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…

Understanding Agent Frameworks, Runtimes, and Harnesses in AI Development

For feedback or concerns regarding this content, please contact us at [email protected]


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 specific needs. While LangGraph can be seen as both a runtime and a framework, the distinctions between these categories remain somewhat fluid. The development community continues to refine these definitions as they explore new mental models for AI development.

For a more detailed exploration of these concepts, visit the LangChain Blog here.

Image source: Shutterstock

Source: https://blockchain.news/news/understanding-agent-frameworks-runtimes-harnesses-ai-development

Market Opportunity
null Logo
null Price(null)
--
----
USD
null (null) Live Price Chart
Disclaimer: The articles reposted on this site are sourced from public platforms and are provided for informational purposes only. They do not necessarily reflect the views of MEXC. All rights remain with the original authors. If you believe any content infringes on third-party rights, please contact [email protected] for removal. MEXC makes no guarantees regarding the accuracy, completeness, or timeliness of the content and is not responsible for any actions taken based on the information provided. The content does not constitute financial, legal, or other professional advice, nor should it be considered a recommendation or endorsement by MEXC.
Tags:

You May Also Like

Here’s How Consumers May Benefit From Lower Interest Rates

Here’s How Consumers May Benefit From Lower Interest Rates

The post Here’s How Consumers May Benefit From Lower Interest Rates appeared on BitcoinEthereumNews.com. Topline The Federal Reserve on Wednesday opted to ease interest rates for the first time in months, leading the way for potentially lower mortgage rates, bond yields and a likely boost to cryptocurrency over the coming weeks. Average long-term mortgage rates dropped to their lowest levels in months ahead of the central bank’s policy shift. Copyright{2018} The Associated Press. All rights reserved. Key Facts The central bank’s policymaking panel voted this week to lower interest rates, which have sat between 4.25% and 4.5% since December, to a new range of 4% and 4.25%. How Will Lower Interest Rates Impact Mortgage Rates? Mortgage rates tend to fall before and during a period of interest rate cuts: The average 30-year fixed-rate mortgage dropped to 6.35% from 6.5% last week, the lowest level since October 2024, mortgage buyer Freddie Mac reported. Borrowing costs on 15-year fixed-rate mortgages also dropped to 5.5% from 5.6% as they neared the year-ago rate of 5.27%. When the Federal Reserve lowered the funds rate to between 0% and 0.25% during the pandemic, 30-year mortgage rates hit record lows between 2.7% and 3% by the end of 2020, according to data published by Freddie Mac. Consumers who refinanced their mortgages in 2020 saved about $5.3 billion annually as rates dropped, according to the Consumer Financial Protection Bureau. Similarly, mortgage rates spiked around 7% as interest rates were hiked in 2022 and 2023, though mortgage rates appeared to react within weeks of the Fed opting to cut or raise rates. How Do Treasury Bonds Respond To Lower Interest Rates? Long-term Treasury yields are more directly influenced by interest rates, as lower rates tend to result in lower yields. When the Fed pushed rates to near zero during the pandemic, 10-year Treasury yields fell to an all-time low of 0.5%. As…
Share
BitcoinEthereumNews2025/09/18 05:59
The Role of Blockchain in Building Safer Web3 Gaming Ecosystems

The Role of Blockchain in Building Safer Web3 Gaming Ecosystems

The gaming industry is in the midst of a historic shift, driven by the rise of Web3. Unlike traditional games, where developers and publishers control assets and dictate in-game economies, Web3 gaming empowers players with ownership and influence. Built on blockchain technology, these ecosystems are decentralized by design, enabling true digital asset ownership, transparent economies, and a future where players help shape the games they play. However, as Web3 gaming grows, security becomes a focal point. The range of security concerns, from hacking to asset theft to vulnerabilities in smart contracts, is a significant issue that will undermine or erode trust in this ecosystem, limiting or stopping adoption. Blockchain technology could be used to create security processes around secure, transparent, and fair Web3 gaming ecosystems. We will explore how security is increasing within gaming ecosystems, which challenges are being overcome, and what the future of security looks like. Why is Security Important in Web3 Gaming? Web3 gaming differs from traditional gaming in that players engage with both the game and assets with real value attached. Players own in-game assets that exist as tokens or NFTs (Non-Fungible Tokens), and can trade and sell them. These game assets usually represent significant financial value, meaning security failure could represent real monetary loss. In essence, without security, the promises of owning “something” in Web3, decentralized economies within games, and all that comes with the term “fair” gameplay can easily be eroded by fraud, hacking, and exploitation. This is precisely why the uniqueness of blockchain should be emphasized in securing Web3 gaming. How Blockchain Ensures Security in Web3 Gaming?
  1. Immutable Ownership of Assets Blockchain records can be manipulated by anyone. If a player owns a sword, skin, or plot of land as an NFT, it is verifiably in their ownership, and it cannot be altered or deleted by the developer or even hacked. This has created a proven track record of ownership, providing control back to the players, unlike any centralised gaming platform where assets can be revoked.
  2. Decentralized Infrastructure Blockchain networks also have a distributed architecture where game data is stored in a worldwide network of nodes, making them much less susceptible to centralised points of failure and attacks. This decentralised approach makes it exponentially more difficult to hijack systems or even shut off the game’s economy.
  3. Secure Transactions with Cryptography Whether a player buys an NFT or trades their in-game tokens for other items or tokens, the transactions are enforced by cryptographic algorithms, ensuring secure, verifiable, and irreversible transactions and eliminating the risks of double-spending or fraudulent trades.
  4. Smart Contract Automation Smart contracts automate the enforcement of game rules and players’ economic exchanges for the developer, eliminating the need for intermediaries or middlemen, and trust for the developer. For example, if a player completes a quest that promises a reward, the smart contract will execute and distribute what was promised.
  5. Anti-Cheating and Fair Gameplay The naturally transparent nature of blockchain makes it extremely simple for anyone to examine a specific instance of gameplay and verify the economic outcomes from that play. Furthermore, multi-player games that enforce smart contracts on things like loot sharing or win sharing can automate and measure trustlessness and avoid cheating, manipulations, and fraud by developers.
  6. Cross-Platform Security Many Web3 games feature asset interoperability across platforms. This interoperability is made viable by blockchain, which guarantees ownership is maintained whenever assets transition from one game or marketplace to another, thereby offering protection to players who rely on transfers for security against fraud. Key Security Dangers in Web3 Gaming Although blockchain provides sound first principles of security, the Web3 gaming ecosystem is susceptible to threats. Some of the most serious threats include:
Smart Contract Vulnerabilities: Smart contracts that are poorly written or lack auditing will leave openings for exploitation and thereby result in asset loss. Phishing Attacks: Unintentionally exposing or revealing private keys or signing transactions that are not possible to reverse, under the assumption they were genuine transaction requests. Bridge Hacks: Cross-chain bridges, which allow players to move their assets between their respective blockchains, continually face hacks, requiring vigilance from players and developers. Scams and Rug Pulls: Rug pulls occur when a game project raises money and leaves, leaving player assets worthless. Regulatory Ambiguity: Global regulations remain unclear; risks exist for players and developers alike. While blockchain alone won’t resolve every issue, it remediates the responsibility of the first principles, more so when joined by processes such as auditing, education, and the right governance, which can improve their contribution to the security landscapes in game ecosystems. Real Life Examples of Blockchain Security in Web3 Gaming Axie Infinity (Ronin Hack): The Axie Infinity game and several projects suffered one of the biggest hacks thus far on its Ronin bridge; however, it demonstrated the effectiveness of multi-sig security and the effective utilization of decentralization. The industry benefited through learning and reflection, thus, as projects have implemented changes to reduce the risks of future hacks or misappropriation. Immutable X: This Ethereum scaling solution aims to ensure secure NFT transactions for gaming, allowing players to trade an asset without the burden of exorbitant fees and fears of being a victim of fraud. Enjin: Enjin is providing a trusted infrastructure for Web3 games, offering secure NFT creation and transfer while reiterating that ownership and an asset securely belong to the player. These examples indubitably illustrate that despite challenges to overcome, blockchain remains the foundational layer on which to build more secure Web3 gaming environments. Benefits of Blockchain Security for Players and Developers For Players: Confidence in true ownership of assets Transparency in in-game economies Protection against nefarious trades/scams For Developers: More trust between players and the platform Less reliance on centralized infrastructure Ability to attract wealth and players based on provable fairness By incorporating blockchain security within the mechanics of game design, developers can create and enforce resilient ecosystems where players feel reassured in investing time, money, and ownership within virtual worlds. The Future of Secure Web3 Gaming Ecosystems As the wisdom of blockchain technology and industry knowledge improves, the future for secure Web3 gaming looks bright. New growing trends include: Zero-Knowledge Proofs (ZKPs): A new wave of protocols that enable private transactions and secure smart contracts while managing user privacy with an element of transparency. Decentralized Identity Solutions (DID): Helping players control their identities and decrease account theft risks. AI-Enhanced Security: Identifying irregularities in user interactions by sampling pattern anomalies to avert hacks and fraud by time-stamping critical events. Interoperable Security Standards: Allowing secured and seamless asset transfers across blockchains and games. With these innovations, blockchain will not only secure gaming assets but also enhance the overall trust and longevity of Web3 gaming ecosystems. Conclusion Blockchain is more than a buzzword in Web3; it is the only way to host security, fairness, and transparency. With blockchain, players confirm immutable ownership of digital assets, there is a decentralized infrastructure, and finally, it supports smart contracts to automate code that protects players and developers from the challenges of digital economies. The threats, vulnerabilities, and scams that come from smart contracts still persist, but the industry is maturing with better security practices, cross-chain solutions, and increased formal cryptographic tools. In the coming years, blockchain will remain the base to digital economies and drive Web3 gaming environments that allow players to safely own, trade, and enjoy their digital experiences free from fraud and exploitation. While blockchain and gaming alone entertain, we will usher in an era of secure digital worlds where trust complements innovation. The Role of Blockchain in Building Safer Web3 Gaming Ecosystems was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story
Share
Medium2025/09/18 14:40
Top Trader Says One Day the XRP Chart Will Shock Everyone. Here’s why

Top Trader Says One Day the XRP Chart Will Shock Everyone. Here’s why

XRP continues to show strong momentum, attracting attention across the crypto market. A recent post by XRP Queen (@crypto_queen_x) included a chart projecting the
Share
Timestabloid2026/03/13 13:02