FFerhat Yildiz3d ago · 66 min readAgentic AI: A Deep DiveFor much of AI’s history, the difficult part was turning a useful idea into a system that could handle unfamiliar situations. Today’s agents extend language models with tools and feedback. Understandiblog.turingts.com
GGabor KoosOct 20 · 33 min readHow to Build an AI Agent Harness from Scratch in TypeScriptMany AI agent tutorials start with a language model, give it a few tools, and run a loop until it produces an answer. That's enough to demonstrate tool calling, but it leaves the interesting engineerifreecodecamp.org
PPrathamesh ThakareOct 15 · 17 min readBuilding a Coding Harness From Scratch (Part 1) Why do coding agents behave differently? 🤔 I've been using Cursor for a while now, and recently I got access to GitHub Copilot. Switching between the two felt quite different, even when using the samprathamesh-thakare.hashnode.dev
AAkshay GuptaOct 10 · 5 min readUnder the Hood: The 4 Architectural Layers of an Enterprise AI HarnessIn the first part of this series, we established a foundational concept for enterprise AI: Agent = Model + Software Harness. We discussed how a raw language model is essentially a “brain in a jar”, inakshaykgupta.hashnode.dev
MMike DarlingtonOct 2 · 6 min readBetter models won’t fix a broken harnessAt the latest AAIF London event, five talks approached the same question from different parts of the stack: how do you actually make an agent better? I was there to present fx, the agent harness we’re32Xblog.darlington.dev
PParthaOct 1 · 12 min readJev Isn’t an LLM Replacement. It’s a Decision Plane for Agentic SoftwareMany agent systems use a frontier language model to answer questions that are fundamentally branches in code: Which queue should receive this event? Is this retrieval grounded? Does this proposed arpsarathy.hashnode.dev
EEmre ErtugrulSep 24 · 7 min readOverseeing software delivery with JevIn the agentic workflow world of Coro, every job, every task is a series of workflow steps, each handled by specialized agents one after the other, mimicking a real world software developer process. Thorizon-lab.hashnode.dev
IIresh SharmaSep 21 · 6 min readDon’t make the model pay 200 lines to find a functionCoding agents still read like find | cat: dump the tree, grep wide, page 200-line windows until context is landfill. Codeloom’s engine makes reading a cost hierarchy, then puts TypeSafe System One (je12ABblog.iresharma.com
AAkshay GuptaSep 20 · 6 min readDemystifying the AI Harness: What Makes Enterprise AI Actually WorkIf you spend enough time in enterprise technology right now, you’ll notice a distinct shift in the conversation. We are now talking about the Harness and how to apply it in the enterprise space In sim13MAakshaykgupta.hashnode.dev
NNikhil IkharSep 16 · 11 min readAgents Zero to Hero #5: Making an AI Agent Provider-AgnosticAgents Zero to Hero #5: Making an AI Agent Provider-Agnostic We've spent the first four checkpoints building the actual mechanics of an AI coding agent. So far, the progression has been: v0.1 → tool cnik-hil.hashnode.dev
