AI/ML Resources

AI Has Solved the Code Bottleneck. Now Engineering Leaders Have a Measurement Problem.

AI-assisted engineering is shifting the bottleneck from coding to verification. Learn why traditional metrics miss the hidden cost of AI-generated code.

October 8, 2026

by Igboanugo David Ugochukwu

CORE

· 1,770 Views · 2 Likes

OpenAI Watermarks ChatGPT and Codex: What Changes for EU Users

OpenAI will add invisible watermarks to eligible ChatGPT and Codex text in the EU. Learn how detection works, its limits, and what EU users should know.

October 7, 2026

by Liz Ticong

· 1,537 Views · 1 Like

AI Agents Leaked 13,000 Screenshots: Why Enterprise Approval Controls Failed

A reported leak of 13,000 screenshots shows how AI agents can bypass weak approval and audit controls even when organizations have written policies.

October 7, 2026

by Tim Freestone

· 1,725 Views · 1 Like

AI Agents for Software Engineering and Autonomous Development Workflows

Build reliable AI engineering agents with bounded autonomy, isolated workspaces, deterministic verification, permission controls, and measurable workflow evaluation.

October 7, 2026

by Jaswanth Mopathi

· 2,417 Views · 4 Likes

Agentic Workflows Without LLMs? How I Cut a 14-Hour Engineering Workflow to 2 Hours

Cut a 14-hour engineering workflow to ~2 hours — LLM agents only for reasoning, deterministic code for the rest. Good agentic design means knowing when to skip the LLM.

October 7, 2026

by Lucas Yoon

· 1,864 Views · 2 Likes

From Issue to Reviewable Patch: Build a Sandboxed Coding Agent With Deep Agents and Automated Tests

A sandboxed coding agent uses Deep Agents and automated tests to turn issues into tested patches ready for human review.

October 7, 2026

by Akhil Madineni

CORE

· 1,471 Views · 3 Likes

Classification Never Left. It Just Got a New Home in LLMs.

Jev and Laya are new models built only for fast, structured decisions: choice, score, or true and false, not text generation. They read input once and return a label.

October 7, 2026

by Vidyasagar (Sarath Chandra) Machupalli FBCS

CORE

· 1,294 Views · 3 Likes

Building and Serving a Custom Model With Azure ML, Then Wiring It Into a Foundry Agent

This guide walks through custom Azure ML model training and deployment to a Managed Online Endpoint and connecting it to a Microsoft Foundry agent as a function tool.

October 6, 2026

by Jubin Soni, FBCS

CORE

· 5,812 Views · 5 Likes

Resume the Evaluation, Not the Entire Batch: Build a Checkpoint-Aware AI Job Controller With Temporal

A checkpoint-aware Temporal controller resumes interrupted AI evaluations from saved progress instead of rerunning the entire batch.

October 6, 2026

by Akhil Madineni

CORE

· 1,596 Views · 3 Likes

Building an AI-Ready Data Layer Without Rebuilding the Enterprise

Learn in this article how to modernize data architecture gradually while preserving analytics, governance, and reliability.

October 6, 2026

by Rajaganapathi Rangdale Srinivasa Rao

· 1,066 Views · 1 Like

Grounding AI Agents in Governed Data

Stop trusting prompts alone to protect PII. Put AI agents behind the same governed semantic layer as your human analysts.

October 6, 2026

by Jeevan reddy Geereddy

· 1,093 Views · 1 Like

The Context Window Trap: Why More Context Doesn’t Mean Better AI

More context can create more noise, cost, and confusion. AI systems perform better when they retrieve, rank, and prioritize relevant information.

October 5, 2026

by Chidiebere Njoku

· 956 Views · 2 Likes

I Tried Building a "Token Optimization Stack" for Coding Agents. Here's Why I Killed It.

My token-saving stack for Claude Code broke 2 of 3 fixes — and its best savings number came from no op run. Killed it before a trustworthy test hit $1,200+.

October 5, 2026

by Shreyash Thakare

· 845 Views · 1 Like

Building Enterprise File-Heavy AI Workflows: From Secure Uploads to Governed Document Intelligence

A reference architecture for secure, scalable enterprise Document AI, covering ingestion, processing, retrieval, governance, and lifecycle management.

October 5, 2026

by Dr Gopala Krishna Behara

CORE

· 1,459 Views · 1 Like

Kill the Worker, Keep the Research: Build a Recoverable LangGraph Agent on Temporal

Temporal’s durable orchestration and LangGraph checkpoints enable research agents to recover from worker crashes and resume from saved progress.

October 5, 2026

by Akhil Madineni

CORE

· 1,957 Views · 3 Likes

AI on Top of a Dysfunctional System

Explore 10 Product Backlog anti-patterns that AI can make worse by masking dysfunction, missing evidence, and flawed decision-making.

October 2, 2026

by Stefan Wolpers

CORE

· 1,467 Views · 2 Likes

How a 30B Model Runs on Your Laptop

Big tech builds massive GPU data centers for LLMs, yet laptops can run models like Llama or Mistral locally. How is this done?

October 1, 2026

by Akash Lomas

· 2,253 Views · 2 Likes

Embabel vs LangGraph4j: Two Agentic Philosophies for Investment and Risk Analysis in BFSI

The architectural divide between state-machine rigidity and agentic flexibility in financial systems, comparing stateful, multi-agent workflows.

October 1, 2026

by Soham Sengupta

· 1,559 Views · 2 Likes

Are Passphrases Still Secure in the Age of AI?

Passphrases have long been considered the most pragmatic answer to weak passwords, but the usage of AI raises a fair question: does "long and random" still hold up today?

October 1, 2026

by Constantin Kwiatkowski

· 1,362 Views · 1 Like

Designing a Role-Aware Runtime for AI Avatar Systems

Use one shared runtime for AI avatars, with role profiles and adapters managing safety, tools, streaming, and each embodiment.

October 1, 2026

by Himanshu Gautam

· 1,205 Views · 1 Like

The Latest AI/ML Topics