Grok Bot, Claude Code, and Codex Share One Second Brain
Author(s): Rick Hightower Originally published on Towards AI. Reads on main. Writes on a worktree/branch. How typed links and a write boundary stop agents from clobbering each other. Summary: The context window is the agent’s working memory. I have agents running in …
CrewAI I: The Multi-Agent System You Keep Hand-Wiring, Already Built
Author(s): Rick Hightower Originally published on Towards AI. Part 1: The throwaway orchestration glue you keep rewriting every time two LLM calls have to cooperate is exactly the thing CrewAI was built to delete. You have done this before. Two model calls …
One Formula to Map the Positional Encoding Landscape
Author(s): Gaurav Chawla Originally published on Towards AI. One Formula to Map the Positional Encoding Landscape Every survey of positional encoding I have read presents the methods as a chronological parade: sinusoidal, then learned, then relative, then RoPE, then ALiBi. That framing …
The Anomaly Detector That Learns by Counting
Author(s): Gaurav Chawla Originally published on Towards AI. The Anomaly Detector That Learns by Counting 10,000 Bayesian models, no training loop: how conjugate priors caught red-team activity in a billion-event authentication log Bayesian statistics gives you a principled way to combine prior …
Unlocking Rotational Dynamics via data-RoPE
Author(s): Mohit Sewak, Ph.D. Originally published on Towards AI. Unlocking Rotational Dynamics via data-RoPE A physical gyroscopic model illustrating how data-dependent RoPE restores continuous complex rotational dynamics to real-valued state space architectures. Late one evening in early 2024, sitting over a rapidly …
How Deep Research Agents Turn Complex Questions Into Trusted Answers
Author(s): Shahidullah Kawsar Originally published on Towards AI. AI Engineer Interview Preparation Click here for the full AI Engineer Prep list. Read this blog free. The rest of the article is an interview-style quiz (multiple questions) on how deep research agents should …
How to Find the Optimal Coding Agent Interface
Author(s): Eivind Kjosbakken Originally published on Towards AI. How to Find the Optimal Coding Agent Interface The interface that you use to interact with your coding agents is very important. There is a large variety of options out there that you can …
Reading a Model’s Hidden Layers with Anthropic’s Jacobian Lens
Author(s): Ejiro Onose Originally published on Towards AI. Reading a Model’s Hidden Layers with Anthropic’s Jacobian Lens When a language model answers a question, most of the computation happens in the middle of the network(the hidden layers), long before you see the …
Prompt Injection and Agent Security: The Unsolved Problem
Author(s): Shrashti Singhal Originally published on Towards AI. Your agent can’t tell your instructions from an attacker’s. Nobody’s fully fixed that — and the more capable your agent gets, the more that costs you. Part nine of a series on building production …
Power BI’s ADBC Migration Has Started. What Databricks, Snowflake and BigQuery Teams Need to Test This Month.
Author(s): Gulab Chand Tejwani Originally published on Towards AI. There is a migration happening in Power BI that almost nobody is writing about, and the reason is that it is not a feature. It is a driver swap. Microsoft is replacing the …
Part X — Z-Ordering and Data Clustering Explained: Why Your Partitioned Table Still Scans Everything
Author(s): chakshu_salgotra Originally published on Towards AI. Part X — Z-Ordering and Data Clustering Explained: Why Your Partitioned Table Still Scans Everything Data skipping, min/max statistics, space-filling curves, and liquid clustering — the file-layout mechanics that decide whether your query reads 40 …
Your Fabric Capacity Isn’t Slow — It’s Throttled
Author(s): Priyanka Shah Originally published on Towards AI. Bursting, smoothing, carryforward and burndown — plus the Capacity Metrics chart that tells you whether you can wait it out or have to intervene. The reports didn’t break. That was the confusing part. The …
GPT-5, Llama And Qwen Agree: YAML Is Smaller Than JSON And Costs More Tokens
Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. Ten serialisations, seven production tokenizers. Across a hundred records YAML is 3% fewer bytes than minified JSON and 21% more tokens — and the format nobody suggests halves it again. …
From Prompt to Diagram to Pull Request: Building AI-Powered Collaboration on a Visual Canvas
Author(s): Dave R – Microsoft Azure & AI MVP☁️ Originally published on Towards AI. How Lucid’s AI diagramming, AI whiteboarding, and the Lucid MCP server let AI agents create, share, and update living documents, with a map to the Microsoft AI stack. …
Llama 3.2 Needs Eight Tokens For One Bengali Word. Gemma 3 Needs One.
Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. Eight tokenizers, the same document, twenty-one languages. The seven current ones agree on English to within four percent — and disagree by up to 4.95x once you leave it. মানুষ …
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