AI REALLY SAVE AN ANALYST? 📊 | 0 |
| 20 |  BA AS AN AI ORCHESTRATOR: THE ANALYST’S 🆕 ROLE
🔥 The BA role is changing. A few years ago, analysts mostly worked as translators between business and delivery. Today, more and more of us are becoming something else too: AI orchestrators.
🟢 What does that mean in practice? It means the analyst is no longer just writing requirements alone. Now the analyst often:
- asks AI to generate first drafts,
- compares multiple answer options,
- checks logic and gaps,
- gives business context,
- validates what is useful,
- and turns raw AI output into something the team can actually use.
So the value is shifting. It is less about “who writes the first version fastest”
and more about:
- asking the right question,
- giving the right context,
- choosing the right tool,
- combining human judgment with AI speed,
- and keeping quality under control.
In other words, AI does not remove the analyst from the process. It makes the analyst more important in a different way. Because someone still has to:
- connect business goals and system logic,
- see contradictions,
- challenge weak assumptions,
- and make sure the final output is not just fast, but correct and useful.
That is why I think one of the key BA/SA skills now is not only analysis. It is orchestration: how to coordinate AI, people, context, and decisions into one working result.
🟢 The analyst of the near future is not just a document writer. The analyst is a workflow designer, sense-maker, and quality controller in an AI-assisted environment.
Do you already feel this shift in your work?
#BusinessAnalysis #SystemsAnalysis #RequirementsEngineering #AIAgents #GenerativeAI #DigitalTransformation | 0 |
