Mateja Putic matejaputic

AI Writing Tropes to Avoid

Add this file to your AI assistant's system prompt or context to help it avoid common AI writing patterns. Source: tropes.fyi by ossama.is

Word Choice

"Quietly" and Other Magic Adverbs

Context Compaction

Research on how other coding assistants implement context compaction to manage long conversations.

Overview

Context compaction (also called "handoff" or "summarization") is a technique to manage the context window in long coding sessions. When conversations grow too long, performance degrades and costs increase. Compaction summarizes the conversation history into a condensed form, allowing work to continue without hitting context limits.

Claude Code

Native Secure Enclave backed ssh keys on MacOS

It turns out that MacOS Tahoe can generate and use secure-enclave backed SSH keys! This replaces projects like https://github.com/maxgoedjen/secretive

There is a shared library /usr/lib/ssh-keychain.dylib that traditionally has been used to add smartcard support to ssh by implementing PKCS11Provider interface. However since recently it also implements SecurityKeyProivder which supports loading keys directly from the secure enclave! SecurityKeyProvider is what is normally used to talk to FIDO2 devices (e.g. libfido2 can be used to talk to your Yubikey). However you can now use it to talk to your Secure Enclave instead!

Raspberry Pi 5 - Google Coral Edge M.2 TPU installation guide

To get started with either the Mini PCIe or M.2 Accelerator, all you need to do is connect the card to your system, and then install our PCIe driver, Edge TPU runtime, and the TensorFlow Lite runtime. This page walks you through the setup and shows you how to run an example model.

The setup and operation is the same for both M.2 form-factors, including the M.2 Accelerator with Dual Edge TPU.

Requirements

Raspberry Pi 5 with the following Linux operating system:
Raspberry Pi OS (64-bit) based on Debian 10 or newer

Moved to https://api.fmhy.net

Note

I’ve written a newer optimized 2026 version of this guide with a faster setup using Zinit + Starship and improved plugin loading.

This version avoids slow shell startups and works better with modern Zsh setups.

Updated guide: https://gist.github.com/n1snt/2cccc8aa5f7b645a7628d3512c70deb6

Oh my zsh.

how to leverage oracle's temping offers

free tier limits

The limits of the free tier say that you can create up to 4 instances.

x2 x86 instances (2core/1g)
x2 ampere instances (with 4core/24g spread between them)
200GB total boot volume space across all intances (minimum of 50G per instance)

[!WARNING]

	import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";
	import { spawnSync } from "node:child_process";
	import { mkdirSync, readFileSync, writeFileSync } from "node:fs";
	import { basename, join } from "node:path";

	const PLACEHOLDER = "[Review feedback]";
	const CUSTOM_PENDING = "review-feedback-pending";
	const CUSTOM_RESOLVED = "review-feedback-resolved";

	type PendingReview = {

	#!/usr/bin/python3

	import re
	import sys
	from tabulate import tabulate

	comments_re = re.compile(r'/\.\/')

	in_chain, eof = False, False
	headers, table = [], []

	<?xml version="1.0" encoding="UTF-8"?>
	<opml version="1.0">
	<head>
	<title>RSS subscriptions for chris.albon@gmail.com</title>
	<dateCreated>Sat, 27 Feb 2021 17:33:45 +0000</dateCreated>
	<ownerEmail>chris.albon@gmail.com</ownerEmail>
	</head>
	<body>
	<outline text="Google AI Blog" title="Google AI Blog" type="rss" xmlUrl="http://feeds.feedburner.com/blogspot/gJZg" htmlUrl="http://ai.googleblog.com/"/>
	<outline text="FastML" title="FastML" type="rss" xmlUrl="http://fastml.com/atom.xml" htmlUrl="http://fastml.com/"/>