

Date
Feb 10, Tuesday
Time
7:00 pm - 8:00 pm (GMT+2)
Format
ONLINE - Live Discussion + Q&A (English)
Because I want to see real industry insights and ask questions
Seats are limited.

Perspective:
Business and transformation view - how companies move past the hype cycle and capture real value.
Perspective:
What it takes to scale engineering and execution in the real world and how AI changes the baseline for high-performing teams.
Perspective:
How companies actually pick AI use cases, implement them and avoid scattered efforts.
Perspective:
How AI shifts go-to-market leverage and what high-output teams can now build and sell.
Because I want to see real industry insights and ask questions
Seats are limited.
How roles shift (junior, senior, lead) when AI is embedded into daily workflow
What skills become high-leverage (and what starts to matter less)
Why adoption fails inside orgs (and what makes it stick)
What “small, high-output teams” enable (delivery speed, product iteration, services, new GTM patterns)
The new baseline for quality and risk when AI touches production (review patterns, guardrails, security thinking)

Most Importantly:
You’ll get a realistic view of what changes next - and what to do about it without breaking your org.
Because I want to see real industry insights and ask questions
Seats are limited.

Feb 10, Tuesday
7 pm GMT+2
Online
60-minute live session +Q&A
English
What’s really stopping engineers from going all-in with LLMs (beyond job fear)
What upskilling looks like when it’s done for real - not theory
The patterns: who adapts fast, who struggles, and why
If you want to stay relevant: what to learn, unlearn, and stop doing entirely
The hardest internal friction points teams hit when they try to adopt LLMs
Where resistance actually comes from (engineering, leadership, compliance, clients)
What “unrealistic expectations” look like - and how to reset them without slowing down
What will be meaningfully different inside orgs 2 years from now
How teams attempt to measure progress: productivity, quality, learning, risk
If delivery gets dramatically faster/cheaper, what breaks in today’s service and product models
What happens to hourly pricing and “time-based” thinking
Whether the future is fewer people, different people, or different team shapes
How you get clients comfortable with LLM usage in real engagements
Which models survive the next 5 years - and what feels under-exploited right now
What it means to be a “good engineer” when AI is part of the default workflow
Which parts of the job become more valuable - and which quietly fade
The honest answer to: “Should I be worried about my job?”
Key Takeaway:
Prepare for the new world order without hype.
Get a practical map of how roles shift, what to learn next and how to adopt AI without breaking your org
Because I want to see real industry insights and ask questions
Seats are limited.
A mid-to-senior engineer who ships production code
A tech lead or engineering manager trying to keep standards high while moving faster
A CTO or founder thinking about org design, hiring and leverage
Anyone tired of hype and looking for practical direction
Not ideal if you want “prompt tricks” or a tool tutorial. This is about the job and the system around it.
No. This is about roles, workflows, teams, and business impact.
Yes - we leave time for live Q&A at the end.
Live attendance gets you:
- Q&A - you can ask your situation and get direct answers
- the real energy and nuance that gets cut in clips
- the chance to influence what we go deeper on next
We’ll share the recording later, but live is where you get the most value.
Yes.
Because I want to see real industry insights and ask questions
Seats are limited.
AI Empowered Devs is a members only community for developers and tech leaders who want to use AI in real software engineering - not just play with tools.
The goal is practical: share what actually works in production, what breaks, and how to adopt AI without sacrificing code quality.
We started on 20th of Jan. 2026 and already have ~80 signed up members for the pilot phase. We will be using this phase to test formats, collect feedback, and refine what delivers the most value - before opening officially.
A place where developers help developers with real workflows, examples, and honest feedback
A signal-heavy environment (less hype, more proof)
Repeatable formats that improve skills fast: show-and-tell, teardown sessions, implementation clinics, and Q&A with practitioners
The goal of the community is simple:
to upskill your AI-first engineering skills, so you can keep your job or land a better one
or to build your own product faster and with more confidence using AI
Networking with devs, CTOs and founders who are actually building with AI
Guest speakers and practitioners (like this series) sharing real workflows and lessons learned
Members sharing wins, tools, patterns and failures so others don’t repeat them
A growing library of practical resources (playbooks, checklists, prompts with guardrails, workflows)
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