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Powered by AI - but only if it's done right

January 4, 2023
Powered by AI - but only if it's done right

Before chatGPT started the recent AI tsunami, we wrote about AI-enhanced coding with pro's and cons linked to it. Artificial Intelligence can be a tremendous asset when it comes to improving productivity, yet there remains room for growth in various zones of the development process such as design, debugging, UX design and project management.

With AI on your side, software creation is made easier than ever before - but let's dive in to the shortcomings first.

Areas where AI may be weaker than humans

  1. Designing and architecting software systems: This involves envisioning the overall structure and layout of a software system, and deciding how its various components will work together. AI may struggle to come up with creative solutions or to anticipate how different components will interact.
  2. Debugging and troubleshooting: Finding and fixing bugs in software can be a complex and time-consuming process. AI may be able to automate some aspects of debugging, but it may struggle to understand the underlying causes of problems or to devise effective solutions.
  3. User experience (UX) design: Creating a user-friendly and intuitive interface for a software application requires a deep understanding of how people think and interact with technology. AI may be limited in its ability to anticipate user needs and preferences, or to create interfaces that are easy to use.
  4. Managing and leading software development projects: Leading a team of software developers requires strong communication and interpersonal skills, as well as the ability to motivate and inspire others. AI may be limited in its ability to effectively manage and lead human team members.

Prompt engineering

Thankfully, it's not about AI or humans, but rather a fusion of both working together. In the past, Googling has been an indispensable skill for developers; now they have one more essential tool: prompt engineering.

Prompt engineering is a technique that steers the output of an AI system through providing specific prompts and inputs. These prompts can influence content, style or tone, and help the AI focus on specific tasks. A common example is generating natural language text (e.g. articles or social media posts). By specifying a topic, the AI can generate text relevant to this topic and avoid unrelated content. For instance, the 4 points above were done by asking the following from AI: "What are the tasks or areas in software development where AI is most likely to struggle or be weaker compared to humans?"

Professionals powered by AI

By leveraging the combined power of human intelligence and machine learning technology, we can take advantage of both worlds. When it comes to risks in AI generated code, the dangers are comparable to those found in human-made code:

AI-generated code poses risks of errors, bugs, incompatibilities, cyber attack vulnerabilities, legal/copyright issues. Maintenance and compatibility may be more difficult than code written by humans. Remember that if the AI system used to generate the code has been trained on biased data, the code may contain biases that could lead to discriminatory outcomes or unfair treatment of certain groups.

Artificial intelligence has the potential to bring existing risks to fruition faster than ever before — so stay vigilant!

Infinite tasksourcing - best of both worlds

At NerdCloud we build our own platform with the tools and services we offer to our customers - we drink our own champagne! Combining the finest of both human and AI capabilities:

  • Risk management: infinitely scalable without technology limitations, IPR ownership at customer (we also use AI to boost our productivity)
  • Elasticity: possibility to scale costs up or down each month based on need, time estimates of tasks for free to support planning
  • Simplicity: it’s a plugin, we take care of all "HR issues" and there is no new UI that is required

Did we mention that it's free to try? Let's talk!