// LLM & Language Models

Multimodal LLMs: Working With Text, Images, and Audio Together

Multimodal LLMs process text, images, audio, and video in a single model, enabling use cases like document analysis, chart understanding, and audio transcription without separate pipelines.

May 17, 2026

7 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// LLM & Language Models

When to Fine-Tune an LLM (And When Not To)

The most common fine-tuning mistake is using it to inject knowledge. Fine-tuning changes style and behavior, not what the model knows. Prompting should always come first.

May 17, 2026

7 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// LLM & Language Models

Using LLMs for Data Analysis: What Works and What Doesn't

LLMs excel at writing SQL and pandas code for data analysis, but they cannot reliably calculate over large datasets. The correct model: LLMs write code, computers run it.

May 17, 2026

7 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// LLM & Language Models

LLM API Rate Limits: What They Are and How to Handle Them

LLM API rate limits enforce per-minute token and request caps. Exponential backoff with jitter, request queuing, and caching are the standard strategies for handling them gracefully.

May 17, 2026

5 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// Prompt Engineering

Prompt Engineering Complete Guide 2026: Every Technique That Actually Works

Every major prompt engineering technique with real before-and-after examples. Zero-shot, CoT, system prompts, RAG, ReAct, and what does not work despite the hype.

May 17, 2026

17 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// Prompt Engineering

Role Prompting: How to Use Personas to Get Better LLM Outputs

Role prompting assigns a persona to the model to shift its responses toward domain-specific language and reasoning. When it helps, when it backfires, and real before-and-after examples.

May 17, 2026

8 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// Prompt Engineering

Getting Structured Output From LLMs: JSON, XML, and Format Control

Getting reliable structured output from LLMs requires more than asking for JSON. Three methods from least to most reliable, with real prompt examples and failure modes for each.

May 17, 2026

9 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// Prompt Engineering

Prompt Chaining: How to Break Complex Tasks Into Reliable Steps

Prompt chaining passes the output of one LLM call as input to the next. Four patterns with real examples, and when chaining is worth the complexity vs. a single prompt.

May 17, 2026

9 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// Prompt Engineering

Self-Consistency Prompting: How to Improve Accuracy Through Multiple Samples

Self-consistency runs the same prompt multiple times and takes the majority answer. Wang et al. showed 5-40% accuracy improvements on reasoning tasks. When the cost is worth it.

May 17, 2026

8 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// Prompt Engineering

Prompt Injection Attacks: What They Are and How to Prevent Them

Prompt injection is when malicious input overrides your system prompt. Two attack types, documented real-world examples, and five defense strategies ranked by effectiveness.

May 17, 2026

6 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// Prompt Engineering

Prompting for Code Generation: Techniques That Actually Improve Output Quality

Code prompting is different because outputs are verifiably correct or wrong. Six techniques that consistently improve code quality, with specific examples and the most underused application.

May 17, 2026

9 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

// Prompt Engineering

Tree of Thought Prompting: When to Use It and When It's Overkill

Tree of Thought has the model explore multiple reasoning paths and pick the best. Yao et al. 2023 showed significant gains on hard problems. Most tasks don't need it - here's when they do.

May 17, 2026

8 min read

Mahmudul Haque Qudrati

CEO & ML Engineer

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Recent Articles

Multimodal LLMs: Working With Text, Images, and Audio Together

When to Fine-Tune an LLM (And When Not To)

Using LLMs for Data Analysis: What Works and What Doesn't

LLM API Rate Limits: What They Are and How to Handle Them

Prompt Engineering Complete Guide 2026: Every Technique That Actually Works

Role Prompting: How to Use Personas to Get Better LLM Outputs

Getting Structured Output From LLMs: JSON, XML, and Format Control

Prompt Chaining: How to Break Complex Tasks Into Reliable Steps

Self-Consistency Prompting: How to Improve Accuracy Through Multiple Samples

Prompt Injection Attacks: What They Are and How to Prevent Them

Prompting for Code Generation: Techniques That Actually Improve Output Quality

Tree of Thought Prompting: When to Use It and When It's Overkill