Andrej Karpathy says the goal is to maximize how long an agent runs without your intervention. But there's a false summit most teams hit first: individual speed goes up while system speed stalls, your laptop roars under four parallel Gradle builds, and review queues back up. Kaushik and Iury trace the full arc — from local multitasking to cloud-hosted async work to fully autonomous agents that fire on repo events and put PRs in your inbox.

• Andrej Karpathy on agents and token throughput - NoPriors podcast — maximize agent runtime, not token burn
• Cursor Agent Mode - Multiagent interface - introduced the multi-agent board as a new paradigm for local parallel agents
• Google Antigravity - Agent Manager interface
• Claude Code Agent Teams - spawn
  sub-agents from a main orchestrator, with tmux pane integration
• Git worktrees - /reddit

• Google Jules - hosted GitHub-connected agent,
  proposes a plan, edits code, runs tests, opens a PR
• Cursor Cloud Agents - remote agents
  that clone your repo in the cloud and work in parallel
• OpenAI Codex - cloud software
  engineering agent for parallel tasks
• Claude Code on the web - cloud-hosted Claude Code
  sessions decoupled from your local machine

• Episode 307 - Harness Engineering - the earlier episode on
  shaping agent environments — and why this ceiling exists

We'd love to hear from you. Email is the best way to reach us or you can check our contact page for other ways.

We want to hear all the feedback: what's working, what's not, topics you'd like to hear more on.

• Contact us
• Newsletter
• Youtube
• Website

• Kaushik Gopal
• Iury Souza

[!fyi] We transitioned from Android development to AI starting with
Ep. #300. Listen to that episode for the full story behind
our new direction.

You already know how LLMs work from our popular 20-minute explainer. Now we take it to images. What does Michelangelo have to do with stable diffusion? More than you'd think. Walk away knowing how image generation actually works — and what it has in common with the text models you already understand.

Full shownotes at fragmentedpodcast.com.

• Episode 303 - How LLMs work in 20 minutes - text generation
• VAE -
  Variational Autoencoder
• RGB Color model - wikipedia
• Word2Vec technique - wikipedia
  • Efficient Estimation of Word Representation -
    original Word2Vec paper by Mikolov et al.
• High-Resolution Image Synthesis with Latent Diffusion Models -
  Rombach et al. (2022) — the paper behind Stable Diffusion
• Image Training data
  • LAION-5B - 5 billion image-text pairs
    scraped from the web, used to train many image generation models
  • WebLI - Google's internal image-text
    dataset
• Michelangelo

We'd love to hear from you. Email is the
best way to reach us or you can check our contact page for other
ways.

We want to hear all the feedback: what's working, what's not, topics you'd like
to hear more on.

• Contact us
• Newsletter
• Youtube
• Website

• Kaushik Gopal
• Iury Souza

[!fyi] We transitioned from Android development to AI starting with
Ep. #300. Listen to that episode for the full story behind
our new direction.

The hard part of AI coding isn't generating code — it's controlling quality, safety, and drift. Kaushik and Iury break down harness engineering: the five pillars for shaping an agent's environment and what it looks like when teams build custom harnesses from scratch.

Full shownotes at fragmentedpodcast.com.

• Harness Engineering -
  OpenAI's post on building their Codex codebase (~1M lines of code, 1,500 PRs
  merged, zero manually written)

• The Feed's Lost and Found -
  Iury's newsletter consolidating harness engineering themes

1. Agent legibility
2. Closed feedback loops
3. Persistent memory
4. Entropy control
5. Blast radius controls

• Minions: Stripe's one-shot, end-to-end coding agents -
  Stripe forked Goose to build custom agents for their codebase
• Goose - open-source coding agent from Block
• Superpowers by Jesse Vincent - skills
  that enforce a proper software engineering process
• Open Code - open-source coding agent you can fork and
  customize

• Agent Harness Glossary -
  Latent Patterns
• Towards self-driving codebases -
  Cursor
• Agentic Workflows -
  GitHub Next
• Future of Software Development -
  ThoughtWorks

We'd love to hear from you. Email is the
best way to reach us or you can check our contact page for other
ways.

We want to hear all the feedback: what's working, what's not, topics you'd like
to hear more on.

• Contact us
• Newsletter
• Youtube
• Website

• Kaushik Gopal
• Iury Souza

[!fyi] We transitioned from Android development to AI starting with
Ep. #300. Listen to that episode for the full story behind
our new direction.

AGENTS.md is becoming the common language for AI coding tools, but keeping repo
rules, personal rules, and tool-specific files in sync is still messy. In this
episode, Kaushik and Iury break down the sync problem, compare their own setups,
and unpack what the latest AGENTS.md research actually says.

Full shownotes at fragmentedpodcast.com.

• AGENTS.md - Official spec
• Custom instructions with AGENTS.md -
  Open AI
• Keep your AGENTS.md in sync - Kaushik's post
• Rulesync - What Iury uses
• Tweet by Ryan Carson and Claude frustrations

• Evaluating AGENTS.md: Are Repository-Level Context Files Helpful for Coding Agents?
• Harness engineering - Check the section about using AGENTS.md as a table of contents
• OpenCode

We'd love to hear from you. Email is the
best way to reach us or you can check our contact page for other
ways.

We want to hear all the feedback: what's working, what's not, topics you'd like
to hear more on.

• Contact us
• Newsletter
• Youtube
• Website

• Kaushik Gopal
• Iury Souza

[!fyi] We transitioned from Android development to AI starting with
Ep. #300. Listen to that episode for the full story behind
our new direction.

Subagents are becoming a core primitive for serious AI-assisted development. In this episode, Kaushik and Iury disambiguate "agent" terminology, unpack plan mode vs subagents, and explain how parallel, scoped workers improve research quality without polluting the main thread.

Full shownotes at fragmentedpodcast.com.

Agents, Modes, Subagents: official harness docs

• Claude Code Subagents
• Gemini CLI Subagents
• Opencode Subagents
• Cursor Subagents
• Antigravity Agent Modes
• AOE Scouting

• Introducing Claude Opus 4.5
• Deep-Research Agents Paper
• Post: GPT-5 System Card by Alex
  Xu
• Self-Driving Codebases Blog -
  multi-agent systems making 1,000 commits/hour

We'd love to hear from you. Email is the
best way to reach us or you can check our contact page for other
ways.

We want to hear all the feedback: what's working, what's not, topics you'd like
to hear more on.

• Contact us
• Newsletter
• Youtube
• Website

• Kaushik Gopal
• Iury Souza

[!fyi] We transitioned from Android development to AI starting with
Ep. #300. Listen to that episode for the full story behind
our new direction.

Agent Skills look simple, but they are one of the most powerful building blocks
in modern AI coding workflows. In this episode, Kaushik and Iury break down when
to use skills, how progressive disclosure works, and how skills compare with
commands, instructions, and MCPs.

Full shownotes at fragmentedpodcast.com.

• Progressive Disclosure -
  how skills are loaded into context
• Agent Skills Open Specification
• AAIF (Agentic AI Foundation) -
  Linux Foundation initiative for AI interoperability
• Needle in a Haystack Problem - original
  "Lost in the Middle" paper
• Agent-Invokable vs User-Invokable -
  merging skills and commands in Claude Code

• Skill Creator -
  Anthropic's skill for creating new agent skills
• Claude Code frontmatter reference
  • see model: * & context: fork

• Anthropic Skills GitHub Repository -
  official collection of Claude skills and examples
• Clawdhub - Clawdbot's skill hub. All versions are
  archived here
• SKILLS.sh - Vercel's skills hub

[!warning] Don't install from hubs blindly.

Inspect the repo code before adding anything to your agent.

• Prompt Injection Attacks -
  OWASP guide to LLM prompt injection vulnerabilities
• OpenClaw <- MoltBot <- Clawdbot
• OpenClaw Security Analysis -
  analysis of prompt injection risks in open agent frameworks
• Malware found in a top-downloaded Clawhub skill -
  incident report thread

• Few-Shot Prompting -
  improving outputs with examples
• .agents/skills - proposal
  to standardize the skills folder path
• Vercel: AGENTS.md vs Skills -
  comparison of agent instruction methods

We'd love to hear from you. Email is the
best way to reach us or you can check our contact page for other
ways.

We want to hear all the feedback: what's working, what's not, topics you'd like
to hear more on.

• Contact us
• Newsletter
• Youtube
• Website

• Kaushik Gopal
• Iury Souza

[!fyi] We transitioned from Android development to AI starting with
Ep. #300. Listen to that episode for the full story behind
our new direction.

Ever get asked "how do LLMs work?" at a party and freeze? We walk through the full pipeline: tokenization, embeddings, inference — so you understand it well enough to explain it. Walk away with a mental model that you can use for your next dinner party.

_Full shownotes at fragmentedpodcast.com.

• OpenAI Tokenizer visualizer -
  Visualize how text becomes tokens

• RGB Color model - wikipedia
• Word2Vec technique - wikipedia
  • Efficient Estimation of Word Representation -
    original Word2Vec paper by Mikolov et al.

• Word embedding
• Temperature, Top-k, Top-p samping

We'd love to hear from you. Email is the
best way to reach us or you can check our contact page for other
ways.

We want to hear all the feedback: what's working, what's not, topics you'd like
to hear more on. We want to make the show better for you so let us know!

• Contact us
• Newsletter
• Youtube
• Website

• Kaushik Gopal
• Iury Souza

[!fyi] We transitioned from Android development to AI starting with
Ep. #300. Listen to that episode for the full story behind
our new direction.