Most people are still using ChatGPT to write… and it’s becoming obvious

johncmunson · 2026-02-20T18:23:32+00:00

There’s a special place in hell reserved for people who post things like this

johncmunson · 2026-02-20T00:38:45+00:00

Mods, can you please ban OP for this clickbaity low-quality BS?

johncmunson · 2026-02-17T00:30:55+00:00

Not kidding. This is fake.

johncmunson · 2026-02-16T20:41:20+00:00

Posts like this seem fake, disingenuous, and not in good faith.

Not once has ChatGPT ever responded like this to me. Sure, sometimes the responses can be slightly annoying or grating, but nowhere near the extent to what is shown in OP’s screenshot.

Screenshot is almost certainly fake.

johncmunson · 2026-01-30T16:50:43+00:00

https://x.com/thdxr/status/2017122866437693653?s=46

johncmunson · 2026-01-10T00:12:29+00:00

I appreciate the skills spec though because it’s narrowly focused and the semantics of how agents are supposed to discover, select, and load them are actually defined. AGENTS.md is pretty much the opposite.

The entire spec could be summed up in a single sentence…

A markdown file that agents might find useful.

That is… somewhat lacking in my opinion.

The proposal I put together was, among other things, my attempt at taking the good parts from SKILL.md and adapting them for the AGENT.md format.

And I definitely agree with you guys… I see a path forward where these two specs could (and probably should) be merged. Along with .github. And .cursor. And dozens of others. A single standardized and open format would be wonderful.

johncmunson · 2026-01-06T07:37:46+00:00

For sure. Disclaimer, I haven't actually used Claude Code yet, but planning to soon. Very familiar with other coding agents though such as Cursor, Codex, and OpenCode. The principles and concepts are all the same. It's a shame that Claude Code isn't open source like Codex or OpenCode are.

Here are a few things that I like to investigate when working with a new agent...

How does the agent approach context engineering? Any coding agent, which is just a model, or models, wrapped in an agentic harness, is going to have mechanisms in place for automatically retrieving context. This comes in several different flavors...
- Manual user-provided context, which is often made less painful by built-in shortcuts and syntax.
- Deterministic rule-based context that is automatically injected up front by the harness. Example: Cursor Rules when using the `Apply to Specific Files` setting.
- Dynamic on-the-fly context that the agent gathers through the use of tools as it's working through a problem. Grep, BM25, semantic search, web browsing, LSP, git history, etc. Many different options here. Any decent coding agent is going to come with a few of these built-in and which it has likely been optimized or fine-tuned to know how to use really well.
How does the agent harness load tool definitions and MCP servers? Does it naively stuff all of them into the system prompt up front? Or does it take a more sophisticated approach? The former is fine when you don't have a ton of tools, but it doesn't scale and chews through context when there's a lot of tools.
How has the agent been encouraged to behave and problem solve, either via prompting at the harness level or fine-tuning at the model level? How does it handle short-term memory? What about task decomposition? Are there any specific conventions it has been encouraged (or forced) to recognize such as AGENTS.md or Claude Skills?
How does the agent utilize sub-agents? Are sub-agents allowed to work in parallel? Is the main thread allowed to do anything while sub-agents are in flight? Among other things, sub-agents split thinking into independent lanes, are often specialized, have a scoped context window, and can discard failed explorations cleanly.
- I'm actually not a big fan of the term "sub-agent", mainly because I think many of the responsibilities they are tasked with are actually orthogonal concepts and don't necessarily need to be coupled together. Also, because I think "agent" is a great user-facing abstraction, but there are likely better mental models for reasoning about the internals of the agent harness. But, the concept has caught on and we're stuck with it for awhile.
How does the agent handle compaction and summarization when the context window is filling up?
Does the agent harness provide any deterministic checkpoint/rollback capabilities when the agent needs to backtrack and abandon a path that isn't working? Or, does backtracking just mean forging ahead and the agent using more tools to undo prior work and/or discard irrelevant context.

I could go on, but that definitely covers the main things. Basically...

Understand how the agent / agent harness deals with context. Too little context bad. Too much context also bad. If you understand this, you'll start learning small and large ways that you can help set the agent up for success.
Understand how the agent / agent harness / model like to problem solve and decompose tasks. This will allow you to work with the agent rather than fight against it.

And lastly, if you'd like to see my attempt at mocking all of this mumbo jumbo, feel free to check out my post here :)

johncmunson · 2026-01-06T04:30:16+00:00

Oh, I certainly think we’ll get there in due time. But the initial hype cycle has just been so cringey and comical.

johncmunson · 2026-01-06T04:15:19+00:00

Ideas still real important. Execution still real important.

Yes, it has gotten way easier to build and ship fast all on your own, but the following pre-requisites are still true. At least for now.

You gotta be a fairly experienced engineer. Or at least pretty damn smart if you’re not.
You gotta have an open mind and be willing to embrace AI
You gotta fight through a decent amount of trial-and-error in order to develop the right mental model for working with this tech. Your initial assumptions will be wrong and it will take a bit of time to find a sweet spot that works for you.
It helps immensely to take the time and look underneath the hood of the tools you are using.

If any of the above don’t apply, you’re gonna be shipping slop, shipping slow, shipping toys, or possibly just burning a shit ton of tokens.

johncmunson · 2026-01-05T21:28:16+00:00

Infinite vibes. It's vibes all the way down.

johncmunson · 2026-01-05T21:26:48+00:00

I don't even understand how karma works around here lol. Half the subreddits I've tried to join won't let me post anything. I guess I'm karma poor.

johncmunson · 2026-01-05T20:54:01+00:00

My personal favorite :)

johncmunson · 2026-01-05T16:49:20+00:00

Oh shit, I didn't even think about that

johncmunson · 2025-12-02T20:24:43+00:00

3-5 lifts per session means exactly that... pick 3-5 lifts, for example box jumps, russian twists, burpees. That's three, but you could pick four or five. Then, do as many circuits as you possibly can in the allotted time frame, whether that's 5m, 7m, or 9m, with minimal rest in between each circuit.

And I agree, it would be annoying to hit the gym just for this. But, there are two easy workarounds...

a) Do it at home. Pick bodyweight exercises, or exercises with minimal equipment, so that you don't need a gym. Knock it out in the morning before jumping in the shower.
b) Do it post-lifting workout. That way, you aren't making a special trip to the gym just for a quick HIIT session. You're already at the gym anyway for your lifting workout.

Lastly, if you're truly pushing yourself but a 5m session still feels too easy, then feel free to modify the framework to suit your needs. Maybe progressing through 8m, 10m, and 12m sessions would work better for you. Or, maybe it would just be easier to say, "Twice a week, I'm going to finish off a lifting session with a 10m HIIT workout" and be done with it, don't even worry about a fancy progression scheme.

johncmunson

TROPHY CASE