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AI adoption in software program improvement is accelerating quick, and naturally, shoppers wish to know the place we stand.
Over the previous few months, we’ve obtained extra questions from companions questioning:
“Are you utilizing AI to hurry issues up?”
“Why is supply slower when AI is meant to assist?”
“Is Onix behind?”
Let’s handle that — brazenly and with information.
The Promise vs Actuality of AI-Powered Coding
Undoubtedly, AI instruments like GitHub Copilot, Cursor, and Claude have modified how code is written. Many builders really feel sooner when utilizing them. Nevertheless, current research reveal a extra complicated actuality, particularly for knowledgeable groups engaged on production-level software program.
A 2025 randomized trial by METR, a nonprofit backed by Open Philanthropy, examined AI-assisted improvement in real-world circumstances. Sixteen seasoned open-source builders accomplished 246 coding duties utilizing instruments like Cursor Professional and Claude 3.5/3.7. Surprisingly, builders with AI help had been 19% slower on common.
Much more fascinating: the identical builders thought they had been working sooner. In actuality, a lot of their time was spent reviewing AI output, rewriting buggy ideas, and adjusting deceptive completions. Solely 44% of AI-generated code was accepted, and over 9% of dev time went to cleansing it up.
Why This Occurs — And Why It Issues
At Onix, we’ve noticed comparable patterns. AI provides a real pace increase for junior builders or early MVPs. However the carry isn’t computerized for senior engineers engaged on security-sensitive or legacy techniques.
Right here’s what slows groups down:
- Time spent prompting and tweaking AI-generated ideas
- Verifying unfamiliar package deal imports or hallucinated code
- Making certain outputs comply with our structure and elegance guides
- Cleansing up technical debt launched by fast AI patches
Briefly, AI can write code. However manufacturing software program is greater than writing, studying, testing, debugging, and sustaining. And that’s the place shortcuts can price greater than they save.
As TechRadar notes in its protection of the METR examine:
“Builders might understand a productiveness increase, however the actuality consists of extra time spent reviewing and correcting AI output — not much less.” (TechRadar)
The place Onix Stands — and Why
We’re dedicated to integrating AI instruments responsibly. That means:
- Utilizing AI to assist builders, not exchange them
- Prioritizing safety, code high quality, and long-term maintainability
- Making certain shoppers obtain secure, scalable, production-grade options
This additionally means not forcing AI the place it doesn’t match. A few of our builders have been fast to adapt AI into their workflow. Others take extra time — and we assist that. As a result of chopping corners on studying isn’t an possibility when constructing severe techniques.
As a improvement accomplice, our job is to ship worth, not velocity for its personal sake.
How We’re Transferring Ahead
To make use of AI successfully with out compromising supply requirements, we’re taking a structured method:
- ✅ Piloting instruments like Cursor and GitHub Copilot with junior groups and remoted options
- ✅ Implementing automated code scanning and peer evaluate gates for all AI-assisted code
- ✅ Rolling out inside coaching on immediate engineering, AI debugging, and code validation
- ✅ Accumulating inside metrics to trace whether or not AI truly improves time-to-value and high quality
We’re additionally coordinating this technique with our tech leads, who’re instantly concerned in validating the method, instruments, and affect, team-wide.
Last Ideas: AI Is a Instrument, Not a Shortcut
We perceive the stress to “go sooner with AI.” However we gained’t commerce high quality, stability, or safety for short-term hype.
As an alternative, we’re investing in the correct AI integrations that assist our staff ship higher work whereas assembly our shoppers’ excessive expectations.
Within the phrases of MIT Sloan:
“Generative AI provides massive boosts for lower-skill duties — however the positive aspects flatten on the high-skill finish. For senior devs, the affect is extra nuanced.” (MIT Sloan)
That’s exactly what we’re navigating immediately.
We’re studying, adapting, and at all times placing our shoppers first.
AI in Software program Growth at Onix: Progress, Challenges, and Why High quality Comes First was initially printed in Chatbots Life on Medium, the place persons are persevering with the dialog by highlighting and responding to this story.
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