JetBrains

ACP: The Universal Remote Control for AI Agents — Alex Hancock, Block

Sep 9, 2026 · 11:01

Alex Hancock, a Block engineer who works on the Goose harness and the MCP Rust SDK, argues agentic AI has a standard for agents reaching outward (MCP) but none for clients telling harnesses what to do — in the worst case one client per harness, like needing a different browser per website. His answer is ACP, the agent client protocol from Zed and JetBrains: JSON-RPC-based, carrying sessions, user messages, tool calls, and permission requests, and extensible via underscore-prefixed custom methods so shared patterns can move onto a standards track. He demos Zed and a Poolside terminal client driving the same Goose agent, plus a new HTTP and websocket remote transport. With remote transports for protocol, MCP, and models, all four pieces of the stack become independently placeable.

Building an ACP-Compatible Agent Live — Bennet Fenner, Zed

Jul 8, 2026 · 18:19

Bennet Fenner from Zed demonstrates building an ACP-compatible coding agent live, showing how the Agent-Client Protocol lets agents and editors communicate over JSON-RPC. He starts with a minimal agent that reads and edits files, then adds ACP support using the TypeScript SDK—implementing initialize, session creation, and prompt handling. Next, he streams model tokens via session updates, emits tool call progress with file paths and diffs, and proxies file system operations through the client. The demo culminates in the agent bootstrapping itself to add a terminal tool, which then runs shell commands inside Zed. ACP currently works over stdio; a remote transport is in development.

GitHub Copilot: The World's Most Widely Adopted AI Developer Tool

Feb 6, 2025 · 29:49

GitHub Senior DevOps Advocate Dave Bernason demonstrates how GitHub Copilot has evolved from an AI code generator to a comprehensive developer assistant with chat, enterprise knowledge bases, pull request summaries, and third-party extensions, emphasizing that Copilot keeps developers in flow and requires human oversight. He shows Copilot Chat explaining code, refactoring, debugging, and generating unit tests. Copilot Enterprise adds Bing search, knowledge bases from Markdown files, and repo indexing for accurate answers, exemplified by updating a hard-coded sales tax function to use the Avalara API. Copilot Extensions integrate third-party tools like Octopus Deploy for deployment dashboards within chat. Bernason also covers prompt engineering tips—specificity improves suggestions—and highlights Copilot's support for any language, even COBOL, for modernization.

Decoding Mistral AI's Large Language Models: Devendra Chaplot

Nov 21, 2024 · 18:16

Devendra Singh Chaplot of Mistral AI details the company's open-source large language models, including Mistral 7B, Mixtral 8x7B, Mixtral 8x22B, and CodeStral 22B, arguing that open models complement rather than compete with profit by serving as branding tools and driving customer acquisition for proprietary upgrades. He explains the three-stage LLM training process—pre-training on trillions of tokens, instruction tuning with prompt-response pairs, and learning from human feedback via preference optimization—emphasizing that more data does not guarantee better performance due to noise. The episode highlights Mistral's focus on optimizing the performance-to-cost ratio, with CodeStral 22B outperforming larger models like Code LLaMA 70B while being smaller and multilingual across 80+ programming languages. Practical guidance is given: prototype with high-end commercial models, then fine-tune open models for specific tasks to balance performance and cost.

Move Fast Break Nothing: Dedy Kredo

Nov 8, 2023 · 13:01

Dedy Kredo, co-founder and CPO of CodiumAI, argues that code generation needs a GAN-like architecture with a separate code integrity critic, and that behavior coverage is a more useful metric than code coverage. He demonstrates CodiumAI's IDE extensions (200,000 installs) on the open-source AutoScraper project (5,000 GitHub stars with no tests), automatically mapping behaviors, generating tests for happy paths and edge cases, and using reflection to auto-fix failures. The tool then enhances code with deep improvements (performance, security) and, via a PR assistant, catches a forgotten API key vulnerability. Kredo closes with a personal note about the Hamas attack on Israel, showing his co-founder on reserve duty while CodiumAI usage continues to rise.