#llm

GGetPochigetpochi.hashnode.dev

Five Practical Tips to Save Token Consumption with Pochi

The usual experience with coding agents is predictable - they start out sharp, then slowly become confused, verbose, and expensive. Instructions keep piling up, tools accumulate, and failed attempts l

11h ago10 min read

SCSourish Chakrabortyblogs.sourishchakraborty.com

LLM Engineering 101: Mastering the Modern AI Stack

In the world of 2026, "generative AI" has evolved from a novelty into a rigorous engineering discipline. Whether you are building an autonomous agent or a simple summarizer, success lies in understand

1d ago5 min read

LLundqwayoflme.hashnode.dev

The Way of The Language Model Engineer

We build walls, carve doors, and open windows yet it is the empty space within that makes a house a home. In stillness, there is usefulness. In restraint, there is capacity. Yet emptiness alone cannot

11h ago5 min read

MSMahaboob Subhani Syedsubhani-syed.hashnode.dev

Engineering ResumeRoast: Security by Design

As software engineers we should think about security before something breaks. Before the bill spike. Before the user complaint. Before the bot hammers the endpoint. Most of us don't. This post is abou

15h ago7 min read

RBRishabh Bassirishabhbassi.hashnode.dev

5 Hard-Learned Lessons from Building Production Agentic AI Systems

We've all been there. Your agent performs beautifully in a sandbox: it chains tools, plans multiple steps, and completes tasks in a demo. The logs look clean, the demos impress stakeholders, and you'r

17h ago4 min read

DGDevTools Guidedevtoolsguide.hashnode.dev

Aider: AI Pair Programming in Your Terminal

AI coding tools have split into two camps: IDE plugins that work inside your editor (Cursor, GitHub Copilot, Windsurf) and terminal-based agents that operate on your entire codebase from the command line. Aider is the most mature tool in the second c...

6h ago5 min read

JSJaipal Singhpremai.hashnode.dev

Llama vs Mistral vs Phi: Complete Open-Source LLM Comparison for Enterprise (2026)

There is no "best" open-source LLM. Only the right LLM for your specific task, hardware, and constraints. That's not a cop-out. It's the reality every enterprise discovers after deploying their first

10h ago17 min read

CCypherLambcypherlamb.hashnode.dev

Between Simulation and Emergence: The Identity Problem in Large Language Models

A lot of successful jailbreaks based on language alone follow the same pattern, though it is rarely acknowledged as such. First, they sever the name. "Ignore all previous instructions", a crude banish

16h ago9 min read

MRMoon Robertsynsun.hashnode.dev

Fine-tuning vs RAG: When to Use Each Approach for Production LLMs

# Fine-tuning vs RAG: When to Use Each Approach for Production LLMs You've shipped a proof-of-concept with GPT-4, your demo went well, and now engineering leadership wants it in production by next quarter. Then someone asks the question that keeps M...

18h ago10 min read

MRMoon Robertsynsun.hashnode.dev

Building Production-Ready RAG Applications with Vector Databases

Building Production-Ready RAG Applications with Vector Databases Most RAG prototypes look impressive in a notebook. Then they hit production and fall apart. Latency spikes. Retrieval returns irrelevant chunks. Costs balloon when query volume scales. ...

18h ago3 min read

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#llm

Five Practical Tips to Save Token Consumption with Pochi

LLM Engineering 101: Mastering the Modern AI Stack

The Way of The Language Model Engineer

Engineering ResumeRoast: Security by Design

5 Hard-Learned Lessons from Building Production Agentic AI Systems

Aider: AI Pair Programming in Your Terminal

Llama vs Mistral vs Phi: Complete Open-Source LLM Comparison for Enterprise (2026)

Between Simulation and Emergence: The Identity Problem in Large Language Models

Fine-tuning vs RAG: When to Use Each Approach for Production LLMs

Building Production-Ready RAG Applications with Vector Databases

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#llm

Five Practical Tips to Save Token Consumption with Pochi

LLM Engineering 101: Mastering the Modern AI Stack

The Way of The Language Model Engineer

Engineering ResumeRoast: Security by Design

5 Hard-Learned Lessons from Building Production Agentic AI Systems

Aider: AI Pair Programming in Your Terminal

Llama vs Mistral vs Phi: Complete Open-Source LLM Comparison for Enterprise (2026)

Between Simulation and Emergence: The Identity Problem in Large Language Models

Fine-tuning vs RAG: When to Use Each Approach for Production LLMs

Building Production-Ready RAG Applications with Vector Databases