Agile, AI, and Low-Code: Tech at PAKCon 2023


Missed PAKCon? Here are 3 tech talks that share a commonly overlooked truth: Technology isn’t an end by itself but rather an instrument to accomplish business goals

By Ronny Shani

There were 11 tech-related sessions in PAKCon 2023. Some focused on investments, others on growth or people, and all tackled this year’s motto: The Obvious.

As expected, most explored the intersection of automation and AI, highlighting the democratization these tools bring to the tech ecosystem, as they allow more people to be active participants in building what they need instead of mere passive users.

Speaking of the obvious, we want to spotlight three talks that share a commonly overlooked truth: Technology isn’t an end by itself but rather an instrument to accomplish business goals.

3 things you forgot about agile

In his keynote, our CTO and MD, Stephan Schulze, highlights the 3 Cs that are at the core of agile product development:

  1. Customer-Centric Development
  2. Collaboration and Communication
  3. Continuous Improvement

Stephan points out a fact that’s too often ignored: Implementing Scrum or other frameworks is not enough. Agile is about embracing iterative, incremental development and incorporating the relevant attitude in daily business activities, decisions, and interactions.

Paired with focus, consistency, and a clear vision of the end goal, agile is a way to secure and maintain your competitive advantage.

When is it Done? 3 Misunderstandings About Agile Product Development

Causality makes AI more than just a hype

Saman Arefi, our Senior Data Scientist, talked about the actual business value you can derive from AI if you’re willing to go beyond hype and buzzwords.

Popular AI systems take your input and spit out the most probable output without comprehending the relationship between the two. Meanwhile, causality can make them useful for more than a bit of dull fun.

Causality, the understanding of the cause and effect of specific actions, introduces an additional factor into this simple equation: A treatment that accounts for the possibility of altering the outcome.

Saman uses the example of a business deliberating a price increase. Traditional AI models would only show the relationship between customer orders and earnings, while a causal model would illustrate the relationship between the price increase (treatment) and revenue. This allows companies to identify how different customers respond to price hikes in various scenarios, making the system more transparent and more valuable as a business tool.

Why Causality is the Next Big Step in AI

Technology is (not) broken

Tamer El-Hawari, our CPO, hosted a panel with Tim Niemeier, co-founder and CTO of ROQ, Richard Illig, Head of Product at Flightright, and Stephan Schulze, where they tried to map the current state of software development.

In an ever-evolving landscape, emerging trends like composable software, no-code/low-code platforms, and AI-driven tools challenge traditional paradigms of who and how to build tech products. Is this the next step in this evolution, or are we undermining the foundation of technology, introducing too much decentralization that could lead to anarchy instead of inspiring creativity?

The panelists discuss the impact of these solutions on software development, noting their benefits and drawbacks: While no-code/low-code can speed up the development process and allow non-technical team members to contribute to product development, you’re guaranteed to hit a roadblock at some point. These solutions aren’t scalable and have limited functionality, which makes them great for prototyping, leaving complex projects to experienced software engineers. 

Technology is Broken

Visit the Project A Knowledge Conference website for more inspiring sessions and hands-on talks from founders, investors, and leading digital experts.

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