Bodhint

Applications of as²t AI in Software & Development

Bodhint Business Research
19 September 2024 | 2 mins read

AI is employed to streamline the code generation process, particularly for repetitive or boilerplate sections. By analyzing patterns in existing codebases, AI algorithms can automatically generate code snippets, reducing the manual effort required for routine programming tasks. This use case significantly accelerates development cycles, allowing programmers to focus on more complex and creative aspects of coding. The AI-driven code generation also promotes consistency across the codebase, ensuring adherence to coding standards. Ultimately, this application of AI enhances productivity, minimizes errors, and empowers software developers to deliver high-quality code efficiently.

There’s no denying that AI has a place in the future of software engineering, so getting ahead of artificial intelligence adoption is crucial for tech leaders to stay competitive. AI won’t replace software developers anytime soon. Even with customization, specific use cases, and wishful thinking, AI has its limitations. That said, AI will change how software engineers work — 70% of developers report AI coding tools give them an advantage in completing tasks and improve their productivity.

Continuous Delivery of Software Development Cycle

An IT software vendor user's Agile team uses as²t to write high volumes of code and draft PRs for teams to review. With as²t's assistance, their developers can increase their overall rate of delivery to make it feel more continuous.

What is the python code to generate this image?

import matplotlib.pyplot as plt
import numpy as np

# Create a grid of points
x = np.linspace(-1, 1, 400)
y = np.linspace(-1, 1, 400)
X, Y = np.meshgrid(x, y)

# Define the function
def f(x, y):
return np.sin(np.pi * x) \
* np.cos(np.pi * y)

# Create the contour plot
plt.figure(figsize=(8, 8))
CS = plt.contour(X, Y, \
f(X, Y), 20, colors='red')
CS2 = plt.contour(X, Y, \
f(X, Y)**2, 20, colors='green')

# Set the axes limits
plt.xlim([-1, 1])
plt.ylim([-1, 1])

# Remove the axes ticks and labels
plt.xticks([])
plt.yticks([])

# Show the plot
plt.show()

The software engineer gets the first draft from as²t off the ground quickly. When developers aren’t sure where to start or have trouble entering a flow state, AI-generated code gives a great place to start. AI can improve software reviews by automating your testing process. After refining the code, it can condense long pieces of text into shorter passages. This concise rewrite is easier to parse and adjust down the line.

As AI and its benefits continue to grow, the onus is on engineering leaders to keep up with emerging trends to make the most out of the technology. For example, LangChains is an open-source framework that allows developers to chain together multiple large language models and perform more advanced actions.

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