Today in the Gemini app, we’re unveiling a new image editing model from Google DeepMind. People have been going bananas over it already in early previews — it’s the top-rated image editing model in the world. Now, we’re excited to share that it’s integrated into the Gemini app so you have more control than ever …
Image editing in Google Gemini gets a major upgrade Read More »
In my last article, I shared how to use MCP to integrate LLMs into your full data science workflow. I also briefly mentioned another . A skill is a reusable package of instructions and optional supporting files. It helps AI handle a recurring workflow more reliably and consistently. At a minimum, it needs a SKILL.md …
Beyond Prompting: Using Agent Skills in Data Science Read More »
Image by Editor Contents# Introduction# Understanding Why This Stack Works# Reviewing Prerequisites# Step 1: Installing uv# Step 2: Creating a New Project# Step 3: Adding Dependencies# Step 4: Configuring Ruff (Linting and Formatting)# Step 5: Configuring Ty for Type Checking# Step 6: Configuring pytest# Step 7: Examining the Complete pyproject.toml# Step 8: Writing Code with Polars# Managing the Daily Workflow# Changing the Way You Write Python with …
Python Project Setup 2026: uv + Ruff + Ty + Polars Read More »
Today, we’re introducing Gemini 3.1 Flash TTS, the latest text-to-speech model that delivers improved controllability, expressivity and quality — empowering developers, enterprises and everyday users to build the next generation of AI-speech applications. Starting today, 3.1 Flash TTS is rolling out: Improved speech quality and controllability We’ve improved the overall speech quality of Gemini 3.1 …
Gemini 3.1 Flash TTS: New text-to-speech AI model Read More »
ContentsTL;DRThe Breaking Point of RAG SystemsWhat Context Engineering Actually IsWho This Is ForFull Pipeline ArchitectureComponent 1: The RetrieverComponent 2: The Re-rankerComponent 3: Memory with Exponential DecayDeduplicationToken Budget Under PressureComponent 4: Context CompressionComponent 5: The Token Budget EnforcerWhat Happens Under Real Token PressureMeasuring What It Actually Buys YouMemory Decay by Importance ScorePerformance CharacteristicsHonest Design DecisionsTrade-offs and …
RAG Isn’t Enough — I Built the Missing Context Layer That Makes LLM Systems Work Read More »
Image by Author Contents# Introduction# Understanding the .claude Folder# Establishing Why the Folder Is Created# Analyzing Common Files and Structure# Explaining How the Folder Operates# Evaluating the Deletion of the .claude Folder# Implementing Best Practices for Management# Identifying Common Developer Mistakes# Concluding Thoughts # Introduction You open a project, run a Claude-powered tool, and suddenly, there is a new folder sitting in your directory …
, my AI assistant stored a memory with an importance score of 8/10. Content: “Investigating Bun.js as a potential runtime swap.” I never actually switched to Bun. To be fair, it was a two-day curiosity that went nowhere. But this memory persisted for six months, popping up each time I asked about my build process …
Image by Editor Contents# Introduction# 1. Surgical Precision with Prompt-Based Slide Revisions# 2. Bridging the Gap with PPTX Export# 3. High-Fidelity Synthesis via Cinematic Video Overviews# 4. Frictionless Artifact Creation Directly from Chat# 5. Ingesting Scale: EPUB and Long-Form Source Support# The End-to-End Power Workflow # Introduction Google NotebookLM has evolved far beyond a simple study aid. With the addition of the …
Advanced NotebookLM Tips & Tricks for Power Users Read More »
ContentsIntroductionSetup of the CalendarsPrevious Months and different month lengthsWhat happens with the previous year?Weekly calculations – Head scratchingMixing weekly with monthly logicWeekly calculations – That’s interesting!ConclusionReferences Introduction After the initial euphoria with the new calendar-based time intelligence, I started looking deeper into the new feature to see what these new possibilities mean in the real …
When Things Get Weird with Custom Calendars in Tabular Models Read More »
Image by Editor Contents# Introduction# Understanding Method Chaining# Entering Pyjanitor: Application Example# Wrapping Up # Introduction Working intensively with data in Python teaches all of us an important lesson: data cleaning usually doesn’t feel much like performing data science, but rather like acting as a digital janitor. Here’s what it takes in most use cases: loading a dataset, discovering …
All About Pyjanitor’s Method Chaining Functionality, And Why Its Useful Read More »
