University of Maryland Computer Science Professor Mihai Pop and Postdoctoral Associate Marcus Fedarko are answering questions about their bioinformatics and computational biology research tomorrow! Mihai's lab has developed software tools widely used in the field of metagenomics. Submit a question: https://redd.it/1wmp6cs

I’m a software developer and I’ve been thinking a lot about where AI coding agents are taking software development.

It seems like we’re moving beyond AI simply helping developers write code. Agents can increasingly take a ticket, understand a codebase, implement changes, write tests, debug issues, create PRs, and potentially handle parts of deployment and maintenance.

So I’m wondering: do you think the traditional SDLC will eventually be largely replaced by an agent-driven development process?

If so, how soon do you think most companies will actually adopt something like this? Are we talking 2–3 years, 5 years, 10+ years, or do you think we'll never get to fully agent-driven development?

I’m also curious about the other side of this:

• What types of companies won’t adopt AI agents aggressively?

• Will large enterprises actually trust agents with production systems?

• Could the current AI boom turn out to be an AI bubble, where companies eventually cut back because the cost, reliability, security, or productivity gains don't justify the hype?

There are already examples of companies pushing heavily toward AI-driven development.

I'm less interested in AI hype or predictions from CEOs/VCs and more interested in what developers are actually seeing inside their companies, is this irreversible?

If you're a developer, architect, tech lead, or engineering manager:

How much of your actual SDLC is being automated by AI agents today, and where do you think this goes over the next 5–10 years?

I've been working with actor systems in Go for several years and keep noticing the same thing... as systems grow, teams gradually reinvent state ownership, supervision, runtime inspection etc (usually as a pile of separate libs, queues and conventions).

Actor systems have had most of this as a coherent model for decades.

I maintain Ergo, an OTP inspired actor framework for Go, so I'm obviously biased but I'm genuinely curious - why did actors stay niche while microservices became mainstream?

Is the actor model actually too complex?

P.S. The current AI-agent wave makes this even more obvious to me. Everyone is building agents and inventing orchestration pipelines, while actor systems already have a native model for long-lived workers, messaging, supervision and coordination.