Field guide Coding
Using Amp for Real Coding Work
How to brief, place, delegate, and verify a coding task with Amp.
With Agents · Post published 28 Jun 2026
Recently added
New to this library, not necessarily new to the world.
Added
Field guide Coding
Your Repo Is the Memory: Durable Context for AI Coding Agents
How to decide which coding-agent context belongs in chat, AGENTS.md, skills, work items, docs, tests, and saved results.
With Agents · Post published 2 Jul 2026
Field guide Coding
Make the Agent Prove It
A practical acceptance framework for agent-written code: the harder a failure is to undo, the stronger the evidence required.
With Agents · Post published 28 Jun 2026
Field guide Coding
Right-Sized Threads, Durable State
How to keep connected agent work in one thread, split only when separation helps, and carry accepted state across the boundary.
With Agents · Post published 28 Jun 2026
Added
video Coding
Building Pi in a World of Slop — Mario Zechner
Mario Zechner explains why he built Pi as a minimal, self-modifying coding-agent harness after frustrations with opaque context management and feature-heavy tooling. The talk covers Pi's small core and extension model, Terminal-Bench results, agent spam pressure on open-source maintainers, and a practical warning to slow down, scope agent tasks, and keep humans responsible for critical code.
AI Engineer · Source dated 16 Apr 2026
video Coding
I Hated Every Coding Agent, So I Built My Own — Mario Zechner (Pi)
Mario Zechner explains why he built Pi after Claude Code, OpenCode, and other harnesses stopped matching his need for predictable context, observability, and extensibility. The talk covers agent history from ChatGPT copy-paste to agentic search, Claude Code feature bloat, OpenCode context pitfalls, Terminal-Bench and Terminus as evidence for minimal harnesses, Pi’s four-tool design and TypeScript extensions, and defenses against agent-generated open-source spam.
Mastra · Source dated 31 Mar 2026
video Coding
A love letter to Pi | Lucas Meijer
Lucas Meijer shares habits for agent-assisted engineering: ask agents for HTML reports, make repositories easier to navigate, define evaluation criteria before a run, and request videos, screenshots, and slide decks that speed up review. The talk becomes a hands-on Pi demo covering tree-shaped context management, discarding unhelpful side quests, custom slash-command extensions, virtual-terminal visibility, and self-modifying software.
Build Monumental · Source dated 25 Mar 2026
video Coding
Simon Willison: Engineering practices that make coding agents work
Simon Willison explains the practical engineering habits that make coding agents useful today: red-green TDD, manual verification with real commands, conformance-driven development, high-quality scaffolds, sandboxed execution, fake data for risky workflows, and human review for code that will be maintained.
The Pragmatic Engineer · Source dated 19 Mar 2026
video Coding
The Friction is Your Judgment — Armin Ronacher & Cristina Poncela Cubeiro, Earendil
Armin Ronacher and Cristina Poncela Cubeiro argue that agentic coding needs the right friction: review checkpoints, modular codebases, deterministic rules, and human callouts for architecture, permissions, migrations, dependencies, and reliability decisions.
AI Engineer · Source dated 18 Apr 2026
video Coding
Collaborative AI Engineering: One Dev, Two Dozen Agents, Zero Alignment — Maggie Appleton, GitHub
Maggie Appleton argues that coding agents make implementation cheap enough that team alignment becomes the bottleneck. The talk critiques single-player agent workflows and demos ACE, GitHub Next's prototype for shared sessions, cloud computers, previews, terminals, and agent collaboration.
AI Engineer · Source dated 26 Apr 2026
video Coding
Pi Building Pi, OpenClaw's Minimalist Coding Agent
Mario Zechner demonstrates how he uses Pi to maintain Pi itself, pairing a deliberately minimal agent harness with strong human architectural control. The session covers minimalist tool design, self-modifying agent extensions, issue triage with GitHub CLI, deterministic checks, transcript-like branch workflows, and why human taste and module boundaries still matter when agents can generate code at high volume.
The Modern Software Developer · Source dated 12 Jun 2026
Collection additions Coding
The West Coast Builders — coding-agent collection
Eight selected conversations with Jinjing Liang, Gil Feig, Ben Vinegar, Thorsten Ball, Li Yin, Quinn Slack, Mario Zechner, and Peter Steinberger from Mayank Gupta's broader interview playlist. Topics include agent harnesses, parallel worktrees, inspectable session history, review, architecture, model economics, and durable context. Product claims and forecasts remain the guests' accounts, not independently verified results.
Mayank Gupta
3 summaries on this page
- Amp Code Founder on future of Coding Agents →
Source dated 2 Apr 2026
- LLMs are killing Agent Harness →
Source dated 20 May 2026
- Pi Agent Creator on future of Agentic Coding →
Source dated 28 Mar 2026
Collection summary Coding
Building Pi, and what makes self-modifying software so fascinating
From The Pragmatic Engineer — selected conversations
The Pragmatic Engineer · Source dated 29 Apr 2026
Collection additions Coding
Raising an Agent Season 1 - Series
A multi-episode series in which the Amp team documents building Amp. Topics include the shift from prompt to context engineering, autonomous feedback loops, sub-agent architectures for context management, the ‘Oracle’ pattern for multi-model reasoning, why codebases must adapt to agents, and evaluating models across providers. The team argues that results depend on model quality rather than hidden tricks, and treats agents as power tools rather than magic.
Amp, Inc.
2 summaries on this page
- Killing the Sidebar →
Source dated 5 Feb 2026
- The Assistant Is Dead, Long Live the Factory →
Source dated 22 Jan 2026
Added
podcast Coding
Amp: The Emperor Has No Clothes
Sourcegraph CEO Quinn Slack and Amp co-creator Thorsten Ball discuss the philosophy behind Amp, its 15-times-a-day shipping cadence without code reviews, and coding-agent architecture. Topics include why subagents and prompt optimizers may be misguided, the declining importance of model selectors, agent-friendly tooling, version control for agent-written code, and how agents change enterprise development workflows.
Latent Space · Source dated 26 Sept 2025
video Coding
The Emerging Skillset of Wielding Coding Agents
Beyang Liu traces AI coding tools from autocomplete to autonomous agents and defends contested design choices: autonomous edits, minimal UI, and model coupling. He covers Amp’s implementation, power-user practices such as detailed prompts, feedback loops, and sub-agents, and anti-patterns such as micromanaging and underprompting.
AI Engineer · Source dated 30 Jun 2025
video Coding
The Truth About Coding Agents: Why 90% of Your Time Is Now Code Review
Beyang Liu discusses Sourcegraph’s Amp agent and the shift from writing code to orchestrating agents, where he says 90% of time goes to code review. Topics include the ‘Smart’ versus ‘Fast’ agent architecture, Chinese open-source models for agentic tool use, and probabilistic software in which developers manage intent while agents handle implementation.
a16z Deep Dives · Source dated 25 Nov 2025