Introduction
At the start of 2025, AI still felt experimental. By the end of the year, it became routine.
Not because it replaced anyone’s expertise, but because it became integrated into our daily routines, making work a little faster and a little less frustrating. We asked our team which AI tools actually earned a place in their workflows this year; here’s what they had to say.
Debugging Was the Entry Point
For most people, AI showed up first as a debugging partner.
Whether through Copilot, Cursor, ChatGPT, or Gemini, these tools were consistently useful for interpreting error messages, fixing syntax issues, and working in unfamiliar languages. As one person put it, “They’re very strong in bash and handle simple bugs well.”
That trust faded with complexity. When problems spanned multiple files, pipelines, or HPC environments, AI became less reliable. “They’re great at fixing syntax issues but far less consistent when the problem spans several scripts,” another team member noted.
Faster Starts, Careful Finishes
AI helped with scaffolding code, prototyping analyses, and drafting documentation. “It can speed up a lot of analysis when things are straightforward,” one person said.
But no one described AI as something they trusted blindly. Algorithmic logic and deeper design still required human judgment. As one response cautioned, “You need to have a good understanding of what a solution should look like.”
AI made it easier to begin, not easier to stop thinking.
When AI Overreached
A recurring frustration on our team was AI over-eagerness.
Tools often tried to do too much at once, like rewriting large blocks of code or jumping to conclusions before the problem was fully defined. “The tools are over-eager and try to do too much,” one person observed.
The tools performed better when asked to perform smaller tasks with well defined boundaries.
The Quiet Wins Were Non-Coding
Some of the most valued tools weren’t for code at all.
Automated transcription in Zoom and Notion reduced the mental overhead of meetings. “It takes the pressure off capturing every detail and lets me focus on thinking,” one team member shared.
Notebook-style tools also helped people ramp up on new projects, synthesize background material, and explore mechanisms of action, acting more like research assistants than coders.
No One Tool Won
There was no single “best” AI tool in 2025.
People switched between tools depending on the task, the model version, and the level of trust required. As one person put it, “We need to get comfortable switching between these tools and their versions.”
Team members also noted the benefits of using multiple tools on the same task to cross check results and build trust in the outputs.
Industry Trends Echo Our Experience
The broader developer community is reflecting many of the same patterns our team has observed. According to the 2025 Stack Overflow Developer Survey, AI tool usage has become mainstream: roughly 84% of developers now use or plan to use AI tools in their workflows, and more than half of professional developers rely on them daily. At the same time, positive sentiment toward these tools has softened, with only about 60% of respondents viewing AI favorably and a notable share expressing skepticism about the accuracy of AI-generated outputs.
In other words, AI isn’t just something people experiment with anymore, it’s embedded in how developers work. But, like our team reflected, widespread adoption hasn’t erased the need for human judgment, professional expertise, or careful oversight.
What We’re Watching in 2026
Looking ahead, a few themes stand out:
- Better control, not bigger models
The biggest gains will come from interfaces that let humans review, constrain, and guide AI output more precisely. - Stronger multi-file and system-level reasoning
Debugging across pipelines, workflows, and environments remains a weak spot and a major opportunity. - AI as infrastructure, not novelty
Transcription, summarization, and context retrieval will continue to fade into the background as expected tooling. - Tool fluency as a core skill
Knowing when to use AI, which model to use, and when not to use it at all will matter more than brand loyalty.
2025 wasn’t the year AI took over.
It was the year it settled in and 2026 will be about deciding how deliberately we let it shape the way we work.
As AI becomes part of everyday work, the question is no longer if to use it, but how. Click here to schedule a free introductory call to discuss how Bridge Informatics helps teams navigate that shift thoughtfully and effectively.