The post Understanding Agent Frameworks, Runtimes, and Harnesses in AI Development appeared on BitcoinEthereumNews.com. Tony Kim Oct 27, 2025 05:23 Explore the distinctions between agent frameworks, runtimes, and harnesses in AI development, focusing on LangChain, LangGraph, and DeepAgents, as detailed by the LangChain Blog. The LangChain Blog recently delved into the intricate world of agent frameworks, runtimes, and harnesses, offering insights into how these components function and interact within AI development. The discussion centers around three prominent open-source packages maintained by LangChain: LangChain, LangGraph, and DeepAgents. Agent Frameworks: LangChain LangChain is primarily identified as an agent framework, designed to provide abstractions that simplify application development. These abstractions serve as mental models, facilitating easier onboarding for developers and standardizing the building process. However, there are challenges associated with abstractions, particularly if they obscure the underlying processes or lack flexibility for advanced use cases. LangChain 1.0 emphasizes structured content blocks, agent loops, and middleware to enhance flexibility. Other notable agent frameworks include Vercel’s AI SDK, CrewAI, and OpenAI Agents SDK. Agent Runtimes: LangGraph LangGraph stands out as an agent runtime, essential for running agents in production environments. It addresses infrastructure-level needs such as durable execution, streaming support, and human-in-the-loop capabilities. Built from scratch, LangGraph is designed to be a production-ready runtime, powering agent frameworks like LangChain. Comparable projects in this space include Temporal and Inngest, which focus on durable execution engines. Agent Harnesses: DeepAgents DeepAgents represents a newer category, termed as an agent harness. It builds upon LangChain, offering features like default prompts, tool handling, and access to a filesystem, presenting a more comprehensive solution than a typical framework. This concept is akin to Claude Code’s approach with their Claude Agent SDK, although the term ‘agent harness’ is still gaining traction. Choosing the Right Tool Understanding the nuances between these components aids in selecting the appropriate tool for… The post Understanding Agent Frameworks, Runtimes, and Harnesses in AI Development appeared on BitcoinEthereumNews.com. Tony Kim Oct 27, 2025 05:23 Explore the distinctions between agent frameworks, runtimes, and harnesses in AI development, focusing on LangChain, LangGraph, and DeepAgents, as detailed by the LangChain Blog. The LangChain Blog recently delved into the intricate world of agent frameworks, runtimes, and harnesses, offering insights into how these components function and interact within AI development. The discussion centers around three prominent open-source packages maintained by LangChain: LangChain, LangGraph, and DeepAgents. Agent Frameworks: LangChain LangChain is primarily identified as an agent framework, designed to provide abstractions that simplify application development. These abstractions serve as mental models, facilitating easier onboarding for developers and standardizing the building process. However, there are challenges associated with abstractions, particularly if they obscure the underlying processes or lack flexibility for advanced use cases. LangChain 1.0 emphasizes structured content blocks, agent loops, and middleware to enhance flexibility. Other notable agent frameworks include Vercel’s AI SDK, CrewAI, and OpenAI Agents SDK. Agent Runtimes: LangGraph LangGraph stands out as an agent runtime, essential for running agents in production environments. It addresses infrastructure-level needs such as durable execution, streaming support, and human-in-the-loop capabilities. Built from scratch, LangGraph is designed to be a production-ready runtime, powering agent frameworks like LangChain. Comparable projects in this space include Temporal and Inngest, which focus on durable execution engines. Agent Harnesses: DeepAgents DeepAgents represents a newer category, termed as an agent harness. It builds upon LangChain, offering features like default prompts, tool handling, and access to a filesystem, presenting a more comprehensive solution than a typical framework. This concept is akin to Claude Code’s approach with their Claude Agent SDK, although the term ‘agent harness’ is still gaining traction. Choosing the Right Tool Understanding the nuances between these components aids in selecting the appropriate tool for…

        Highlights:  The BNB price is down 2% to $1111.46, despite the trading volume spiking 26%. The BNB on-chain demand has slipped, with the open interest plummeting 3% showing a drop in demand.  The technical outlook shows a tight tug-of-war, with the bulls attempting to overcome resistance zones.   The BNB price is down 2% today, to trade at $1111.46. Despite the plunge, the daily trading volume has soared 26% showing increased market activity among traders. However, BNB Chain has seen declining network activity, with the open interest plummeting, signaling a drop in demand.  On Chain Demand on BNB Cools Off The BNB Chain is in a state of cooldown of network activity, which indicates low on-chain demand. In most instances, when a network fails to ensure large volumes or revenues, it means that there is low demand or outflows to other networks.  BNB DeFi Data: DeFiLlama According to DeFiLlama data, the volume of the Decentralized Exchanges (DEXs) is down to at least $2.12 billion in comparison to the high of $6.313 billion on October 8, which also means low on-chain liquidity.  On the other hand, Coinglass data shows that the volume of BNB has grown by 3.97% to reach $4.95 billion. However, the open interest in BNB futures has dropped by 3.36% to reach $1.74 billion. This reduction in open interest is an indication of a conservative stance by investors since the number of new positions being opened is low. This could be an indication that investors are not so sure about the short-term price outlook. BNB Derivatives Data: CoinGlass Meanwhile, the long-to-short ratio is sitting at 0.9091. This shows that the traders are undecided on BNB price’s next move, as it sits below 1.  BNB Price Moves Into Consolidation The chart displays the BNB/USD price action on a 4-hour timeframe, with the token currently hovering around $1111.46. The 50-day Simple Moving Average (SMA) is at $1113, while the 200-day SMA sits at $1129, cushioning the bulls against upside movement. The price has mostly been trending below both SMAs, indicating that the bears are having the upper hand.  The BNB trading volume is up, soaring 26%, signaling the momentum is real. On the 4-hour chart, BNB is trading within a consolidation channel. In such a case, this pattern may act as an accumulation period, giving the bulls hind wings to break above resistance zones.  BNB/USD 4-hour chart: TradingView Zooming in, the Relative Strength Index (RSI) sits at 44.15, below the 50 level. This shows weakening momentum in the BNB market, and might lead to the RSI plunging to the oversold region if the bulls don’t regain control. In the short term, the BNB price could move up to $1113 resistance and flip it into support. A close above this zone will see the bulls target $1126 resistance, giving the bulls strength to reclaim the $1230 mark.  Conversely, if the resistance zones prove too strong, a dip towards $1012 could be plausible. In such a case, this could be a prime buy zone for the risk-takers. In the long term, if the token keeps the hype alive, the bulls may reclaim the $1375 high or higher.    eToro Platform    Best Crypto Exchange   Over 90 top cryptos to trade Regulated by top-tier entities User-friendly trading app 30+ million users    9.9   Visit eToro eToro is a multi-asset investment platform. The value of your investments may go up or down. Your capital is at risk. Don’t invest unless you’re prepared to lose all the money you invest. This is a high-risk investment, and you should not expect to be protected if something goes wrong.