Just Talk To It - the no-bs Way of Agentic Engineering | Peter Steinberger
This is a good read for AI coding. (Peter is the author of OpenClaw.)
The above reminds me of all the complex plugins I’ve looked at, and I get a little intimidated with my doc-driven development plugin. So it is refreshing to see this perspective - you don’t need to make it complex - use the model!
What about $openmodel#
I keep an eye on China’s open models, and it’s impressive how quickly they catch up. GLM 4.6 and Kimi K2.1 are strong contenders that slowly reach Sonnet 3.7 quality, I don’t recommend them as daily driver tho.
The benchmarks only tell half the story. IMO agentic engineering moved from “this is crap” to “this is good” around May with the release of Sonnet 4.0, and we hit an even bigger leap from good to “this is amazing” with gpt-5-codex.
Plan Mode & Approach#
What benchmarks miss is the strategy that the model+harness pursue when they get a prompt. codex is far FAR more careful and reads much more files in your repo before deciding what to do. It pushes back harder when you make a silly request. Claude/other agents are much more eager and just try something. This can be mitigated with plan mode and rigorous structure docs, to me that feels like working around a broken system.
I rarely use big plan files now with codex. codex doesn’t even have a dedicated plan mode - however it’s so much better at adhering to the prompt that I can just write “let’s discuss” or “give me options” and it will diligently wait until I approve it. No harness charade needed. Just talk to it.
What about MCPs
Other people wrote plenty about MCPs. IMO most are something for the marketing department to make a checkbox and be proud. Almost all MCPs really should be clis. I say that as someone who wrote 5 MCPs myself.
I can just refer to a cli by name. I don’t need any explanation in my agents file. The agent will try $randomcrap on the first call, the cli will present the help menu, context now has full info how this works and from now on we good. I don’t have to pay a price for any tools, unlike MCPs which are a constant cost and garbage in my context. Use GitHub’s MCP and see 23k tokens gone. Heck, they did make it better because it was almost 50.000 tokens when it first launched. Or use the
ghcli which has basically the same feature set, models already know how to use it, and pay zero context tax.
This again reinforces that the terminal is the future for the foreseeable future. I’ve heard multiple times now that MCPs blow up context and gobble tokens.
Conclusion#
Don’t waste your time on stuff like RAG, subagents, Agents 2.0 or other things that are mostly just charade. Just talk to it. Play with it. Develop intuition. The more you work with agents, the better your results will be.
And yes, writing good software is still hard. Just because I don’t write the code anymore doesn’t mean I don’t think hard about architecture, system design, dependencies, features or how to delight users. Using AI simply means that expectations what to ship went up.
PS: This post is 100% organic and hand-written. I love AI, I also recognize that some things are just better done the old-fashioned way. Keep the typos, keep my voice.
