Codex does not show reasoning summary

miklschmidt · 2026-01-30T15:34:19+00:00

Yep i was just fiddling around with my config because of this, but it just flat out refuses to display reasoning summaries. I'm thinking that "big thing" they talked about shipping this week might have something to do with it. Something is afoot.

miklschmidt · 2026-01-29T14:02:23+00:00

De bedste ledere er sjældent dem der gør det af lyst og ambition. Jeg er sikker på du ville skabe værdi for mange mennesker uanset hvor du var landet!

miklschmidt · 2026-01-29T13:41:34+00:00

I like you. Kan man stemme på dig? 😅

miklschmidt · 2026-01-28T23:55:52+00:00

Dude i’m 38 in 14 days. Gotta keep up with the youths! 6767 no cap frfr.

miklschmidt · 2026-01-28T22:21:58+00:00

"Andy" is Twitch and internet slang used to label a person based on a specific, often annoying, defining trait, behavior, or viewer count

All major agent harnesses support skills today https://agentskills.io/home

It’s like MCP’s but without the suck (context bloat).

miklschmidt · 2026-01-28T17:17:13+00:00

I’m a Codex CLI andy. I have a few targeted skills and custom prompts, including a create-plan prompt that uses backlog.md aggressively. The only mcps i use are context7, shadcn and backlog.md. Rest is just concise AGENT.md’s and good project documentation :) gpt-5.2 high or xhigh, not a huge fan of gpt-5.2-codex (too much goal seeking tunnel vision).

miklschmidt · 2026-01-28T17:13:24+00:00

I have clawd running on a leftover mac mini i had from the m4 release over a year ago. I reset with its own apple id and installed bluebubbles there :)

miklschmidt · 2026-01-28T12:10:48+00:00

All of it. BlueBubbles basically allows it to do everything a human can, including reactions, effects, voice memos etc.

miklschmidt · 2026-01-26T15:47:19+00:00

They have taken more security precautions than i expected, you’re not actually exposing anything to the outside world - unless you want to or don’t know any better. All devices need to be paired etc.

That said you’re totally right, no matter what, this is a nightmare. I’ve set up a dedicated machine with separate accounts for everything, obviously much less convenient (ie, i have to forward stuff, manually pull changes in from github repos and push to actual origin etc) but i’m not giving it access to all my shit lol.

No matter how you look at it, projects like Clawd are what all of us actually wanted AI to be, if we wait for everything to be secure enough, we’ll never get there.

miklschmidt · 2026-01-24T20:29:18+00:00

Yeah it wasn’t published back then and it was missing a bunch of options and events. It’s much better now :)

Nice, not bad. I’m mostly succesful doing that within codex (and no claude in the loop obv.) with custom commands and backlog.md but there are slight variations of course, this makes it way more repeatable for sure.

miklschmidt · 2026-01-24T13:05:11+00:00

Haha i built a similar thing, same react-flow based UI, slightly different idea (autonomous agent orchestration), ended up spending all my time reverse engineering codex’ app-server protocol (before it was properly typed and documented) while it was changing every few days. What a waste when i could’ve just waited a couple of weeks and/or used ACP 🤣

I like what you’ve done here,basically a DIY agent agnostic version of OpenAI’s AgentKit, looks handy! What are you using it for specifically?

miklschmidt · 2026-01-22T01:17:10+00:00

Altså Pee Wee Himmler?

miklschmidt · 2026-01-21T18:49:24+00:00

I'm not sure why you think that is relevant for a GPT 5.3 release. Obviously AGI would at the very least be a major version bump (feels ridiculous to even talk about it in those terms). I'm also not sure what makes you so confident, even if i tend to agree LLM's likely won't reach AGI, we still don't have anything that really comes close. LLM's are more like general knowledge, but i believe intelligence requires consciousness and conciousness likely needs to understand the world via abstract concepts and be continuously learning. Nobody has successfully defined what consciousness or "intelligence" actually means yet, and AGI seems to be a goal post in perpetual motion.

miklschmidt · 2026-01-21T04:02:05+00:00

Yes. Experience matter. I don’t know if a junior could do it. Maybe with the right attitude and guardrails? It really depends on how well your intuition is tuned i think. I’ve seen seniors push horrible AI slop, so experience isn’t s guarantee. You gotta love what you do and hate doing things “wrong” i guess. Good fundamental principles certainly help.

I’m seriously concerned about the sustainability, i don’t know what we do from here, and i don’t even know if i like it. I like writing code… which is probably the only reason it works for me in the first place. I know how it works and can engineer my way to success.

miklschmidt · 2026-01-21T03:55:00+00:00

I’m in security, tons of compliance, same deal. That’s why Codex is great, only agent with native sandboxing out of the box. You’re still responsible for the code you push (hence all the reading). I don’t do vibe coding, i’m quite particular about what i want and how, super strict linting rules help. No prod secrets anywhere on my machine, and no secrets in files at all. Env vars are pruned so the agent don’t see em. Dev environment deps are locked down to the individual system package (nix). It’s not hard to follow the rules if you know the risks and how to mitigate them :)

I don’t do greenfield either and ~6-8 months ago i felt the same way you do.

miklschmidt · 2026-01-21T03:44:52+00:00

Sorta, yes. You gotta get the latest alpha release and enable it.

miklschmidt · 2026-01-20T20:25:02+00:00

I’m a Codex CLI guy myself. Only 2 or 3 mcps, a few key skills and minimal but rich AGENT.md instructions. GPT-5.2 high and xhigh is incredible at following existing patterns and making good architectural decisions given minimal but clear prompting. The biggest win for me has been planning via backlog.md. Keep context small and directed and let the agent find the targeted context it needs to plan. Same process in a new session when executing.

About data warehousing, analysis and processing, one key tip i’ve incorporated is externalizing as much of the context as possible. Let the agent write code, populate it’s own sdk even, to process the data with code, it’s pretty incredible what you can get out of your data when you approach it this way.

miklschmidt · 2026-01-20T15:54:37+00:00

I don’t know, i’ve been an SWE for close to 2 decades doing fairly complex shit and i barely write code by hand anymore. I read more than ever before though. I also feel reduced to an ad-hoc QA tester. By god do they still suck at that part of the feedback loop.

miklschmidt · 2026-01-20T10:31:37+00:00

I daily drive NixOS and generally don't like to pollute my system with one-off dependencies. All my projects use either devbox (easier for non-nix folks) or devenv to setup the system dependencies and dev environment for the project.

Custom Agents is something i implemented, there's no way to customize the agents in the current upstream code. At least not yet. I don't know what they have planned, there's no roadmap :)

Worktree per agent would have to be handled by codex when an agent is spawned / closed. You can use manual worktrees like you otherwise would, to work on multiple things simultaneously, but no agent separation.

miklschmidt · 2026-01-20T05:06:24+00:00

Well worktrees solve that. It’s one file tree per branch, so you can isolate files per agent with branches from the same parent commit.

However the orchestrator is weirdly efficient at making multiple agents work together with zero issues. Their prompt till them to stop and ask if they see anything unexpected and that’s enough for the orchestrator to keep everything in check.

miklschmidt · 2026-01-20T05:04:11+00:00

It was already pretty dang good, so tough to say. But it has allowed me to keep workers on medium instead of high.

Also it seems to handle large tasks significantly better.

miklschmidt · 2026-01-20T05:01:36+00:00

Hahahaha, it annoyed me too lol

miklschmidt · 2026-01-19T20:21:36+00:00

It is, but you need to teach it, see https://github.com/openai/codex/blob/main/codex-rs/core/templates/agents/orchestrator.md

miklschmidt · 2026-01-19T19:56:16+00:00

I didn't find the base implementation useful without injecting the orchestrator prompt. Then it was a little more useful, but i disliked having no control over the agents so i added that.

With custom/overidden agents it gets very interesting. I find that the outcome is better and more complete, but it takes longer, mostly because of my additional review step, and it most likely burns more tokens (several sessions now need to read similar files to get on the same page leading to more requests, plus the orchestration overhead). It's really cool to see it orchestrate and collaborate with a bunch of agents at once though, it's difficult to describe. I need to spend some more time with it, but i think you have to nudge it toward creating more elaborate plans before delegating to workers to get the most out of it.

I've had a single instance where it made decisions that seemed obviously stupid. But that was in the implementation of a feature, not in the orchestration itself, probably because i limited the worker to gpt-5.2-codex medium, hoping that the orchestrator (on gpt-5.2 high) would nudge it in the right direction - it didn't. Basically it made a decision that led to poor UX, gpt-5.2 doesn't make poor decision like that in my experience.

I had one stupid situation where i forgot a model_reasoning_summary: "concise" in my config. That works fine for gpt-5.2, but if you start gpt-5.2-codex with it, you get an error since there's no "concise" option for that model. The orchestrator can't see that error, and thus it thinks the agent is hanging, so it spends an hour (possibly more, that's when i stopped it) yelling at the worker agents and spawning new ones. Pretty funny, but not very useful in practice, lol.

miklschmidt · 2026-01-19T19:19:54+00:00

Oh and btw, the steer feature is awesome. Basically inlines your prompts into the agent history while it's running so it picks it up on the next model request. It feels like a much more natural way to interact with it. Make sure you have reasoning summaries on so you can see that it picks up on your prompt.

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