open-weight LLMs have come a long way on agent tasks! but the harness you wrap them in matters just as much as the model itself, and arguabl…

open-weight LLMs have come a long way on agent tasks! but the harness you wrap them in matters just as much as the model itself, and arguably the interface you use to drive that harness matters even more. dev workflows are deeply personal. what works well for one developer may hinder another, so it's difficult to converge on a single UX that isn't either compromising or too generalized (e.g. CLI vs. TUI vs. GUI vs. IDE extension) while it doesn't come without drawbacks, ACP a solid stopgap for running the same harness across multiple interfaces. pick your frontend, keep your agent. deepagents ships with this out of the box -- two ways to plug it in: - deepagents-acp is our standalone ACP server to serve any agent - deepagents-cli --acp to use our existing CLI agent over ACP point any ACP-compatible client at it and you've got the same deepagents harness, your choice of open-weight model & provider, and your choice of interface. some popular exemplars: - toad is an agent-agnostic TUI that ships deepagents support built-in, made possible via ACP https://github.com/batrachianai/toad (@willmcgugan @textualizeio) - you can use deepagents directly in any modern IDE, see this blog post from @jetbrains coauthored by our very own @Hacubu: https://blog.jetbrains.com/ai/2026/04/using-acp-deep-agents-to-demystify-modern-software-engineering/) the model is yours to pick. the interface is yours to pick. the harness shouldn't be the thing that locks you in.

Source: Harrison Chase (X) | 2026-05-05