GitHub Copilot Cuts Coding Time by 10%—Startup VP Hails ChatGPT‑Like Tool

OpenAI’s Generative AI Toolbox Goes Beyond ChatGPT

While the ChatGPT chatbot has captured headlines, OpenAI has released a lineup of generative‑AI tools that target developers, analysts, and creators.

Codex Powers GitHub Copilot

• Codex is a language model that processes code, offering predictions that accelerate software engineering.
• GitHub Copilot acts as an “autocomplete” for programmers, examining existing code and proposing the next lines that might resolve a problem.
• Engineers can also describe a desired function in natural language; Copilot then supplies a coding skeleton that addresses the request.

Scaffold Creation Becomes Effortless

Software architects frequently assemble scaffolding—a boilerplate foundation that outlines an application’s structure. Copilot replicates these patterns with high accuracy, supplying up to 40 % of the written code in enabled projects, according to GitHub.

Productivity Gains Evident

Insight observations indicate that Copilot offers a decisive boost to engineering productivity, allowing developers to focus more on problem solving than routine coding.

Copilot can help developers become more productive

Beagle CTO Adopts Copilot to Slash Repetitive Work

Cyrus Ghazanfar, the chief technology officer at the 401(k)-management startup Beagle, revealed that his company began testing Microsoft’s Copilot in recent months.\n

After quickly discovering that the AI tool saved him valuable time by eliminating rote tasks, Ghazanfar now mandates his three‑engineer team to incorporate Copilot into their daily workflow.\n

Already, the technology has proven useful for building databases, the CTO said.\n

Key Takeaways

• Beagle’s three engineers now use Copilot as a core part of their development process.
• Copilot has helped the company create databases more efficiently.
• The CTO credited Copilot for cutting time spent on repetitive work.

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Innovative Database Creation with AI Assistance

Efficient Coding Through Copilot

Ghazanfar explained that specific database frameworks require a distinct approach to creation. He highlighted Copilot’s usefulness, noting its ability to handle repetitive tasks effectively.

Many databases share common attributes like a creation timestamp. Ghazanfar now employs Copilot to quickly generate a database incorporating these properties by simply requesting the AI-powered bot.

Engineering Perspective on Copilot’s Accuracy

• Bill Mers, Vice President of Engineering at LookDeep Health, described Copilot as “almost creepy” when it accurately predicts the code he intends to write.
• The AI tool learns from a vast GitHub project corpus, which raises legal concerns.
• Copilot also uses the project context to propose customized code solutions.

Mers estimated that Copilot reduced his coding time by 10%. He occasionally writes comments in his scripts to describe their purpose. Copilot detects these comments and writes human‑language descriptions of the code’s functionality.

A Time‑Saving Experience

“All the typing and thinking—I didn’t have to do it,” Mers said, underscoring the convenience Copilot brings to his daily development workflow.

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Copilot is sometimes inaccurate

Copilot’s “Accurate” Code is a Double‑Edged Sword

Ghazanfar warned that trusting Copilot can be risky. When the AI’s suggestions fail, developers must manually correct mistakes, a process that demands human expertise. Both Copilot and ChatGPT confidently present answers even when they’re wrong, so users still need to spot and fix errors.

Former GitHub CEO Calls Copilot a Lottery

Nat Friedman, who oversaw the launch, compared Copilot to a lottery at a recent San Francisco event. He explained that while most suggestions are incorrect, occasionally Copilot delivers the perfect solution for a developer’s specific need.

Copilot’s “Hallucinations” Hurt Developers

Like ChatGPT, Copilot frequently “hallucinates”: it confidently proposes code that doesn’t truly exist. Mers highlighted that a developer might think an API call works, only to discover the API never existed.

• Missing APIs – Code looks great, but the referenced API does not exist.
• Complex Tasks – Developers must understand what they’re asking for and how to fix suggested code.
• Fast Cadence – Tools like Copilot accelerate software creation, increasing the demand for skilled developers.

Why Engineers Will Not Vanish

Ghazanfar said that Copilot can build a basic iOS app but not more sophisticated projects. Developers still need to know how to ask the right questions, correct wrong code, and write code in flexible, non‑opinionated frameworks. Because Copilot relies on existing web code, it cannot invent the next generation of technology. Human critical thinking remains essential.