Thoughts on my own. Posts not reflect the opinions of my past or current employers. More about me: diegopacheco.github.io
Networking Troubleshooting/Debugging with Wireshark & tcpdump
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This is the 3rd and final post on the Apache Mina series. I highly recommend you check out posts I and II. tcpdump is very important networking debugging tool. tcpdump allows us to capture traffic because on a specific port. Wireshark is a visual(there is a terminal version as well) network capture and analyzer tool. We will use tcpdump to capture traffic between our mina TCP server app and a telenet client session. We will use the tcpdump capture to feed Wireshark and we will use Wireshark to understand what's going on between the client and the server on the network stack. Wireshark has a killer feature to follow TCP flow: meaning you can see all exchanges from client and server. So I made a video showing in detail this whole thing. So Let's get started.
I often don't blog about this kind of stuff. Yesterday I friend of mine showed me this awesome project called cool-retro-term . When you work with Cloud Computing and DevOps Engineering you spend lots of time on the black screen testing things on the cloud. When I saw this project I got very excited because it brings some nostalgy back to my life. To be 100% clearI'm not that old as my friend :-) However I share his joy into this retro terminals. This also reminds me some old games like Fallout 1 . I just this is pure fun so I'm sharing here with you guys some screenshots and also how to run on Gnome Ubuntu 17.04.
Harness Engineering is pretty trendy at the moment. Harness engineering is a way to better drive or operationalize an LLM model. The idea is that you are renting an LLM model as a service, but you own the harness. The harness is a way to be less dependent on the model (LLM). LLMs are not deterministic at all, and they are not general intelligence; they are pretty limited to their training data. Inference cost is very expensive, and the era of subsidizing is over . AI was sold as a promise to solve engineering and elevate us to a new level of abstraction, and so far thats far from being a reality. I keep hearing people say "wait two years" every year. More and more engineers spend more time trying to drive LLMs to produce the right code. When that is well executed, we can see 10-30 % productivity gains across our industry. Such good execution results from proper testing, robust CI/CD, great automation, amazing observability, and attention to technical excellence. When that is...
AI coding Agents like Claude Code , OpenAI Codex , and Gemini CLI have disrupted how software engineering is done. IMHO, the most disruptive agents are Claude code and Codex. However, a lot of things already happened, some progress has been made, and there is some evolution in the space. We saw the birth of custom and subagents to avoid passing the whole context window down, custom commands to have more control over a workflow, or when a specific task is executed. Hooks add more determinism and make sure tests and linters are executed as part of the guardrails. From the explosion of MCPs to Multi-Agent Systems. There are many interesting changes and evolutions happened, we learned somethings while some things are still to be learned. For this blog post, I will cover some of the evolution in AI coding agents (mainly around Claude code). I did a lot of POC with agents, 74 Agent-related POCs at the moment. One thing I keep saying is that POCs are getting expensive, now not ...