Last week I released the first article in my hands-on 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗙𝗿𝗼𝗺 𝗦𝗰𝗿𝗮𝘁𝗰𝗵 series. It covers the tool use element of an Agent. I wanted to do this for quite some time now and finally the time has arrived! If you are using any orchestration

AI Supercomputer on my desk! 𝗡𝗩𝗜𝗗𝗜𝗔 𝗗𝗚𝗫 𝗦𝗽𝗮𝗿𝗸 has arrived and I finally got my hands on one of these beasts a few days ago. A quick reminder why it is a big deal: 🚀 NVIDIA GB10 Grace Blackwell Superchip. 💾 128 GB of Unified System memory - you can run models

🚨 ATTN. New Jersey: MIKIE SHERRILL… - Refuses to commit that she won’t raise New Jersey’s sales tax. - Her plan will “cost you an arm and a leg, but if you’re a good person, YOU’LL DO IT.” As Governor, Mikie Sherrill will make YOU PAY! Vote AGAINST her on 11/4.

AI Supercomputer on my desk! 𝗡𝗩𝗜𝗗𝗜𝗔 𝗗𝗚𝗫 𝗦𝗽𝗮𝗿𝗸 has arrived and I finally got my hands on one of these beasts a few days ago. A quick reminder why it is a big deal: 🚀 NVIDIA GB10 Grace Blackwell Superchip. 💾 128 GB of Unified System memory - you can run models

Integrating 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 Systems via 𝗠𝗖𝗣 👇 If you are building RAG systems and packing many data sources for retrieval, most likely there is some agency present at least at the data source selection for retrieval stage. This is how MCP enriches the evolution of

Integrating 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 Systems via 𝗠𝗖𝗣 👇 If you are building RAG systems and packing many data sources for retrieval, most likely there is some agency present at least at the data source selection for retrieval stage. This is how MCP enriches the evolution of

FTMO Verified prop traders walk their path. Rise now and start your FTMO Challenge!

𝗔𝗜 𝗔𝗴𝗲𝗻𝘁’𝘀 𝗠𝗲𝗺𝗼𝗿𝘆 is the most important piece of 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴, this is how we define it 👇 In general, the memory for an agent is something that we provide via context in the prompt passed to LLM that helps the agent to better plan and

𝗔𝗜 𝗔𝗴𝗲𝗻𝘁’𝘀 𝗠𝗲𝗺𝗼𝗿𝘆 is the most important piece of 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴, this is how we define it 👇 In general, the memory for an agent is something that we provide via context in the prompt passed to LLM that helps the agent to better plan and

The main 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗧𝘆𝗽𝗲𝘀 👇 It’s no secret that an AI Agent is a piece of software wrapping an LLM or multiple LLMs as a reasoning engine to guide its execution flow. The deployment types for these agents also closely resemble those of software or

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The main 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗧𝘆𝗽𝗲𝘀 👇 It’s no secret that an AI Agent is a piece of software wrapping an LLM or multiple LLMs as a reasoning engine to guide its execution flow. The deployment types for these agents also closely resemble those of software or

🎥 @NioCorp $NB: 30 Seconds Investors Should See • Construction-ready U.S. critical minerals project with all major permits secured • Offtake visibility: 75% of planned niobium output under long-term agreements plus the largest scandium sales deal on record • Financing

Building even a simple 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗴𝗿𝗮𝗱𝗲 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 (𝗥𝗔𝗚) 𝗯𝗮𝘀𝗲𝗱 𝗔𝗜 𝘀𝘆𝘀𝘁𝗲𝗺 is a challenging task. Read until the end to understand why 👇 Here are some of the moving parts in the RAG based systems that

Subscribe to my Newsletter to join 33.000+ AI Builders and Leaders learning about the latest in AI:

Building even a simple 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗴𝗿𝗮𝗱𝗲 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 (𝗥𝗔𝗚) 𝗯𝗮𝘀𝗲𝗱 𝗔𝗜 𝘀𝘆𝘀𝘁𝗲𝗺 is a challenging task. Read until the end to understand why 👇 Here are some of the moving parts in the RAG based systems that

𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 and what you need to know about it as an AI Engineer? Simple naive RAG systems are rarely used in real world applications. We are usually adding some agency to the RAG system - ideally a minimal amount. There is 𝗻𝗼 𝘀𝗶𝗻𝗴𝗹𝗲 𝗯𝗹𝘂𝗲𝗽𝗿𝗶𝗻𝘁 on how

Most new traders lose money because they skip the foundation. 📚 Study first. Trade later. Be patient. Follow for more trading tips.

𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 and what you need to know about it as an AI Engineer? Simple naive RAG systems are rarely used in real world applications. We are usually adding some agency to the RAG system - ideally a minimal amount. There is 𝗻𝗼 𝘀𝗶𝗻𝗴𝗹𝗲 𝗯𝗹𝘂𝗲𝗽𝗿𝗶𝗻𝘁 on how

Less talking, more building: 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗦𝘆𝘀𝘁𝗲𝗺 𝗳𝗿𝗼𝗺 𝘀𝗰𝗿𝗮𝘁𝗰𝗵! 👇 Some weeks ago I released an episode of my Newsletter and an update to the 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗛𝗮𝗻𝗱𝗯𝗼𝗼𝗸 GitHub repository. There I implemented a Deep

Less talking, more building: 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗦𝘆𝘀𝘁𝗲𝗺 𝗳𝗿𝗼𝗺 𝘀𝗰𝗿𝗮𝘁𝗰𝗵! 👇 Some weeks ago I released an episode of my Newsletter and an update to the 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗛𝗮𝗻𝗱𝗯𝗼𝗼𝗸 GitHub repository. There I implemented a Deep

𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗥𝗼𝗮𝗱𝗺𝗮𝗽. 👇 It is created with beginners in mind but can be easily adapted if you are proficient in some of the areas already. 𝘖𝘯 𝘢 𝘩𝘪𝘨𝘩 𝘭𝘦𝘷𝘦𝘭: 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 throughout the journey, but

Join me to learn above in my end-to-end AI Engineering bootcamp (10% off with code LastChance): https://t.co/X11eTSk3NP Next cohort kicking off next week!

𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗥𝗼𝗮𝗱𝗺𝗮𝗽. 👇 It is created with beginners in mind but can be easily adapted if you are proficient in some of the areas already. 𝘖𝘯 𝘢 𝘩𝘪𝘨𝘩 𝘭𝘦𝘷𝘦𝘭: 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 throughout the journey, but

🚨 Last call for a free Webinar: 𝘌𝘷𝘢𝘭𝘶𝘢𝘵𝘪𝘰𝘯 𝘋𝘳𝘪𝘷𝘦𝘯 𝘋𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵 𝘧𝘰𝘳 𝘈𝘨𝘦𝘯𝘵𝘪𝘤 𝘈𝘐 𝘚𝘺𝘴𝘵𝘦𝘮𝘴 🗓️ Today & 16:00 GMT Evals are notoriously difficult to implement in real world Agentic AI applications. Nevertheless, we cannot build reliable