Stanford's ACE paper was just open sourced
Details
- External ID
- 46141125
- Source
- HN
- Company
- —
- Product
- Stanford's ACE paper was just open sourced
- Website domain
- github.com
- Launched
- Dec. 3, 2025
- Cohort
- —
- Upvotes
- 8
- Upvotes percentile
- 0.4217557251908397
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:25 p.m.
- Updated at
- Sept. 7, 2026, 9:25 p.m.
Description
Last month, the SambaNova team, in partnership with Stanford and UC Berkeley, introduced the viral paper Agentic Context Engineering (ACE), a framework for building evolving contexts that enable self-improving language models and agents. Today, the team has released the full ACE implementation, available on GitHub, including the complete system architecture, modular components (Generator, Reflector, Curator), and ready-to-run scripts for both Finance and AppWorld benchmarks. The repository provides everything needed to reproduce results, extend to new domains, and experiment with evolving playbooks in your own applications.
Enrichment
- Theme
- AI agent frameworks and developer tools
- Vertical
- Horizontal
- Function
- Dev tools
- Audience
- Developer
- AI stance
- AI feature
- Project type
- Hobby / open-source project
- Normalized one-liner
- open source ace paper implementation
- Manually corrected
- False
Could you build this?
No ACE is a machine learning research paper implementation from Stanford/SambaNova dealing with complex agentic context engineering algorithms and model memory optimization.
What it would actually take: Requires an advanced ML research background to design and implement iterative prompt-optimization and context-refinement loops across agentic LLM trajectories. Development involves complex benchmarking harnesses, statistical evaluation pipelines, and integration with high-throughput inference backends like SambaNova or vLLM.
Discussion
1 comment analyzed.
Feature requests: CLI terminal with learning from interactions, Auto-update playbooks based on user interactions, Agents improve over multiple sessions
Competitors
Other products that read as similar to this one — 18 launches clear the similarity bar, closest 8 shown.
Attention rank: #11 of 19 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 30 days after the earliest competitor.
- Legit, Open source Git-based Version control for AI agents · hn · 2026-01-09 · 9 upvotes · similarity 0.36
- Framework for building multi-agent equity research agents · hn · 2026-02-25 · 6 upvotes · similarity 0.36
- AgentML · hn · 2025-11-03 · 5 upvotes · similarity 0.36
- Open sourcing our ERP (Sold $500k contracts, 7k stars) · hn · 2026-02-10 · 32 upvotes · similarity 0.35
- Ace from Automat Workforce · ph · 2026-09-30 · 77 upvotes · similarity 0.35
- LLM agents that write Python to analyze execution traces at scale · hn · 2026-03-07 · 5 upvotes · similarity 0.35
- AceEasily · ph · 2026-09-18 · 1 upvotes · similarity 0.33
- Paper2Any · hn · 2025-12-18 · 13 upvotes · similarity 0.33
Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a dev tools tool for Sales yet.