Software Engineering and AI insights

I am maintaining this list actively.

I work day to day in software engineering where all everyone talks about is AI and it's impact.

I am anti-AI when it comes to creative arts, music, entertainment etc.

I am generally middle of the road when it comes to AI use for productivity.

I read AI research papers, test out AI tools, and experiment with coding agents at work to give myself the opportunity of a fair assessment.

Things AI Agents are contributing to software engineering:

Generating trivial and tedious code.
Greatly improving intellisense.
Maintaining dependencies.
Maintaining and configuring CI pipelines, automation and bash scripts etc.
Providing decent human-readable insights into stacktraces that then help me figure out a bug quicker. (Note - not actually fixing the bug itself or figuring it out).
Saving ~10% of the time it took me to write some non-trivial code by offering me suggestions on what I might want to type next.
Saving ~30% of my time doing some refactoring.
Shortcutting documentation and note taking, particularly with incidents.

Working well with technical people.
Working well with non-technical people.
The inertia of big organisations.
Co-ordinating and prioritising roadmaps.
Making the hard decisions of what we work on now versus what we drop.
Discovering the most valuable solution to a user's problem.
Discovering the most pragmatic solution to a user's problem.
Figuring out what "pragmatic solution" means within the context of the tech stack, code, problem space, stakeholder appetite and timelines.
Innovative and novel approaches to existing solutions.
Teaching a stakeholder to talk about their problem and not the solution they want.
Pairing back a fully featured product to it's thinest slice of value.
Managing the healthy tension between releasing today to create a small amount of value, and releasing next week with a more fully featured product.
The "shower thinking" and "programmer's dream" divine inspiration.
The knowledge you have built about the domain you work in.
Knowing the "gotchas" that aren't described in code, or documented, but are inherent behavioural issues that occur when a new feature is introduced or novel interactions are seen.

Providing some productivity boosts in the programming portion of a software engineer's job.
Distracting decision makers from identical value produced through cheaper, quicker, more deterministic, less carbon-intensive means.
Making a lot of decision makers solution's tool first, not problem first.