Isaac Flath & Eleanor Berger

Cohort 1

Cohort 2

Over 100 pages of answered questions, guides, and tips and tricks from Isaac Flath and Eleanor Berger!

Tips, Guides, and Answered Questions

A curated collection of LLM Context for building web applications efficiently with FastHTML. Includes `.ruler` formatted context, a Playwright MCP server example that works, and a small README tutorial to connect it all to Claude Code or other tools. This is the companion context to <a href="https://www.youtube.com/watch?v=CAxtf2nsnKE" rel="noopener noreferrer" target="_blank">this free talk</a> on Youtube

FastHTML LLM Context for AI Assisted Web Development

Are you making the most of AI-assisted development? Take this 5-part self-assessment to rate capabilities across foundational knowledge, interactive use, context &amp; environment, development process, and governance. Get a readiness score plus personalized priorities and learning resources.

Self Assessment: Are You Prepared for Making the Most of AI-Assisted Software Development?

Make it code like you do. Turn generic AI assistants into coding partners that actually get your style and have the right context.

AI Leader, ex-Microsoft, ex-Google

Eleanor Berger

Founder, Builder, OSS, & Consultant

Isaac Flath

Founder of Kentro Tech

Elite AI Assisted Coding

Senior Director, IT Ops

Operations 

Data Scientist

Lead AI Eng

Founder & Lead Researcher

Retiree

AI Engineer

developer

Product Owner (Self-employed)

Microsoft

Google

Canonical

Travel + Leisure

Cable & Wireless Communications

SpecStory

Answer AI

AnkiHub

Stop wasting time with generic AI suggestions. Learn to create a personalized AI coding partner that actually understands YOUR specific context and requirements, regardless of which AI tool you use (Cursor, Copilot, Amp, Claude Code, Windsurf, etc.).・Focus on real-world applications・Vendor-agnostic approach ensures long-term value・Continuous improvement through automated pattern analysis・Practical tools you'll use daily in production environments-Course Overview・Duration: 3 weeks, 12 live sessions・Format: Cohort-based course・Goal: Transform generic AI assistants into personalized coding partners that understand your codebase, patterns, and needsEach part (week) of the course includes:・2 live lessons・Office hours session (Q&amp;A and discussion)・Live practice session・Homework assignment (with both beginner-friendly and stretch exercises)・Pre-reads and lesson materials・Deep-dive collections (optional) for further studyIn addition, learning continues with:・Questions and discussions in the course Discord server・Guest lectures・Student exchange and collaboration Companies Our Students Are From・Amazon (AWS)・Microsoft・Google・X・Shopify・Cisco・LinkedIn・Red Hat・DocuSign・Booz Allen Hamilton・and more

Transform generic AI assistants into personalized coding partners

Spec First Planning and Context

Universal AI Setup System

AI Tools Setup And Usage

Enterprise Use and Security

Asynchronous agents

While this is not a coding course, this content is to help people code

Coding Experience

Developers who want to build technically solid solutions with confidence

Coders who want to move from copy-and-paste to consistent and reliable AI-assisted development skills

Engineers and leaders who need to adopt and grow dependable and repeatable AI-assisted software development processes

Customise Your Browser with Agentic Coding

Engineering & AI Leader; Elite AI-Assisted Coding co-instructor

Dev-efficiency and AI expert; Elite AI-Assisted Coding co-instructor

Follow along as we create working user scripts and extensions in real time using agentic coding tools.

Build user scripts and browser extensions live

Discover how to add missing features or change behaviours you don't like.

Tailor your browser to work your way

Let your AI agent figure out manifests, content scripts, and browser APIs for you.

Skip the learning curve with AI

Extend Your AI Agent with Custom Tools

See why a generic agent is limited and how purpose-built tools transform it into a powerful assistant for your work

Understand why custom tools unlock agent power

Follow along as we live-code each approach and walk through the key patterns

Build MCP servers, CLI scripts, and Skills from scratch

Identify which repetitive tasks and environment-specific needs would benefit most from custom tooling

Know what to build for your own workflow

Modern Multi-Vector Code Search

Aamir Shakir

Founder of Mixedbread

What's the technical difference between todays semantic search and a "standard" hybrid search + reranker from last year

What makes semantic search work for code?

Learn the latest architectures and how a "single" vector per chunk is replaced with "multiple" for better search

What is "multi-vector" search and semantic chunking?

Learn the challenges of a multi-vector search and how extreme quantization with clustering is done to make it possible

Why wasn't multi-vector done before?

The 1/2 Token Codebase Search.

Rui Huang

Mixedbread Founding Engineer

Performance comparisons for coding agents using agentic search vs new semantic search (quantitative and qualitative)

Understand why semantic search is back

Shows the simple setup prcess for having synced agent agnostic file watcher with semantic search

Set up the best semantic code search with mgrep

Learn to set up a scalable indexed approach that coding agents can use that scales to enterprise-sized codebases

Indexed Code Search for Private and Enterprise codebases

Agentic Coding Workflows with Qoder CLI and Quest Mode

Hang Yu

Product Lead for Qoder @ Alibaba

See how Quest mode operates independently in the background, and understand how this differs from interactive agents

Distinguishing autonomous AI coding from co-pilot approaches

Identify scenarios and task where delegating to autonomous agents produces better outcomes than real-time collaboration.

Identifying when autonomous coding is preferable to co-pilot

Examine actual production use cases that demonstrate how autonomous AI coding handles real-world development tasks.

Applying autonomous workflows to production code

Local Parallel Coding Agents with Vibe Kanban

Louis Knight-Webb

Cofounder & CEO @ Bloop

Run coding agents in parallel without conflicts.

Get to know Vibe Kanban

Focus on planning and quality instead of watching terminal logs with a tool for centrally managing your tasks.

Learn about local agent parallelisation

OpenHands: AI software development agent platform

Ray Myers

Chief Architect at All Hands

OpenHands is a leading open-source and hosted software development agent platform - versatile and powerful.

Get to know OpenHands

Learn from Ray about the power of agentic AI coding and how it fits within the broader software development landscape.

Learn about agentic AI coding

Learn to build agents with the newly released OpenHands SDK to go beyond the basics

Open Hands SDK

Build Your Own AI Coding Agent from Scratch

Hack together a tiny coding agent with us, end to end.

Build a simple AI coding agent

Understand how AI coding agents work so you can use them better.

Build a mental model of agents

Use context management, clear specs, small steps, interactive and structured flows.

Practice AI-assisted coding best practices

Agentic Code Search with GitHits

Olli-Pekka Heinisuo

Senior Applied AI Architect & Co-founder @ Softlandia

A clear mental model of how GitHits distils up-to-date, ready-to-use examples from public GitHub repos.

How Agentic Code Search Works

A live walk-through from a real task to a paste-ready snippet, including quick adaptation and verification.

From Problem to Working Code in Minutes

Practical tips for setup, privacy, limits, and when to trust results — plus how to pilot it with your team.

Isaac Flath & Eleanor Berger

Isaac Flath & Eleanor Berger

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