# What's Easy Now? What's Hard Now?

DevFeed: [What's Easy Now? What's Hard Now?](<https://devfeed.tech/articles/what-s-easy-now-what-s-hard-now-12595.md>)

Original publisher: [Read original article](<http://brooker.co.za/blog/2026/05/18/whats-easy-whats-hard.html>)

Author: Marc Brooker

Published: 2026-05-18T00:00:00Z

Content type: opinion

Language: en

Sources: [Marc Brooker's Blog](<https://devfeed.tech/sources/marc-brooker-s-blog.md>), [Marc Brooker's Blog](<https://devfeed.tech/sources/marc-brooker-s-blog-2.md>)

Topics: [AI-assisted coding](<https://devfeed.tech/topics/ai-assisted-coding.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [developer tooling](<https://devfeed.tech/topics/developer-tooling.md>), [Software Engineering](<https://devfeed.tech/topics/software-engineering.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [coding-agents](<https://devfeed.tech/tags/coding-agents.md>), [developer-tooling](<https://devfeed.tech/tags/developer-tooling.md>), [llm](<https://devfeed.tech/tags/llm.md>), [software-development](<https://devfeed.tech/tags/software-development.md>), [software-engineering](<https://devfeed.tech/tags/software-engineering.md>)

## AI overview

The article examines what coding agents are good and bad at as AI changes software development. It argues that coding agents can rapidly build meaningful, correct software at very low cost and can outperform humans on some tasks, while remaining less capable in others. It explains this behavior through feedback loops: agents combine an LLM's useful but flawed standalone behavior with iterative feedback, enabling capabilities beyond the LLM alone.

## Source excerpt

What's Easy Now? What's Hard Now? Take it easy. This is the fourth in a series about how AI is changing software development, after It's time to be right., What about juniors?, and My heuristics are wrong. What now?. It stands alone, but if you found this interesting you may also find those interesting. I've been spending a lot of time thinking about the shape of the capabilities of coding agents. What they're good at now, what they're going to be good at. What they're bad at now, how much of that is inherent and how much is transient. This is worth thinking about, because it's the most important question shaping the future of software, and of software engineering. I don't pretend to have an answer, but am coming to a conclusion that may be deeply counter-intuitive. Coding agents are becoming very good indeed, and can build meaningful and correct software very quickly and at transformatively low cost. They have super-human abilities on some coding tasks. Of course, computer systems have had super human abilities for at least 85 years1. I think we're going to find, as we have over those nine decades, that this new technology we're building is vastly super-human in some areas2, and not nearly as capable as humans in others. Which raises the important question of how, and why. Feedback is powerful Early on in my EE education, one of my professors drew a simple circuit on the board that's been stuck in my mind ever since. It looked like this3: Apply a voltage on the left, and on the right you get the square root of that voltage4. The two components are an opamp and an analog multiplier IC (e.g. the deeply obsolete MC1495). This simple circuit encapsulates possibly the most important idea in electrical engineering: feedback is uniquely powerful. Maybe unreasonably powerful. It's the idea that makes nearly every electronic device work, it keeps planes in the sky, and stops your oven from burning your dinner. Components inside feedback loops can be made to behave significa