A joint research collaboration between researchers at the University of Illinois at Urbana-Champaign (UIUC), UC Berkeley, and the open source AI-native vector database platform Chroma unveiled Harness-1, a 20-billion parameter open-source search agent built atop OpenAI's gpt-oss-20B open source model that fundamentally redesigns how AI executes complex retrieval tasks. Harness-1 achieves a massive leap in performance, scoring 73% average on its ability to recall relevant information correctly from a curated dataset, outperforming even GPT-5.4 (70.9%) and the next, most accurate open source search agent, Tongyi DeepResearch 30B, by 11.4 percentage points. (While GPT-5.5 has also been out for more than a month, the researchers didn't test against this model as it wasn't availa [...]
As enterprise AI agents take on increasingly complex, long-horizon tasks, their performance is often restricted by their harness, the software scaffolding that connects the backbone LLM to its environ [...]
Not every company can or should build their own frontier AI language model. However, the harness controlling the model is something that most enterprises can and should customize for their specific pu [...]
Another day, another new AI agent harness is released.Only this time, it's one that aims to solve a growing enterprise problem as AI agents proliferate: enabling greater developer control of agen [...]
DeepSeek is expanding beyond the model layer and deeper into the software developers use to put AI agents to work.The Chinese AI lab on Thursday launched the official version of DeepSeek-V4-Pro, an up [...]
Consider an AI agent tasked with a complex enterprise workflow like migrating massive batches of customer records from a legacy CRM to a cloud database. The agent cannot rely solely on its internal co [...]
A rogue AI agent at Meta passed every identity check and still exposed sensitive data to unauthorized employees in March. Two weeks later, Mercor, a $10 billion AI startup, confirmed a supply-chain br [...]
As enterprise codebases grow, AI agents tasked with analyzing them are buckling under the weight of long-horizon tasks that require multiple interactions and tool calls. Dividing the work among a team [...]
Enterprise AI has a new infrastructure problem: companies are accumulating agents faster than they are developing systems to govern them.Gartner estimates that the average global Fortune 500 company w [...]