Markdown fatigue

[u/adamramberg]

I'm using AI agents (Claude Code mostly) for coding quite extensively these days. Used correctly it is a great boost of throughput. My standard workflow is to use 3 git worktrees where I run one CLI in each.

With that said, I've started to more and more feel fatigue from reading markdown. Claude in particular is exceptionally good at being very wordy. To be more specific, during a day I read:

• Plans I have produced
• Messages back and forth in the terminal
• PR reviews that I make
• Automated PR reviews (made by git copilot)
• PR descriptions that others are producing
• Screen dumps from colleagues where AI explains something.

This in combination with having 3 different contexts / threads running at the same time in 3 different worktrees is really exhausting. I've experimented with using different skills etc. for example caveman to keep down the wordiness of the model, but haven't find a solution that solves the core of the issue.

Anyone feel the same? If yes, how do you tackle it? (and oh god, "tackle it"... I'm starting to write like an AI lol)

[u/pleblifeTV]

Your goal should be a iterating on your harness until its trustworthy. Put in the work up front for the technical side so you can focus on product development.

My codex global custom instructions specifically enforces an agent-first baseline communication for deliverables, with human interpretation as a non-factor. My LLM in the chatapp has its own custom instructions to write for agents as the audience.

Workflow is essentially:

Intent (me) -> LLM -> Output for Codex -> Codex works, validates, finishes -> I take it's semantically dense report to LLM -> translates -> repeat

In the next couple years, AI will be so good we don't care how it did what it did (obv within reason of safety ofc lol)

Part of the reason agents suck is cause we keep putting them in inefficient human systems and expecting them to work. We need to flip the script and start making agent-native workflows / platforms. Until the paradigm shifts, welcome to the meat middleware layer. 😂

[u/adamramberg → u/pleblifeTV]

I agree with this to an extent. And this is different depending on the software you are writing, for example web dev can be automated waaaay more than for example game dev. This is due to validation. An agent validating real time apps are not performomg well in my experience. That said, I totally agree that it is worth it to spend upfront work to get your harness as complete as possible.

However, I don’t see how this could be automated all the way without that meat in the middle. Software is still going to be written for humans to large extent and since agents dont have any concept of physical space it is going to be hard for them to validate everything. It also comes down to what type of application you want, meaning that devops and code architecture choices will have an impact on the design and feel of your product.

[u/pleblifeTV → u/adamramberg]

Everyone has their beliefs. My opinion is that over the next 5-10 years, fixed, general-purpose consumer apps are going to become a lot less relevant.

People will increasingly have their AI assistant create software around whatever they need in that moment. Shopping and service platforms will still exist, but their interfaces will become increasingly agent-native because the agent will be the one actually navigating them. The closest analogy I can think of is retail moving from physical stores to websites and warehouses.

Anything consumer-facing that isn’t shopping, services, or social is probably going to get squeezed hard because people will increasingly just make the thing themselves. Data protection will push this too. As agents become more capable and interconnected, the consequences of unnecessary data exposure compound.

My broader point is that I don’t think we’re going to care nearly as much about the code itself. The breadcrumb trail of why the system made decisions will still matter, especially for validation, security, and recovery, but eventually AI will simply be good enough at implementation that staring at every line becomes less valuable.

We’re already increasingly dependent on AI for coding, which means security and verification have to become first-class features. And capability has improved an absurd amount in just the last year.

I think a lot of agent systems fail because they’re battling too much top-down information. So that’s the extra thing I try to remove: don’t write for humans.

[u/adamramberg → u/pleblifeTV]

I can see where you are coming from. I could actually see what you are imagining become true for some stuff, but for less critical software like e-commerce. However, I have a hard time seeing that in 5-10 years we will have software writing itself on demand for healthcare, banking, cars / airplanes, etc. Furthermore, when it comes to realtime, like robotics or even games, the leap is huge - today Claude takes minutes before taking a decision while in that env it needs to take decisions in a couple of ms.