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Gambit, an open-source agent harness for building reliable AI agents

Details

External ID
46641362
Source
HN
Company
—
Product
Gambit, an open-source agent harness for building reliable AI agents
Website domain
github.com
Launched
Jan. 16, 2026
Cohort
—
Upvotes
91
Upvotes percentile
0.8899868247694335
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

Hey HN!Wanted to show our open source agent harness called Gambit.If you’re not familiar, agent harnesses are sort of like an operating system for an agent... they handle tool calling, planning, context window management, and don’t require as much developer orchestration.Normally you might see an agent orchestration framework pipeline like:compute -> compute -> compute -> LLM -> compute -> compute -> LLMwe invert this so with an agent harness, it’s more like:LLM -> LLM -> LLM -> compute -> LLM -> LLM -> compute -> LLMEssentially you describe each agent in either a self contained markdown file, or as a typescript program. Your root agent can bring in other agents as needed, and we create a typesafe way for you to define the interfaces between those agents. We call these decks.Agents can call agents, and each agent can be designed with whatever model params make sense for your task.Additionally, each step of the chain gets automatic evals, we call graders. A grader is another deck type… but it’s designed to evaluate and score conversations (or individual conversation turns).We also have test agents you can define on a deck-by-deck basis, that are designed to mimic scenarios your agent would face and generate synthetic data for either humans or graders to grade.Prior to Gambit, we had built an LLM based video editor, and we weren’t happy with the results, which is what brought us down this path of improving inference time LLM quality.We know it’s missing some obvious parts, but we wanted to get this out there to see how it could help people or start conversations. We’re really happy with how it’s working with some of our early design partners, and we think it’s a way to implement a lot of interesting applications:- Truly open source agents and assistants, where logic, code, and prompts can be easily shared with the community.- Rubric based grading to guarantee you (for instance) don’t leak PII accidentally- Spin up a usable bot in minutes and have Codex or Claude Code use our command line runner / graders to build a first version that is pretty good w/ very little human intervention.We’ll be around if ya’ll have any questions or thoughts. Thanks for checking us out!Walkthrough video: https://youtu.be/J_hQ2L_yy60

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Agent / copilot
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
framework for building reliable ai agents
Manually corrected
False

Could you build this?

Yes An AI agent harness orchestrates LLM API calls, manages message context windows, handles tool schema execution, and plans steps, which is the exact type of software AI assistants excel at generating using Python or TypeScript.

Discussion

20 comments analyzed.

Competitors mentioned: Mastra, LangChain, Tenuo, OpenRouter

Concerns raised: Enforcement is probabilistic, not guaranteed security, PII protection claims lack guarantee despite rubric grading, Context leakage and lifetime management between agent calls, Prompt injection vulnerabilities in nested agent chains, Dense documentation and unclear how to do basic things like parameters

Feature requests: Support for Gemini API alongside OpenAI and OpenRouter, Load files as input text instead of just string literals, Deduplicate configuration (e.g., default language defined in one place), Constrain output length for tasks like summarize_text, Cryptographically signed warrants for authorization/capability verification

Competitors

Other products that read as similar to this one — 982 launches clear the similarity bar, closest 8 shown.

Attention rank: #116 of 983 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 79 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a agent / copilot tool for Agriculture yet.